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2,931 results on '"Bordeaux population health (BPH)"'

101. CD4/CD8 Ratio and the Risk of Kaposi Sarcoma or Non-Hodgkin Lymphoma in the Context of Efficiently Treated Human Immunodeficiency Virus (HIV) Infection: A Collaborative Analysis of 20 European Cohort Studies

Author: Caby, F., Guiguet, M., Weiss, L., Winston, A. d., Miro, J. M., Konopnicki, D., Le Moing, V., Bonnet, F. h., Reiss, P., Mussini, C., Poizot-Martin, I., Taylor, N. l., Skoutelis, A., Meyer, L., Goujard, C., Bartmeyer, B., Boesecke, C., Antinori, A., Quiros-Roldan, E., Wittkop, L., Frederiksen, C., Castagna, A., Thurnheer, M. C., Svedhem, V., Jose, S., Costagliola, D., Mary-Krause, M., Grabar, S., Judd, A., Zangerle, R., Touloumi, G., Warszawski, J., Dabis, F., Krause, M. M., Ghosn, J., Leport, C., Wit, F., Prins, M., Bucher, H., Gibb, D., Fätkenheuer, G., Del Amo, J., Obel, N., Thorne, C., Mocroft, A., Kirk, O., Stephan, C., Pérez-Hoyos, S., Hamouda, O., Chkhartishvili, N., Noguera-Julian, A., Monforte, A. D., Brockmeyer, N., Prieto, L., Conejo, P. R., Soriano-Arandes, A., Battegay, M., Kouyos, R., Casabona, J., Miró, J. M., Konopnick, D., Goetghebuer, T., Sönnerborg, A., Torti, C., Sabin, C., Teira, R., Garrido, M., Haerry, D., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Victor Dupouy, Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Hôpital Hôtel-Dieu [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Imperial College London, University of Barcelona, Université libre de Bruxelles (ULB), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], University of Amsterdam [Amsterdam] (UvA), Università degli Studi di Modena e Reggio Emilia = University of Modena and Reggio Emilia (UNIMORE), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Sainte-Marguerite [CHU - APHM] (Hôpitaux Sud ), Paracelsus Medizinische Privatuniversität = Paracelsus Medical University (PMU), Evangelismos Athens General Hospital, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Hôpital Bicêtre, Robert Koch Institute [Berlin] (RKI), University Hospital Bonn, National Institute for Infectious Diseases 'Lazzaro Spallanzani', Università degli Studi di Brescia = University of Brescia (UniBs), Team MORPH3EUS (INSERM U1219 - UB - ISPED), University of Copenhagen = Københavns Universitet (UCPH), IRCCS Ospedale San Raffaele [Milan, Italy], Bern University Hospital [Berne] (Inselspital), Karolinska Institutet [Stockholm], Public Health England [London], Hôpital Cochin [AP-HP], Agence Nationale de Recherches sur le Sida et les Hépatites Virales, (CD4/CD8 ratio and cancer risk) project Working Group for the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) in EuroCoord: Ali Judd, Robert Zangerle, Giota Touloumi, Josiane Warszawski, Laurence Meyer, François Dabis, Murielle Mary Krause, Jade Ghosn, Catherine Leport, Linda Wittkop, Peter Reiss, Ferdinand Wit, Maria Prins, Heiner Bucher, Diana Gibb, Gerd Fätkenheuer, Julia Del Amo, Niels Obel, Claire Thorne, Amanda Mocroft, Ole Kirk, Christoph Stephan, Santiago Pérez-Hoyos, Osamah Hamouda, Barbara Bartmeyer, Nikoloz Chkhartishvili, Antoni Noguera-Julian, Andrea Antinori, Antonella d'Arminio Monforte, Norbert Brockmeyer, Luis Prieto, Pablo Rojo Conejo, Antoni Soriano-Arandes, Manuel Battegay, Roger Kouyos, Cristina Mussini, Jordi Casabona, Jose M Miró, Antonella Castagna, Deborah Konopnick, Tessa Goetghebuer, Anders Sönnerborg, Carlo Torti, Caroline Sabin, Ramon Teira, Myriam Garrido, David Haerry, European Project: 287519, European Project: 260694,EC:FP7:HEALTH,FP7-HEALTH-2010-single-stage,EUROCOORD(2011), Admin, Oskar, European Union Seventh Framework Programme - 287519 - INCOMING, European Network of HIV/AIDS Cohort Studies to Coordinate at European and International Level Clinical Research on HIV/AIDS - EUROCOORD - - EC:FP7:HEALTH2011-01-01 - 2015-12-31 - 260694 - VALID, Caby, Fabienne, Guiguet, Marguerite, Weiss, Laurence, Winston, Alan, Miro, Jose M, Konopnicki, Deborah, Le Moing, Vincent, Bonnet, Fabrice, Reiss, Peter, Mussini, Cristina, Poizot-Martin, Isabelle, Taylor, Ninon, Skoutelis, Athanasio, Meyer, Laurence, Goujard, Cécile, Bartmeyer, Barbara, Boesecke, Christoph, Antinori, Andrea, Quiros-Roldan, Eugenia, Wittkop, Linda, Frederiksen, Casper, Castagna, Antonella, Thurnheer, Maria Christine, Svedhem, Veronica, Jose, Sophie, Costagliola, Dominique, Mary-Krause, Murielle, Grabar, Sophie, Global Health, Infectious diseases, AII - Infectious diseases, and APH - Aging & Later Life
Subjects: CD4/CD8 ratio, CD8 T-cells, Kaposi sarcoma, efficient cART, non-Hodgkin lymphoma, 0301 basic medicine, Microbiology (medical), Lymphoma, [SDV]Life Sciences [q-bio], 030106 microbiology, CD4-CD8 Ratio, Non-Hodgkin, HIV Infections, Kaposi, Efficient cART, Drug resistance, HIV superinfection, CD8-Positive T-Lymphocytes, medicine.disease_cause, Men who have sex with men, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, CD4 Lymphocyte Count, HIV, Humans, Incidence, Risk Factors, Lymphoma, Non-Hodgkin, Sarcoma, Kaposi, immune system diseases, Medicine, 030212 general & internal medicine, Non-Hodgkin lymphoma, Transmission (medicine), business.industry, Sarcoma, Resistance mutation, 3. Good health, Infectious Diseases, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Superinfection, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, Viral load, HIV drug resistance, Demography
Abstract: BackgroundA persistently low CD4/CD8 ratio has been reported to inversely correlate with the risk of non-AIDS defining cancer in people living with human immunodeficiency virus (HIV; PLWH) efficiently treated by combination antiretroviral therapy (cART). We evaluated the impact of the CD4/CD8 ratio on the risk of Kaposi sarcoma (KS) or non-Hodgkin lymphoma (NHL), still among the most frequent cancers in treated PLWH.MethodsPLWH from the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) were included if they achieved virological control (viral load ≤ 500 copies/mL) within 9 months following cART and without previous KS/LNH diagnosis. Cox models were used to identify factors associated with KS or NHL risk, in all participants and those with CD4 ≥ 500/mm3 at virological control. We analyzed the CD4/CD8 ratio, CD4 count and CD8 count as time-dependent variables, using spline transformations.ResultsWe included 56 708 PLWH, enrolled between 2000 and 2014. At virological control, the median (interquartile range [IQR]) CD4 count, CD8 count, and CD4/CD8 ratio were 414 (296–552)/mm3, 936 (670–1304)/mm3, and 0.43 (0.28–0.65), respectively. Overall, 221 KS and 187 NHL were diagnosed 9 (2–37) and 18 (7–42) months after virological control. Low CD4/CD8 ratios were associated with KS risk (hazard ratio [HR] = 2.02 [95% confidence interval {CI } = 1.23–3.31]) when comparing CD4/CD8 = 0.3 to CD4/CD8 = 1) but not with NHL risk. High CD8 counts were associated with higher NHL risk (HR = 3.14 [95% CI = 1.58–6.22]) when comparing CD8 = 3000/mm3 to CD8 = 1000/mm3). Similar results with increased associations were found in PLWH with CD4 ≥ 500/mm3 at virological control (HR = 3.27 [95% CI = 1.60–6.56] for KS; HR = 5.28 [95% CI = 2.17–12.83] for NHL).ConclusionsLow CD4/CD8 ratios and high CD8 counts despite effective cART were associated with increased KS/NHL risks respectively, especially when CD4 ≥ 500/mm3.
Published: 2021

102. Performance en classification de données textuelles des passages aux urgences des modèles BERT pour le français

Author: Chenais, Gabrielle, Touchais, Hélène, Avalos, Marta, Bourdois, Loïck, Revel, Philippe, Gil-Jardiné, Cédric, Lagarde, Emmanuel, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), CHU de Bordeaux Pellegrin [Bordeaux], Journée organisée avec le soutien de l’Association française d’Informatique Médicale (AIM) et le Collège Science de l’Ingénierie des Connaissances de l’AFIA dans le cadre de la Plate-Forme Intelligence Artificielle (PFIA), and Avalos, Marta
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], SVM classification supervisée multi-classe, SVM, Natural Langage Processing, Urgences, [STAT.CO] Statistics [stat]/Computation [stat.CO], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], FlauBERT, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Artificial Intelligence, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Traitement automatique du langage, [STAT.CO]Statistics [stat]/Computation [stat.CO], CamemBERT, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], TF-IDF, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], multi-class classification, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Emergency, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: Contextualized language models based on the Transformer architecture such as BERT (Bidirectional Encoder Representations from Transformers) have achieved remarkable performances in various language processing tasks. CamemBERT and FlauBERT are pre-trained versions for French.We used these two models to automatically classify free clinical notes from emergency department visits following a trauma. Their performances were compared to the TF-IDF (Term-Frequency - Inverse Document Frequency) method associated with the SVM (Support Vector Machine) classifier on 22481 clinical notes from the emergency department of the Bordeaux University Hospital. CamemBERT and FlauBERT obtained slightly better results than the TF-IDF/SVM couple for the micro F1-score. These encouraging results allow us to consider further developments in the use of transformers in the automation of emergency department data processing in order to consider the implementation of a national observatory of trauma in France., Les modèles de langue contextualisés basés sur l'architecture Transformer tels que BERT (Bidirectional Encoder Representations from Transformers) ont atteint des performances remarquables dans des diverses tâches de traitement de la langue. CamemBERT et FlauBERT en sont des versions pré-entraînées pour le français. Nous avons utilisé ces deux modèles afin de classer automatiquement des notes cliniques libres issues de visites aux urgences à la suite d'un traumatisme. Leurs performances ont été comparées à la méthode TF-IDF (Term-Frequency-Inverse Document Frequency) associé au classifieur SVM (Support Vector Machine) sur 22481 notes cliniques provenant du service des urgences du CHU de Bordeaux. CamemBERT et FlauBERT ont obtenu des résultats légèrement supérieurs à ceux du couple TF-IDF/SVM pour le micro F1-score. Ces résultats encourageants permettent d'envisager l'utilisation des transformers pour automatiser le traitement des données des urgences dans le cadre de la mise en place d'un observatoire national du traumatisme en France.
Published: 2021

103. Traitement automatique des résumés de passages aux urgences : focus sur la désidentification

Author: Bourdois, Loïck, Avalos, Marta, Chenais, Gabrielle, Contrand, Benjamin, Gil-Jardiné, Cédric, Guennec-Jacques, Antoine, Revel, Philippe, Thiessard, Frantz, Touchais, Hélène, Lagarde, Emmanuel, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), CHU de Bordeaux Pellegrin [Bordeaux], Journée organisée avec le soutien de l’Association française d’Informatique Médicale (AIM) et le Collège Science de l’Ingénierie des Connaissances de l’AFIA dans le cadre de la Plate-Forme Intelligence Artificielle (PFIA), and Avalos, Marta
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], French, Natural Langage Processing, Urgences, Emergency room, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [STAT.CO] Statistics [stat]/Computation [stat.CO], Pré-entraînement, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Français, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [STAT.AP] Statistics [stat]/Applications [stat.AP], Pre-training, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Transformers, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Traitement automatique du langage, [STAT.CO]Statistics [stat]/Computation [stat.CO], [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: In France, structured data on emergency room visits are aggregated at the national level to build a syndromic surveillance system for different health events. For visits motivated by a traumatic event, information on the circumstances is stored in free text clinical notes. Automating the processing of these notes should allow the enrichment of surveillance tools. In development at Inserm and the Emergency Department of the Bordeaux University Hospital, The TARPON (for Automatic Processing of Emergency Room Notes for a National Observatory, in French) project aims to meet this objective by using the latest deep learning tools applied to automatic language analysis. To exploit these data, an automatic de-identification system, guaranteeing the protection of personal data, is necessary. We present here a comparison study of models allowing the de-identification of clinical texts in French., En France, les données structurées concernant les visites aux urgences sont agrégées au niveau national pour construire un système de surveillance syndromique de différents événements de santé. Pour les visites motivées par un événement traumatique, les informations sur les circonstances sont stockées dans des notes cliniques en texte libre. Automatiser le traitement de ces notes devrait permettre l'enrichissement des outils de surveillance. En développement à l'Inserm et au Service des urgences du CHU de Bordeaux, le projet TARPON (Traitement Automatique des Résumés de Passages aux urgences pour un Observatoire National) vise à répondre à cet objectif par le biais des derniers outils d'apprentissage profond appliqués à l'analyse automatique du langage. Pour exploiter ces données, un système de désidentification automatique, garantissant la protection des données personnelles est nécessaire. Nous présentons ici une étude de comparaison de modèles permettant la désidentification des textes cliniques en français.
Published: 2021

104. Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis

Author: Boris P. Hejblum, Rodolphe Thiébaut, Denis Agniel, Marine Gauthier, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Hejblum, Boris
Subjects: 0303 health sciences, Computer science, Design of experiments, Cumulative distribution function, Asymptotic distribution, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Resampling, Covariate, Test statistic, Benchmark (computing), [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], 0101 mathematics, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Algorithm, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], 030304 developmental biology, Statistical hypothesis testing
Abstract: SummaryState-of-the-art methods for single-cell RNA sequencing (scRNA-seq) Differential Expression Analysis (DEA) often rely on strong distributional assumptions that are difficult to verify in practice. Furthermore, while the increasing complexity of clinical and biological single-cell studies calls for greater tool versatility, the majority of existing methods only tackle the comparison between two conditions. We propose a novel, distribution-free, and flexible approach to DEA for single-cell RNA-seq data. This new method, called ccdf, tests the association of each gene expression with one or many variables of interest (that can be either continuous or discrete), while potentially adjusting for additional covariates. To test such complex hypotheses, ccdf uses a conditional independence test relying on the conditional cumulative distribution function, estimated through multiple regressions. We provide the asymptotic distribution of the ccdf test statistic as well as a permutation test (when the number of observed cells is not sufficiently large). ccdf substantially expands the possibilities for scRNA-seq DEA studies: it obtains good statistical performance in various simulation scenarios considering complex experimental designs (i.e. beyond the two condition comparison), while retaining competitive performance with state-of-the-art methods in a two-condition benchmark. We apply ccdf to a large publicly available scRNA-seq dataset of 84,140 SARS-CoV-2 reactive CD8+ T cells, in order to identify the diffentially expressed genes across 3 groups of COVID-19 severity (mild, hospitalized, and ICU) while accounting for seven different cellular subpopulations.
Published: 2021

105. De-identification of Emergency Medical Records in French: Survey and Comparison of State-of-the-Art Automated Systems

Author: Emmanuel Lagarde, Marta Avalos, Frantz Thiessard, Loick Bourdois, Cédric Gil-Jardiné, Philippe Revel, Gabrielle Chenais, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), CHU de Bordeaux Pellegrin [Bordeaux], and Avalos, Marta
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Healthcare Informatics, French, Computer science, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing, Low-resource languages, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], computer.software_genre, Health informatics, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Resource (project management), [STAT.AP] Statistics [stat]/Applications [stat.AP], Named-entity recognition, Pre-training, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Transformers, Protected health information, Injury epidemiology, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Information retrieval, business.industry, Event (computing), Medical record, De-identification, Emergency room, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], 3. Good health, Applied Natural Language Processing, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Test set, NER, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, computer, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: International audience; In France, structured data from emergency room (ER) visits are aggregated at the national level to build a syndromic surveillance system for several health events. For visits motivated by a traumatic event, information on the causes are stored in free-text clinical notes. To exploit these data, an automated de-identification system guaranteeing protection of privacy is required.In this study we review available de-identification tools to de-identify free-text clinical documents in French. A key point is how to overcome the resource barrier that hampers NLP applications in languages other than English. We compare rule-based, named entity recognition, new Transformer-based deep learning and hybrid systems using, when required, a fine-tuning set of 30,000 unlabeled clinical notes. The evaluation is performed on a test set of 3,000 manually annotated notes.Hybrid systems, combining capabilities in complementary tasks, show the best performance. This work is a first step in the foundation of a national surveillance system based on the exhaustive collection of ER visits reports for automated trauma monitoring.
Published: 2021

106. Effects of a physical activity programme to prevent physical performance decline in onco‐geriatric patients: a randomized multicentre trial

Author: Aline Maillard, Brigitte Maget, Alban Rieger, Sophie C. Regueme, Rodolphe Thiébaut, Sandrine Lavau-Denes, Jessica Durrieu, Christophe Laurent, Eric Terrebonne, Haritz Arrieta, V. Servent, Cyril Astrugue, Marianne Fonck, Jérôme Dauba, Isabelle Bourdel-Marchasson, Centre de résonance magnétique des systèmes biologiques (CRMSB), Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB), CHU Bordeaux [Bordeaux], Institut Jean Godinot [Reims], UNICANCER, Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université Lille Nord de France (COMUE)-UNICANCER, CHU Limoges, CHU Mont de Marsan, Institut Bergonié [Bordeaux], Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), and Université de Lille-UNICANCER
Subjects: 0301 basic medicine, Male, lcsh:Diseases of the musculoskeletal system, 0302 clinical medicine, Breast cancer, Quality of life, Weight loss, Neoplasms, Orthopedics and Sports Medicine, older-adults, 2. Zero hunger, Aged, 80 and over, Frailty, style intervention, Incidence, [SDV.MHEP.GEG]Life Sciences [q-bio]/Human health and pathology/Geriatry and gerontology, Age Factors, lcsh:Human anatomy, Physical Functional Performance, University hospital, 3. Good health, Hospitalization, nutrition, adapted physical activity, 030220 oncology & carcinogenesis, activity intervention, Female, Original Article, medicine.symptom, weight-loss, medicine.medical_specialty, Physical activity, [SDV.CAN]Life Sciences [q-bio]/Cancer, frailty, cachexia, lcsh:QM1-695, 03 medical and health sciences, breast cancer, Physiology (medical), medicine, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Humans, cancer survivors, Exercise, Geriatric Assessment, breast-cancer, Onco-geriatrics, Aged, Nutrition, business.industry, Adapted physical activity, Original Articles, medicine.disease, onco-geriatrics, Onco‐geriatrics, practical tool, Gait speed, 030104 developmental biology, Clinical research, Socioeconomic Factors, Physical performance, quality-of-life, Physical therapy, Accidental Falls, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, lcsh:RC925-935, business, gait speed
Abstract: BACKGROUND: Older adults with cancer experience negative long-term functional effects of both cancer and treatments. Exercise may minimize their age-related and cancer-related functional decline. METHODS: We conducted a multicentre open-label 12month randomized clinical trial with two parallel arms including participants aged ≥70years with lymphoma or carcinoma requiring curative treatment. The study started at the beginning of any phase of cancer treatment (surgery, chemotherapy, or radiotherapy). The usual care group (UCG) received the current national recommendations in physical activity (a guideline without specific counselling). The intervention group (IG) received 1year phoned physical activity advice individually adapted to physical assessment (twice a month during the first 6months and then monthly). The primary outcome was the proportion of subjects with a 1year decreased short physical performance battery (SPPB) score of 1 point or more. Physical, cognitive, and clinical secondary outcomes were also investigated. RESULTS: We allocated 301 participants (age 76.7±5.0, female 60.6%) to each group. At baseline, the median SPPB was 10/12 in both groups. Breast was the most frequent tumour site (35.7%). After 1year, 14.0% of participants in the UCG and 18.7% in the IG had a decrease in SPPB score of 1 point or more (P=0.772). At 2years, there was no difference in SPPB, gait speed, International Physical Activity Questionnaire score, and verbal fluency. Subgroup analyses after 2years showed a decline in SPPB for 29.8% of UCG and 5.0% of IG breast cancer participants (P=0.006), in 21.7% of UCG and 6.2% of IG female participants (P=0.019), and in 24.5% of UCG and 11.1% of IG normal nutritional status participants (P=0.009). Falls, hospitalization, institutionalization, and death rates were similar in both groups. CONCLUSIONS: Personalized phoned physical activity advice had not reduced functional decline at 1year but provided preliminary evidence that may prevent physical performance decline at 2years in older adults with breast cancer. © 2019 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of the Society on Sarcopenia, Cachexia and Wasting Disorders. This work was funded by the National Hospital Program of Clinical Research (Programme Hospitalier de Recherche Clinique 2010) and sponsored by the University Hospital of Bordeaux (CHU Bordeaux). Haritz Arrieta was supported by a fellowship from University of the Basque Country (UPV/EHU).
Published: 2019

107. The IeDEA harmonist data toolkit: A data quality and data sharing solution for a global HIV research consortium

Author: Lewis, Judith T., Stephens, Jeremy, Musick, Beverly, Brown, Steven, Malateste, Karen, Ha Dao Ostinelli, Cam, Maxwell, Nicola, Jayathilake, Karu, Shi, Qiuhu, Brazier, Ellen, Kariminia, Azar, Hogan, Brenna, Duda, Stephany N., Vanderbilt University [Nashville], Vanderbilt University Medical Center [Nashville], Indiana University - Purdue University Indianapolis (IUPUI), Indiana University System, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Bern, University of Cape Town, New York Medical College (NYMC), City University of New York [New York] (CUNY), The Kirby Institute for Infection and Immunity in Society (UNSW), University of New South Wales [Sydney] (UNSW), Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), Vanderbilt University School of Medicine [Nashville], Admin, Oskar, Global Health in the Global South (GHiGS), Institut de Recherche pour le Développement (IRD)- Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Global health, HIV Infections, 610 Medicine & health, Health Informatics, Article, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, 360 Social problems & social services, Humans, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [SDV.IB] Life Sciences [q-bio]/Bioengineering, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Information Dissemination, Data Collection, Data quality, Data harmonization, HIV, Data Accuracy, Computer Science Applications, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Biomedical informatics, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Software
Abstract: International audience; We describe the design, implementation, and impact of a data harmonization, data quality checking, and dynamic report generation application in an international observational HIV research network. The IeDEA Harmonist Data Toolkit is a web-based application written in the open source programming language R, employs the R/Shiny and RMarkdown packages, and leverages the REDCap data collection platform for data model definition and user authentication. The Toolkit performs data quality checks on uploaded datasets, checks for conformance with the network's common data model, displays the results both interactively and in downloadable reports, and stores approved datasets in secure cloud storage for retrieval by the requesting investigator. Including stakeholders and users in the design process was key to the successful adoption of the application. A survey of regional data managers as well as initial usage metrics indicate that the Toolkit saves time and results in improved data quality, with a 61% mean reduction in the number of error records in a dataset. The generalized application design allows the Toolkit to be easily adapted to other research networks.
Published: 2022

108. Development of a Questionnaire for the Search for Occupational Causes in Patients with Non-Hodgkin Lymphoma: The RHELYPRO Study

Author: Matrat, M. (Mireille), Gain, M. (Murielle), Haioun, C. (Corinne), Le Bras, F. (Fabien), Nisse, C. (Catherine), Morschhauser, F. (Franck), Clin, B. (Benedicte), Baldi, I. (Isabelle), Verdun-Esquer, C. (Catherine), Garnier, R. (Robert), Laborde-Casterot, H. (Herve), Herin, F. (Fabrice), Esquirol, Y. (Yolande), Andujar, P. (Pascal), Belacel, M. (Milia), Chouaid, C. (Christos), Chauvet, C. (Claire), Lasfargues, G. (Gerard), Pairon, J-C. (Jean-Claude), Pairon, CHU Lille, Institut Pasteur de Lille, Université de Lille, Centre Hospitalier Intercommunal de Créteil [CHIC], IMPact de l'Environnement Chimique sur la Santé humaine (IMPECS) - ULR 4483, Groupe de Recherche sur les formes Injectables et les Technologies Associées (GRITA) - ULR 7365, Hôpital Henri Mondor, Institut Mondor de Recherche Biomédicale [IMRB], Unité de recherche interdisciplinaire pour la prévention et le traitement des cancers [ANTICIPE], Bordeaux population health [BPH], Hôpital Lariboisière-Fernand-Widal [APHP], Institut Mondor de recherche biomédicale [IMRB], Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail [ANSES], CHI Créteil, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Impact de l'environnement chimique sur la santé humaine - ULR 4483 (IMPECS), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Groupe de Recherche sur les formes Injectables et les Technologies Associées - ULR 7365 (GRITA), Unité de recherche interdisciplinaire pour la prévention et le traitement des cancers (ANTICIPE), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), Normandie Université (NU)-UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-UNICANCER-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Institut Santé-Travail Paris-Est [Créteil], Université Paris-Est Créteil, Faculté de Médecine [Créteil] (UPEC-Médecine), Centre de Recherche Clinique [Créteil] (CRC), Centre Hospitalier Intercommunal de Créteil (CHIC), IMRB - CEPIA/'Clinical Epidemiology And Ageing : Geriatrics, Primary Care and Public Health' [Créteil] (U955 Inserm - UPEC), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Direction des alertes et des vigilances sanitaires (DAVS), Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES), Anses (2015-CRD-29, 2018-CRD-20), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Régional de Lutte contre le Cancer François Baclesse [Caen] (UNICANCER/CRLC), UNICANCER-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-UNICANCER, CHU Toulouse [Toulouse], and Admin, Oskar
Subjects: [SDV.MHEP.HEM] Life Sciences [q-bio]/Human health and pathology/Hematology, Male, Health, Toxicology and Mutagenesis, Chronic lymphocytic leukemia, lcsh:Medicine, Disease, 0302 clinical medicine, immune system diseases, Risk Factors, hemic and lymphatic diseases, Surveys and Questionnaires, Non-Hodgkin lymphoma, Occupational disease, Exposure to solvents, Exposure to pesticides, Workers’ compensation, Multiple myeloma, Lymphoma, Non-Hodgkin, [SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/Hematology, Middle Aged, 030210 environmental & occupational health, 3. Good health, Occupational Diseases, 030220 oncology & carcinogenesis, medicine.medical_specialty, Workers' compensation, [SDV.CAN]Life Sciences [q-bio]/Cancer, Article, 03 medical and health sciences, [SDV.CAN] Life Sciences [q-bio]/Cancer, Internal medicine, Occupational Exposure, medicine, [SDV.EE.SANT] Life Sciences [q-bio]/Ecology, environment/Health, Humans, In patient, [SDV.EE.SANT]Life Sciences [q-bio]/Ecology, environment/Health, business.industry, lcsh:R, Public Health, Environmental and Occupational Health, medicine.disease, Leukemia, Lymphocytic, Chronic, B-Cell, Lymphoma, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Case-Control Studies, Hodgkin lymphoma, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business
Abstract: Non-Hodgkin lymphoma (NHL), multiple myeloma and chronic lymphocytic leukemia are possibly related to environmental and/or occupational exposure. The primary objective of this study was to develop a questionnaire for screening patients with these blood disorders who might benefit from a specialized consultation for possible recognition of the disease as an occupational disease. The study included 205 subjects (male gender, 67.3%, mean age, 60 years, NHL, 78.5%). The questionnaire performed very satisfactorily in identifying the exposures most frequently retained by experts for their potential involvement in the occurrence of NHL. Its sensitivity and specificity in relation to the final expertise were 96% and 96% for trichloroethylene, 85% and 82% for benzene, 78% and 87% for solvents other than trichloroethylene and dichloromethane, 87% and 95% for pesticides, respectively. Overall, 15% of the subjects were invited to ask National Social Insurance for compensation as occupational disease. These declarations concerned exposure to pesticides (64%), solvents (trichloroethylene: 29%, benzene: 18%, other than chlorinated solvents: 18%) and sometimes multiple exposures. In conclusion, this questionnaire appears as a useful tool to identify NHL patients for a specialized consultation, in order to ask for compensation for occupational disease.
Published: 2021

109. Cohort profile: MAVIE a web-based prospective cohort study of home, leisure, and sports injuries in France

Author: Castro, Madelyn Yiseth Rojas, Orriols, Ludivine, Contrand, Benjamin, Dupuy, Marion, Sztal-Kutas, Catherine, Avalos, Marta, Lagarde, Emmanuel, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Calyxis Pôle d'Expertise des Risques, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Avalos, Marta
Subjects: Male, Epidemiology, Health Status, Geographical locations, [STAT.AP] Statistics [stat]/Applications [stat.AP], Risk Factors, Surveys and Questionnaires, Medicine and Health Sciences, Public and Occupational Health, Longitudinal Studies, Prospective Studies, Computer Networks, Child, Data Management, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Traumatic Injury Risk Factors, Middle Aged, Mobile Applications, Sports Science, Socioeconomic Aspects of Health, Europe, Child, Preschool, Athletic Injuries, Medicine, Female, France, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Research Article, Adult, Computer and Information Sciences, Adolescent, Science, Young Adult, Leisure Activities, Mental Health and Psychiatry, Humans, European Union, Sports and Exercise Medicine, Aged, Internet, Infant, Newborn, Biology and Life Sciences, Infant, Health Care, Accidents, Home, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Medical Risk Factors, Wounds and Injuries, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, People and places
Abstract: International audience; MAVIE is a web-based prospective cohort study of Home, Leisure, and Sports Injuries with a longitudinal follow-up of French general population volunteers. MAVIE participants are voluntary members of French households, including overseas territories. Participation in the cohort involves answering individual and household questionnaires and relevant exposures and prospectively reporting injury events during the follow-up. Recruitment and data collection have been in progress since 2014. The number of participants as of the end of the year 2019 was 12,419 from 9,483 households. A total of 8,640 participants provided data during follow-up. Respondents to follow-up were composed of 763 children aged 0–14, 655 teenagers and young adults aged 15–29, 6,845 adults, and 377 people aged 75 or more. At the end of the year 2019, 1,698 participants had reported 2,483 injury events. Children, people aged 50 and more, people with poor self-perceived physical and mental health, people who engage in sports activities, and people with a history of injury during the year before recruitment were more likely to report new injuries. An interactive mobile/web application (MAVIE-Lab) was developed to help volunteers decide on personalized measures to prevent their risks of HLIs. The available data provides an opportunity to analyse multiple exposures at both the individual and household levels that may be associated with an increased risk of trauma. The ongoing analysis includes HLI incidence estimates, the determination of health-related risk factors, a specific study on the risk of home injury, another on sports injuries, and an analysis of the role of cognitive skills and mind wandering. Volunteers form a community that constitutes a population laboratory for preventative initiatives.
Published: 2021

110. Mobile technology as a health literacy enabler in African rural areas: a literature review

Author: Ismaila Ouedraogo, Borlli Michel Jonas Some, Gayo Diallo, Roland Benedikter, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Polytechnique Nazi Boni Bobo-Dioulasso (UNB), European Academy Bozen/Bolzano (EURAC), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), IO is supported with a PhD scholarship from the Government of Burkina Faso. The study is also supported by the PATIENT-Covid19 project. Thus we would like to thank the Agence Universitaire de la Francophonie (AUF) and theCovid mission of University of Bordeaux, and Diallo, Gayo
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Knowledge management, 020205 medical informatics, business.industry, 1. No poverty, Health literacy, 02 engineering and technology, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 03 medical and health sciences, 0302 clinical medicine, Enabling, Political science, 0202 electrical engineering, electronic engineering, information engineering, Mobile technology, 030212 general & internal medicine, Rural area, InformationSystems_MISCELLANEOUS, business
Abstract: Background: Since the launch of mobile phones three decade ago, the latter have been used to support healthcare systems through various mobile health (m-health) applications. In recent years, multiple mobile phone-based health projects and applications have emerged. Despite the great enthusiasm around m-health, few studies have examined the use of cell phones to improve health literacy in Africa. This paper aims to review studies related to the contribution of mobile technologies in improving health literacy in rural areas of Africa. Methods: We performed a four-step systematic review to identify relevant publications: (1) Database selection, (2) Keyword search, (3) Study selection and (4) Data extraction. In addition, manual searching methods were used to find keywords related to m-health initiatives in Africa. Discussion: Our search resulted in the identification of 38 studies and initiatives related to health literacy and mobile technologies in Africa. However, few of these studies focused on health literacy and mobile technologies in rural areas of Africa. We also found that m-health initiatives to date have not been inclusive, with very few integrating local languages in the development of m-health solutions. Our findings thus point to various potential avenues to be investigated in the future.
Published: 2021

111. Correction to: Evolution of body composition following successful kidney transplantation is strongly influenced by physical activity: results of the CORPOS study

Author: Moreau, Karine, Desseix, Aurélie, Germain, Christine, Merville, Pierre, Couzi, Lionel, Thiébaut, Rodolphe, Chauveau, Philippe, CHU Bordeaux [Bordeaux], Hôpital Pellegrin, CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and AURAD Aquitaine
Subjects: Male, 030232 urology & nephrology, Correction, Middle Aged, 030204 cardiovascular system & hematology, lcsh:Diseases of the genitourinary system. Urology, lcsh:RC870-923, Kidney Transplantation, 03 medical and health sciences, 0302 clinical medicine, Nephrology, Body Composition, Humans, Female, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Prospective Studies, Exercise, ComputingMilieux_MISCELLANEOUS
Abstract: Weight gain (mainly gain of fat mass) occurs quickly after successful kidney transplantation and is associated with metabolic complications (alterations of glycaemic control, hyperlipidaemia). Determinants of weight gain are multifactorial and are mainly related to the transplant procedure itself (glucocorticoid use, increased appetite). In the modern era of transplantation, one challenge is to limit these metabolic alterations by promoting gain of muscle mass rather than fat mass. This prospective study was performed to assess determinants of fat mass, fat-free mass and body cell mass changes after kidney transplantation with a focus on physical activity and nutritional behaviour before and after transplantation.Patients were included at the time of listing for deceased donor kidney transplantation. Body composition was determined using dual X-ray absorptiometry and bioimpedance spectroscopy to assess fat mass, fat-free mass and body cell mass (= fat-free mass - extracellular water) at the time of inclusion, 12 months later, and 1, 6, 12 and 24 months after transplantation. Recall dietary data and physical activity level were also collected.Eighty patients were included between 2007 and 2010. Sixty-five had a complete 24-month follow-up after kidney transplantation. Fat mass, fat-free mass and body cell mass decreased during the waiting period and early after kidney transplantation. The nadirs of body cell mass and fat-free mass occurred at 1 month and the nadir for fat mass occurred at 6 months. Maximum levels of all parameters of body composition were seen at 12 months, after which body cell mass and fat-free mass decreased, while fat mass remained stable. In multivariate analysis, male recipients, higher physical activity level and lower corticosteroid dose were significantly associated with better body cell mass recovery after kidney transplantation.Lifestyle factors, such as physical activity level, together with low dose of corticosteroids seem to influence body composition evolution following kidney transplantation with recovery of body cell mass. Specific strategies to promote physical activity in kidney transplant recipients should be provided before and after kidney transplantation.
Published: 2021

112. Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach

Author: Anthony Devaux, Robin Genuer, Karine Peres, Cécile Proust-Lima, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and DEVAUX, Anthony
Subjects: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine learning methods, Epidemiology, Individual prediction, Longitudinal data, Health Informatics, Machine Learning (stat.ML), [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], Machine Learning (cs.LG), Machine Learning, Landmark, Survival data, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistics - Machine Learning, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Humans, Computer Simulation, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Biomarkers, Aged
Abstract: Background The individual data collected throughout patient follow-up constitute crucial information for assessing the risk of a clinical event, and eventually for adapting a therapeutic strategy. Joint models and landmark models have been proposed to compute individual dynamic predictions from repeated measures to one or two markers. However, they hardly extend to the case where the patient history includes much more repeated markers. Our objective was thus to propose a solution for the dynamic prediction of a health event that may exploit repeated measures of a possibly large number of markers. Methods We combined a landmark approach extended to endogenous markers history with machine learning methods adapted to survival data. Each marker trajectory is modeled using the information collected up to the landmark time, and summary variables that best capture the individual trajectories are derived. These summaries and additional covariates are then included in different prediction methods adapted to survival data, namely regularized regressions and random survival forests, to predict the event from the landmark time. We also show how predictive tools can be combined into a superlearner. The performances are evaluated by cross-validation using estimators of Brier Score and the area under the Receiver Operating Characteristic curve adapted to censored data. Results We demonstrate in a simulation study the benefits of machine learning survival methods over standard survival models, especially in the case of numerous and/or nonlinear relationships between the predictors and the event. We then applied the methodology in two prediction contexts: a clinical context with the prediction of death in primary biliary cholangitis, and a public health context with age-specific prediction of death in the general elderly population. Conclusions Our methodology, implemented in R, enables the prediction of an event using the entire longitudinal patient history, even when the number of repeated markers is large. Although introduced with mixed models for the repeated markers and methods for a single right censored time-to-event, the technique can be used with any other appropriate modeling technique for the markers and can be easily extended to competing risks setting.
Published: 2021

113. NPJ Vaccines

Author: Wagstaffe, Helen R., Susannini, Giada, Thiébaut, Rodolphe, Richert, Laura, Lévy, Yves, Lévy, Yves, Bockstal, Viki, Stoop, Jeroen N., Luhn, Kerstin, Douoguih, Macaya, Riley, Eleanor M, Lacabaratz, Christine, Goodier, Martin R, London School of Hygiene and Tropical Medicine (LSHTM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Janssen Vaccines & Prevention [Leiden]
Subjects: viruses, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract: International audience; Natural killer (NK) cells are implicated among immune effectors after vaccination against viral pathogens, including Ebola virus. The two-dose heterologous Ebola virus vaccine regimen, adenovirus type 26.ZEBOV followed by modified vaccinia Ankara-BN-Filo (EBOVAC2 consortium, EU Innovative Medicines Initiative), induces NK cell activation and anti-Ebola glycoprotein (GP) antibody-dependent NK cell activation post-dose 1, which is further elevated post-dose 2. Here, in a multicentre, phase 2 clinical trial (EBL2001), we demonstrate durable ex vivo NK cell activation 180 days after dose 2, with responses enriched in CD56(bright) NK cells. In vitro antibody-dependent responses to immobilised Ebola GP increased after dose 1, and remained elevated compared to pre-vaccination levels in serum collected 180 days later. Peak NK cell responses were observed post-dose 2 and NK cell IFN-γ responses remained significantly elevated at 180 days post-dose 2. Individual variation in NK cell responses were influenced by both anti-Ebola GP antibody concentrations and intrinsic interindividual differences in NK cell functional capacity. In summary, this study demonstrates durable NK cell responses after Ad26.ZEBOV, MVA-BN-Filo Ebola virus vaccination and could inform the immunological evaluation of future iterations of the vaccine regimen and vaccination schedules.
Published: 2021

114. Early signature in the blood lipidome associated with subsequent cognitive decline in the elderly: A case-control analysis nested within the Three-City cohort study

Author: Sophie Lefèvre-Arbogast, Boris P Hejblum, Catherine Helmer, Christian Klose, Claudine Manach, Dorrain Y Low, Mireia Urpi-Sarda, Cristina Andres-Lacueva, Raúl González-Domínguez, Ludwig Aigner, Barbara Altendorfer, Paul J Lucassen, Silvie R Ruigrok, Chiara De Lucia, Andrea Du Preez, Cécile Proust-Lima, Sandrine Thuret, Aniko Korosi, Cécilia Samieri, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut de la Longevite, Structural and Functional Plasticity of the nervous system (SILS, FNWI), and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: lcsh:R5-920, lcsh:R, lcsh:Medicine, Serum biomarker, Metabòlits, Diet, Cognitive dysfunction, Lipidomics, Metabolites, Metabolomics, Dieta, Dementia, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Membrane lipids, lcsh:Medicine (General), Demència
Abstract: International audience; BACKGROUND: Brain lipid metabolism appears critical for cognitive aging, but whether alterations in the lipidome relate to cognitive decline remains unclear at the system level. METHODS: We studied participants from the Three-City study, a multicentric cohort of older persons, free of dementia at time of blood sampling, and who provided repeated measures of cognition over 12 subsequent years. We measured 189 serum lipids from 13 lipid classes using shotgun lipidomics in a case-control sample on cognitive decline (matched on age, sex and level of education) nested within the Bordeaux study center (discovery, n = 418). Associations with cognitive decline were investigated using bootstrapped penalized regression, and tested for validation in the Dijon study center (validation, n = 314). FINDINGS: Among 17 lipids identified in the discovery stage, lower levels of the triglyceride TAG50:5, and of four membrane lipids (sphingomyelin SM40:2,2, phosphatidylethanolamine PE38:5(18:1/20:4), ether-phosphatidylethanolamine PEO34:3(16:1/18:2), and ether-phosphatidylcholine PCO34:1(16:1/18:0)), and higher levels of PCO32:0(16:0/16:0), were associated with greater odds of cognitive decline, and replicated in our validation sample. INTERPRETATION: These findings indicate that in the blood lipidome of non-demented older persons, a specific profile of lipids involved in membrane fluidity, myelination, and lipid rafts, is associated with subsequent cognitive decline. FUNDING: The complete list of funders is available at the end of the manuscript, in the Acknowledgement section.
Published: 2021

115. Health Care Students’ Knowledge of and Attitudes, Beliefs, and Practices Toward the French COVID-19 App: Cross-sectional Questionnaire Study

Author: Montagni, Ilaria, Roussel, Nicolas, Thiébaut, Rodolphe, Tzourio, Christophe, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria), Statistics In System biology and Translational Medicine (SISTM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], Conseil Régional Aquitaine, Université de Bordeaux, The i-Share team is currently supported by an unrestricted grant of the Nouvelle-Aquitaine Regional Council (Conseil Régional Nouvelle-Aquitaine, grant no. 4370420) and by the Bordeaux Initiatives d’excellence program of the University of Bordeaux(ANR-10-IDEX-03-02). The team has also received grants from Public Health France (Santé Publique France, contract no.19DPPP023-0) and the Nouvelle-Aquitaine Regional Health Agency (Agence Régionale de Santé Nouvelle-Aquitaine)., and Admin, Oskar
Subjects: Practice, Monitoring, lcsh:Public aspects of medicine, Field survey, Communication, Mobile app, COVID-19, lcsh:RA1-1270, lcsh:Computer applications to medicine. Medical informatics, Knowledge, Contact tracing, Attitude, Belief, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, lcsh:R858-859.7, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Use, Students, App, Survey
Abstract: BackgroundMany countries worldwide have developed mobile phone apps capable of supporting instantaneous contact tracing to control the COVID-19 pandemic. In France, a few people have downloaded and are using the StopCovid contact tracing app. Students in the health domain are of particular concern in terms of app uptake. Exploring their use and opinions about the app can inform improvements and diffusion of StopCovid among young people. ObjectiveThe aim of this study is to investigate health care students’ knowledge of and attitudes, beliefs, and practices (KABP) toward the StopCovid app. MethodsA field survey was conducted among 318 students at the health sciences campus of the University of Bordeaux, France, between September 25 and October 16, 2020. A quota sampling method was used, and descriptive statistics and univariate analyses were performed. ResultsOf the 318 respondents, 77.3% (n=246) had heard about the app, but only 11.3% (n=36) had downloaded it, and 4.7% (n=15) were still using it at the time of the survey. Among the 210 participants who had heard about the app but did not download it, the main reasons for not using the app were a belief that it was not effective given its limited diffusion (n=37, 17.6%), a lack of interest (n=37, 17.6%), and distrust in the data security and fear of being geolocated (n=33, 15.7%). Among the 72 students who had not heard of the app and were given a brief description of its functioning and confidentiality policy, 52.7% (n=38) said they would use it. Participants reported that the main solution for increasing the use of the app would be better communication about it (227/318, 71.4%). ConclusionsEven among health students, the contact tracing app was poorly used. The findings suggest that improved communication about its advantages and simplicity of use as well as clarifying false beliefs about it could help improve uptake.
Published: 2021

116. Performance of BERT models for French in the classification of textual data from emergency room visits

Author: Chenais, Gabrielle, Touchais, Hélène, Avalos, Marta, Bourdois, Loïck, Revel, Philippe, Gil-Jardiné, Cédric, Lagarde, Emmanuel, Avalos, Marta, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), CHU de Bordeaux Pellegrin [Bordeaux], and Journée organisée avec le soutien de l’Association française d’Informatique Médicale (AIM) et le Collège Science de l’Ingénierie des Connaissances de l’AFIA dans le cadre de la Plate-Forme Intelligence Artificielle (PFIA)
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], SVM classification supervisée multi-classe, Natural Langage Processing, SVM, Urgences, [STAT.CO] Statistics [stat]/Computation [stat.CO], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], FlauBERT, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Artificial Intelligence, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, Traitement automatique du langage, [STAT.CO]Statistics [stat]/Computation [stat.CO], CamemBERT, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], TF-IDF, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], multi-class classification, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Emergency, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: Contextualized language models based on the Transformer architecture such as BERT (Bidirectional Encoder Representations from Transformers) have achieved remarkable performances in various language processing tasks. CamemBERT and FlauBERT are pre-trained versions for French.We used these two models to automatically classify free clinical notes from emergency department visits following a trauma. Their performances were compared to the TF-IDF (Term-Frequency - Inverse Document Frequency) method associated with the SVM (Support Vector Machine) classifier on 22481 clinical notes from the emergency department of the Bordeaux University Hospital. CamemBERT and FlauBERT obtained slightly better results than the TF-IDF/SVM couple for the micro F1-score. These encouraging results allow us to consider further developments in the use of transformers in the automation of emergency department data processing in order to consider the implementation of a national observatory of trauma in France., Les modèles de langue contextualisés basés sur l'architecture Transformer tels que BERT (Bidirectional Encoder Representations from Transformers) ont atteint des performances remarquables dans des diverses tâches de traitement de la langue. CamemBERT et FlauBERT en sont des versions pré-entraînées pour le français. Nous avons utilisé ces deux modèles afin de classer automatiquement des notes cliniques libres issues de visites aux urgences à la suite d'un traumatisme. Leurs performances ont été comparées à la méthode TF-IDF (Term-Frequency-Inverse Document Frequency) associé au classifieur SVM (Support Vector Machine) sur 22481 notes cliniques provenant du service des urgences du CHU de Bordeaux. CamemBERT et FlauBERT ont obtenu des résultats légèrement supérieurs à ceux du couple TF-IDF/SVM pour le micro F1-score. Ces résultats encourageants permettent d'envisager l'utilisation des transformers pour automatiser le traitement des données des urgences dans le cadre de la mise en place d'un observatoire national du traumatisme en France.
Published: 2021

117. ESSAI RANDOMISÉ POUR ÉVALUER L’EFFICACITÉ ET LA SÉCURITÉ DE TRAITEMENTS CHEZ DES PATIENTS AMBULATOIRES ATTEINTS DE COVID-19 AYANT DES FACTEURS DE RISQUE ESSAI COVERAGE FRANCE : PRÉSENTATION DU PROTOCOLE

Author: Onaisi, Racha, Duvignaud, Alexandre, Nguyen Binh, Antoine, Dupouy, Julie, Chastang, Julie, Le Bel, Josselin, Landman, Roland, Naccache, Jean Marc, Lefèvre, Benjamin, Piroth, Lionel, Binquet, C, Makinson, Alain, Darnaud, Thomas, Begue, Cyril, Weiss, Laurence, Richert, Laura, Anglaret, Xavier, Denis, Malvy, Joseph, Jean Philippe, Druais, Pierre Louis, Darmon, David, Ral, Cedric, Lhomme, Edouard, Saint-Lary, Olivier, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Groupe hospitalier Pellegrin, Global Health in the Global South (GHiGS), Institut de Recherche pour le Développement (IRD)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sorbonne Université (SU), Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'investigation clinique de Toulouse (CIC 1436), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Pôle Santé publique et médecine publique [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre hospitalier Saint-Joseph [Paris], Centre Hospitalier Universitaire de Nancy (CHU Nancy), CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre d'Investigation Clinique 1432 (Dijon) - Epidemiologie Clinique/Essais Cliniques (CIC-EC), Université de Bourgogne (UB)-Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Centre Hospitalier Bastia (CHB), Institut de recherche en santé, environnement et travail (Irset), Université d'Angers (UA)-Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Immunologie humaine, physiopathologie & immunothérapie (HIPI (UMR_S_976 / U976)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Haute Autorité de Santé [Saint-Denis La Plaine] (HAS), Université Côte d'Azur (UCA), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U1252 INSERM - Aix Marseille Univ - UMR 259 IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Nantes (UN), Centre de Recherche en Cancérologie et Immunologie Nantes-Angers (CRCINA), Université d'Angers (UA)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, and Dupuis, Christine
Subjects: treatment, [SDV]Life Sciences [q-bio], protocols, trial, Internal, controlled, clinical, [SDV] Life Sciences [q-bio], early, randomized, outpatient, Medicine, General, Covid-19
Abstract: Context. The Covid-19 pandemic is of unprecedented magnitude and has had major social and health consequences. Primary care professionals, mainly general practitioners, ensure the care of most patients with Covid-19. An early-stage treatment administered to patients with risk factors for developing a severe disease could reduce hospitalization and death rates. No treatment is currently validated in this indication. Objectives. To evaluate the safety and efficacy of experimental candidate agents delivered in outpatient settings to reduce the risk of hospitalization or death in at-risk patients with early-stage proven Covid-19 and no indication for hospital admission. Methods. Multicentric, open-label, multi-arm, multi-stage (MAMS) randomized controlled trial with a pilot tolerability and safety phase, and a clinical efficacy phase. Efficacy will be determined by the proportion of participants who have an indication for hospital admission, administration of acute oxygen therapy (because of Covid-19) or who decease between D0 and D14 in the experimental treatment group compared to the control group. Expected results. This trial will assess the tolerance and efficacy of diverse treatments administered at an early stage of Covid-19, in patients with risk factors of developing a severe disease. It will also provide information that can contribute to increase primary care actors' ability to conduct clinical trials at the national level., Contexte. La pandémie de Covid-19 a eu d’importantes répercussions sanitaires et sociales. Les acteurs de soins primaires, en particulier les spécialistes de médecine générale, prennent en charge la majorité des patients atteints de Covid-19. Un traitement précoce initié en première ligne, notamment chez les patients à risque d’aggravation, pourrait réduire les taux d’hospitalisation et de décès. Aucun traitement n’est actuellement validé dans cette indication.Objectif. Évaluer l’efficacité et la tolérance de traitements expérimentaux administrés à un stade précoce, en ambulatoire, dans le but de diminuer le risque de développer une forme sévère de la maladie chez des patients atteints de Covid-19 ayant des facteurs de risque d’aggravation et qui n’ont pas de critères d’hospitalisation.Méthodes. Essai thérapeutique contrôlé randomisé multicentrique, en ouvert, multi-bras, multi-étapes (MAMS) comprenant une phase pilote d’évaluation de la tolérance et une phase d’évaluation de l’efficacité. L’efficacité sera évaluée par la proportion de participants ayant eu une indication d’hospitalisation, une indication d’oxygénothérapie aiguë (en raison de la Covid-19), ou décédés entre J0 et J14 dans le groupe traitement expérimental par rapport au groupe témoin. Résultats attendus. Cet essai permettra d’évaluer la tolérance et l’efficacité de l’administration précoce de divers traitements dans le cadre de la Covid-19 chez des patients à risque de développer des formes graves. Il fournira également des informations susceptibles d’améliorer la recherche clinique interventionnelle impliquant la personne humaine en soins primaires et sa structuration.
Published: 2021

118. Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control ap- proach

Author: Clairon, Quentin, Pasin, Chloé, Balelli, Irene, Thiébaut, Rodolphe, Prague, Mélanie, Clairon, Quentin, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Infectious Diseases and Hospital Epidemiology [Zurich], University hospital of Zurich [Zurich], Institute of Virology (Vienna), Medizinische Universität Wien = Medical University of Vienna, E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), This work has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under projects EBOVAC1 and EBOVAC3 (respectively grant agreement No 115854 and No 800176). The IMI2 Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and the European Federation of Pharmaceutical Industries and Association., Vaccine Research Institute (VRI), and Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)
Subjects: Methodology (stat.ME), FOS: Computer and information sciences, Dynamic population models, Mechanistic models, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Clinical trial analysis, Optimal control theory, Nonlinear mixed effects models, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Statistics - Methodology, Ordinary differential equations
Abstract: We present a parameter estimation method for nonlinear mixed effect models based on ordinary differential equations (NLME-ODEs). The method presented here aims at regularizing the estimation problem in presence of model misspecifications, practical identifiability issues and unknown initial conditions. For doing so, we define our estimator as the minimizer of a cost function which incorporates a possible gap between the assumed model at the population level and the specific individual dynamic. The cost function computation leads to formulate and solve optimal control problems at the subject level. This control theory approach allows to bypass the need to know or estimate initial conditions for each subject and it regularizes the estimation problem in presence of poorly identifiable parameters. Comparing to maximum likelihood, we show on simulation examples that our method improves estimation accuracy in possibly partially observed systems with unknown initial conditions or poorly identifiable parameters with or without model error. We conclude this work with a real application on antibody concentration data after vaccination against Ebola virus coming from phase 1 trials. We use the estimated model discrepancy at the subject level to analyze the presence of model misspecification.
Published: 2021

119. Optimising criteria for manual smear review following automated blood count analysis: A machine learning approach

Author: Marta Avalos, Hélène Touchais, Marcela Henríquez-Henríquez, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, IntegraMedica, British United Provident Association Chile (BUPA Chile), Ajith Abraham, Hide Sasaki, Ricardo Rios, Niketa Gandhi, Umang Singh, Kun Ma, Avalos, Marta, Université de Toulouse (UT), Hideyasu Sasaki, and Ajith Abraham, Hideyasu Sasaki, Ricardo Rios, Niketa Gandhi, Umang Singh, Kun Ma
Subjects: [SDV.MHEP.HEM] Life Sciences [q-bio]/Human health and pathology/Hematology, Decision support system, Computer science, Stability (learning theory), Feature selection, Context (language use), Logistic regression, Machine learning, computer.software_genre, 01 natural sciences, [STAT.CO] Statistics [stat]/Computation [stat.CO], 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Interpretability, 0101 mathematics, [STAT.CO]Statistics [stat]/Computation [stat.CO], Data mining, Selection (genetic algorithm), [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Population Health, business.industry, Model selection, Machine Learning for Healthcare Applications, [SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/Hematology, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], GAM, Imbalance, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Categorisation of continuous variables, 030220 oncology & carcinogenesis, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, Lasso, business, computer, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: International audience; The complete blood count (CBC) performed by automated haematology analysers is the most common clinical procedure in the world. Used for health checkup, diagnosis and patient follow-up, the CBC impacts the majority of medical decisions. If the analysis does not fit an expected setting, the laboratory staff manually reviews a blood smear, which is highly time-consuming. Criteria for reviewing CBCs are based on international consensus guidelines and locally adjusted to account for laboratory resources and populations characteristics. Our objective is to provide a clinical laboratory decision support tool to identify which CBC variables are linked to an increased risk of abnormal manual smear and at which threshold values. Thus, we treat criteria adjustment as a feature selection problem. We propose a cost-sensitive Lasso-penalised additive logistic regression combined with stability selection, adapted to the peculiarities of data and context: class-imbalance, categorisation of continuous predictors, required stability and enhanced interpretability. Using simulated and real CBC data, we show that our proposal is competitive in terms of predictive performance (compared to deep neural networks) and model selection performance (provided that there is sufficient data in the neighbourhood of the true thresholds). The R code is publicly available as an open source project.
Published: 2021

120. Inférence post-clustering pour l'identification des variables responsables de la séparation de paires de clusters

Author: Hivert, Benjamin, Agniel, Denis, Thiébaut, Rodolphe, Hejblum, Boris, Hivert, Benjamin, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Harvard Medical School [Boston] (HMS), Rand Corporation, and CHU de Bordeaux Pellegrin [Bordeaux]
Subjects: [MATH] Mathematics [math], [MATH]Mathematics [math]
Abstract: International audience
Published: 2021

121. Automatic processing of emergency room notes: focus on de-identification

Author: Bourdois, Loïck, Avalos, Marta, Chenais, Gabrielle, Contrand, Benjamin, Gil-Jardiné, Cédric, Guennec-Jacques, Antoine, Revel, Philippe, Thiessard, Frantz, Touchais, Hélène, Lagarde, Emmanuel, Avalos, Marta, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria), CHU de Bordeaux Pellegrin [Bordeaux], and Journée organisée avec le soutien de l’Association française d’Informatique Médicale (AIM) et le Collège Science de l’Ingénierie des Connaissances de l’AFIA dans le cadre de la Plate-Forme Intelligence Artificielle (PFIA)
Subjects: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], French, Natural Langage Processing, Urgences, Emergency room, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], Pré-entraînement, [STAT.CO] Statistics [stat]/Computation [stat.CO], Français, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Pre-training, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Transformers, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Traitement automatique du langage, [STAT.CO]Statistics [stat]/Computation [stat.CO], [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: In France, structured data on emergency room visits are aggregated at the national level to build a syndromic surveillance system for different health events. For visits motivated by a traumatic event, information on the circumstances is stored in free text clinical notes. Automating the processing of these notes should allow the enrichment of surveillance tools. In development at Inserm and the Emergency Department of the Bordeaux University Hospital, The TARPON (for Automatic Processing of Emergency Room Notes for a National Observatory, in French) project aims to meet this objective by using the latest deep learning tools applied to automatic language analysis. To exploit these data, an automatic de-identification system, guaranteeing the protection of personal data, is necessary. We present here a comparison study of models allowing the de-identification of clinical texts in French., En France, les données structurées concernant les visites aux urgences sont agrégées au niveau national pour construire un système de surveillance syndromique de différents événements de santé. Pour les visites motivées par un événement traumatique, les informations sur les circonstances sont stockées dans des notes cliniques en texte libre. Automatiser le traitement de ces notes devrait permettre l'enrichissement des outils de surveillance. En développement à l'Inserm et au Service des urgences du CHU de Bordeaux, le projet TARPON (Traitement Automatique des Résumés de Passages aux urgences pour un Observatoire National) vise à répondre à cet objectif par le biais des derniers outils d'apprentissage profond appliqués à l'analyse automatique du langage. Pour exploiter ces données, un système de désidentification automatique, garantissant la protection des données personnelles est nécessaire. Nous présentons ici une étude de comparaison de modèles permettant la désidentification des textes cliniques en français.
Published: 2021

122. A randomized placebo-controlled efficacy study of a prime boost therapeutic vaccination strategy in HIV-1 infected individuals: VRI02 ANRS 149 LIGHT Phase II trial

Author: P.-M. Girard, L. Guillaumat, Emile Foucat, Valérie Boilet, Giuseppe Pantaleo, Aurélie Wiedemann, Yves Levy, L. Hocqueloux, Jean-Michel Molina, Laura Richert, E. Lhomme, Craig Fenwick, P. Morlat, Véronique Rieux, Jean-Daniel Lelièvre, Christine Lacabaratz, Olivier Bouchaud, C. Bauduin, Mathieu Surenaud, Rodolphe Thiébaut, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Hôpital Henri Mondor, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM), Admin, Oskar, Hôpital Albert Chenevier, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, Team MORPH3EUS (INSERM U1219 - UB - ISPED), CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lausanne = University of Lausanne (UNIL), Agence Nationale de Recherches sur le Sida et les Hépatites Virales (ANRS), Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris 13 (UP13), CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Hopital Saint-Louis [AP-HP] (AP-HP), Génétique et Ecologie des Virus, Génétique des Virus et Pathogénèse des Maladies Virales, Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional d'Orléans (CHRO), University of Lausanne (UNIL), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and DARMIGNY, SANDRINE
Subjects: CD4-Positive T-Lymphocytes, Male, Antiretroviral therapy interruption, [SDV]Life Sciences [q-bio], HIV Infections, CD8-Positive T-Lymphocytes, law.invention, 0302 clinical medicine, Randomized controlled trial, law, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Vaccines, DNA, 030212 general & internal medicine, AIDS Vaccines, 0303 health sciences, human immunodeficiency virus, Immunogenicity, Middle Aged, 3. Good health, [SDV] Life Sciences [q-bio], Vaccination, Anti-Retroviral Agents, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Female, medicine.drug, Interleukin 2, Adult, Immunology, Immunization, Secondary, Viremia, Biology, Placebo, Microbiology, complex mixtures, 03 medical and health sciences, Immune system, [SDV.IMM.VAC] Life Sciences [q-bio]/Immunology/Vaccinology, Virology, Vaccines and Antiviral Agents, medicine, Humans, 030304 developmental biology, clinical trials, HIV, medicine.disease, Therapeutic vaccine, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Insect Science, HIV-1, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, CD8
Abstract: In this placebo-controlled phase II randomized clinical trial, we evaluated the safety and immunogenicity of a therapeutic prime-boost vaccine strategy using a recombinant DNA vaccine (GTU-MultiHIV B clade) followed by a boost vaccination with a lipopeptide vaccine (HIV-LIPO-5) in HIV-infected patients on combined antiretroviral therapy. We show here that this prime-boost strategy is well tolerated, consistently with previous studies in HIV-1-infected individuals and healthy volunteers who received each vaccine component individually., In this placebo-controlled phase II randomized clinical trial, 103 human immunodeficiency virus type 1 (HIV-1)-infected patients under cART (combined antiretroviral treatment) were randomized 2:1 to receive either 3 doses of DNA GTU-MultiHIV B (coding for Rev, Nef, Tat, Gag, and gp160) at week 0 (W0), W4, and W12, followed by 2 doses of LIPO-5 vaccine containing long peptides from Gag, Pol, and Nef at W20 and W24, or placebo. Analytical treatment interruption (ATI) was performed between W36 to W48. At W28, vaccinees experienced an increase in functional CD4+ T-cell responses (P
Published: 2021

123. Influence of the Antiretroviral Regimen on the Early Changes in Plasma HIV RNA and Immune Activation at Initiation of Antiretroviral Therapy in Naïve HIV-1–Infected Patients

Author: Brigitte Autran, Assia Samri, Julià Blanco, Fareed Ahmad, Georg M. N. Behrens, François Raffi, Peter Kelleher, Andreas Plettenberg, Bonaventura Clotet, Mathieu Chalouni, Rodolphe Thiébaut, Marta Massanella, Neat, Christine Katlama, Laura Richert, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Sorbonne Université (SU), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and CHU Bordeaux [Bordeaux]
Subjects: Anti-HIV Agents, [SDV]Life Sciences [q-bio], Human immunodeficiency virus (HIV), HIV Infections, medicine.disease_cause, 03 medical and health sciences, 0302 clinical medicine, Medicine, Humans, Pharmacology (medical), ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, business.industry, Viral Load, Antiretroviral therapy, 3. Good health, CD4 Lymphocyte Count, Regimen, Infectious Diseases, Anti-Retroviral Agents, Immunology, HIV-1, RNA, RNA, Viral, business, 030215 immunology, Immune activation
Abstract: International audience
Published: 2021

124. Automatic phenotyping of electronical health record: PheVis algorithm

Author: Boris P. Hejblum, Vianney Jouhet, Thomas Ferté, Sébastien Cossin, Thierry Schaeverbeke, Thomas Barnetche, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Haut-Lévêque [CHU Bordeaux], CHU Bordeaux [Bordeaux], Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Hejblum, Boris
Subjects: Chronic condition, 020205 medical informatics, Computer science, Health Informatics, 02 engineering and technology, Health records, Machine learning, computer.software_genre, Arthritis, Rheumatoid, Machine Learning, 03 medical and health sciences, Annotation, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Humans, Electronic health records, 030212 general & internal medicine, Natural Language Processing, 030304 developmental biology, 0303 health sciences, Past medical history, business.industry, Medical record, Precision medicine, Data warehouse, Computer Science Applications, 3. Good health, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, High-throughput phenotyping, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Diagnosis code, Artificial intelligence, White box, business, computer, Algorithms, Natural language processing, Phenotypic big data
Abstract: Electronic Health Records (EHRs) often lack reliable annotation of patient medical conditions. Yu et al. recently proposed PheNorm, an automated unsupervised algorithm to identify patient medical conditions from EHR data. PheVis extends PheNorm at the visit resolution. PheVis combines diagnosis codes together with medical concepts extracted from medical notes, incorporating past history in a machine learning approach to provide an interpretable “white box” predictor of the occurrence probability for a given medical condition at each visit. PheVis is applied to two real-world use-cases using the datawarehouse of the University Hospital of Bordeaux: i) rheumatoid arthritis, a chronic condition; ii) tuberculosis, an acute condition (cross-validated AUROC were respectively 0.947 [0.944; 0.948] and 0.987 [0.983; 0.990]). PheVis performs well for chronic conditions, though absence of exclusion of past medical history by natural language processing tools limits its performance in French for acute conditions. It achieves significantly better performance than state-of-the-art methods especially for chronic diseases.
Published: 2021

125. A decision-making tool to fine-tune abnormal levels in the complete blood count tests

Author: Avalos, Marta, Touchais, Hélène, Henríquez-Henríquez, Marcela, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT), IntegraMedica, British United Provident Association Chile (BUPA Chile), Avalos, Marta, and Université Fédérale Toulouse Midi-Pyrénées
Subjects: FOS: Computer and information sciences, Computer Science - Machine Learning, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Population Health, Machine Learning (stat.ML), [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [STAT.CO] Statistics [stat]/Computation [stat.CO], Statistics - Applications, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], GAM, Machine Learning (cs.LG), Imbalance, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Statistics - Machine Learning, Applications (stat.AP), Interpretability, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Lasso, [STAT.CO]Statistics [stat]/Computation [stat.CO], [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract: The complete blood count (CBC) performed by automated hematology analyzers is one of the most ordered laboratory tests. It is a first-line tool for assessing a patient's general health status, or diagnosing and monitoring disease progression. When the analysis does not fit an expected setting, technologists manually review a blood smear using a microscope. The International Consensus Group for Hematology Review published in 2005 a set of criteria for reviewing CBCs. Commonly, adjustments are locally needed to account for laboratory resources and populations characteristics. Our objective is to provide a decision support tool to identify which CBC variables are associated with higher risks of abnormal smear and at which cutoff values. We propose a cost-sensitive Lasso-penalized additive logistic regression combined with stability selection. Using simulated and real CBC data, we demonstrate that our tool correctly identify the true cutoff values, provided that there is enough available data in their neighbourhood., Comment: Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract
Published: 2020

126. Prospective Evaluation of the First Option, Second-Line Therapy in Childhood Chronic Immune Thrombocytopenia: Splenectomy or Immunomodulation

Author: Rodolphe Thiébaut, Corinne Armari-Alla, Marlène Pasquet, Thierry Leblanc, Nathalie Aladjidi, Guy Leverger, Stéphane Ducassou, Wadih Abou Chahla, Hélène Savel, Corinne Guitton, Vincent Barlogis, Helder Fernandes, Isabelle Pellier, Gilles Vassal, Yves Bertrand, Caroline Thomas, Nathalie Cheikh, Salim Laghouati, Sophie Bayart, Djamel Kherfellah, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité d'Hémato-Immunologie pédiatrique [Hôpital Robert Debré, Paris], Service d'Immuno-hématologie pédiatrique [Hôpital Robert Debré, Paris], Hôpital Robert Debré-Hôpital Robert Debré, Unité de Soutien Méthodologique à la Recherche Clinique (USMR), CHU Bordeaux [Bordeaux], CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Référence National des Cytopénies Auto-immunes de l'Enfant (CEREVANCE), Institut d’Hématologie et d’Oncologie Pédiatriques, Hôpital Robert Debré, CHU Lille, Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), CHU Trousseau [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Hôpital de la Timone [CHU - APHM] (TIMONE), Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Pontchaillou [Rennes], Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), CHU Grenoble, Hôpital Bicêtre, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Institut Gustave Roussy (IGR), Université Paris-Saclay, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Male, medicine.medical_specialty, hydroxychloroquine, Adolescent, medicine.medical_treatment, [SDV]Life Sciences [q-bio], Splenectomy, Azathioprine, Gastroenterology, Immunomodulation, 03 medical and health sciences, 0302 clinical medicine, rituximab, children, 030225 pediatrics, Internal medicine, medicine, Humans, Prospective Studies, 030212 general & internal medicine, Child, Prospective cohort study, ComputingMilieux_MISCELLANEOUS, Purpura, Thrombocytopenic, Idiopathic, azathioprine, business.industry, Autoimmune Cytopenia, Infant, Hydroxychloroquine, Immune thrombocytopenia, 3. Good health, Child, Preschool, Chronic Disease, Pediatrics, Perinatology and Child Health, Cohort, second-line treatment, Female, Rituximab, business, medicine.drug
Abstract: International audience; Objective: To describe 4 subgroups of pediatric patients treated with splenectomy, hydroxychloroquine, azathioprine, or rituximab as the first-option, second-line treatment for chronic immune thrombocytopenia.Study design: Selection of patients with chronic immune thrombocytopenia from the French national prospective cohort of pediatric autoimmune cytopenia OBS'CEREVANCE and VIGICAIRE study, treated by splenectomy, hydroxychloroquine, azathioprine, or rituximab as a first second-line treatment.Results: For 137 patients, treated between 1989 and 2016, the median follow-up after diagnosis and after treatment initiation was 8.5 (2.8-26.4) years and 4.7 (1.1-25.1) years, respectively. Median age at diagnosis and at initiation of treatment were 9 (0.7; 16) and 12 (2; 18.1) years, respectively without significant difference between subgroups. For the whole cohort, 24-month event-free survival was 62% (95% CI 55; 71). It was 85% (95% CI 77; 95) for the 56 patients treated with splenectomy, 60% (95% CI 44; 84) for the 23 patients treated with rituximab, 46% (95% CI 30; 71) for the 24 patients treated with azathioprine, and 37% (95% CI 24; 59) for the 34 patients treated with hydroxychloroquine (log-rank P < .0001). For the splenectomy subgroup, being older than 10 years at splenectomy tended to improve event-free survival (P = .05). Female teenagers with antinuclear antibody positivity benefited from hydroxychloroquine therapy.Conclusions: This national study, limiting pitfalls in the analysis of the effects of second-line therapies, showed that splenectomy remains the treatment associated with the better response at 24 months.
Published: 2020

127. Distinct Signatures in the Receptor Repertoire Discriminate CD56bright and CD56dim Natural Killer Cells

Author: Vera, Schwane, Van Hung, Huynh-Tran, Sarah, Vollmers, Vivien Maria, Yakup, Jürgen, Sauter, Alexander H, Schmidt, Sven, Peine, Marcus, Altfeld, Laura, Richert, Christian, Körner, Heinrich Pette Institute [Hamburg], Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), DKMS, Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: [SDV]Life Sciences [q-bio], CD56bright, Immunology, CD56dim, CD205, NK cells, CD58, CD147, CD161, CD82, CD56 Antigen, Killer Cells, Natural, Phenotype, Humans, Immunology and Allergy, ComputingMilieux_MISCELLANEOUS, Original Research
Abstract: NK cells are phenotypically and functionally diverse lymphocytes due to variegated expression of a large array of receptors. NK-cell activity is tightly regulated through integration of receptor-derived inhibitory and activating signals. Thus, the receptor profile of each NK cell ultimately determines its ability to sense aberrant cells and subsequently mediate anti-viral or anti-tumor responses. However, an in-depth understanding of how different receptor repertoires enable distinct immune functions of NK cells is lacking. Therefore, we investigated the phenotypic diversity of primary human NK cells by performing extensive phenotypic characterization of 338 surface molecules using flow cytometry (n = 18). Our results showed that NK cells express at least 146 receptors on their surface. Of those, 136 (>90%) exhibited considerable inter-donor variability. Moreover, comparative analysis of CD56bright and CD56dim NK cells identified 70 molecules with differential expression between the two major NK-cell subsets and allowed discrimination of these subsets via unsupervised hierarchical clustering. These receptors were associated with a broad range of NK-cell functions and multiple molecules were not previously associated with predominant expression on either subset (e.g. CD82 and CD147). Altogether, our study contributes to an improved understanding of the phenotypic diversity of NK cells and its potential functional implications on a cellular and population level. While the identified distinct signatures in the receptor repertoires provide a molecular basis for the differential immune functions exerted by CD56bright and CD56dim NK cells, the observed inter-individual differences in the receptor repertoire of NK cells may contribute to a diverging ability to control certain diseases.
Published: 2020
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128. KEFT: Knowledge Extraction and Graph Building from Statistical Data Tables

Author: Sylvie Desprès, Rabia Azzi, Gayo Diallo, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Marcin Hernes, Krystian Wojtkiewicz, and Edward Szczerbicki
Subjects: Knowledge graph, Information retrieval, Information extraction, Computer science, 05 social sciences, PDF document, Statistical model, 030204 cardiovascular system & hematology, computer.software_genre, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 03 medical and health sciences, 0302 clinical medicine, Knowledge extraction, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Graph (abstract data type), Table recognition, 0509 other social sciences, 050904 information & library sciences, computer
Abstract: International audience; Data provided by statistical models are commonly represented by textual, tabular or graphical form in documents (reports, articles, posters and presentations). These documents are often available in PDF format. Even though it makes accessing a particular information more difficult, it is interesting to process the PDF documents directly. We present KEFT, a solution in the statistical domain and we describe the fully functional pipeline to constructing a knowledge graph by extracting entities and relations from statistical Data Tables. We showcase how this approach can be used to construct a knowledge graph from different statistical studies.
Published: 2020

129. Joint Bone Spine

Author: Vial, Guillaume, Gensous, Noémie, Savel, Hélène, Richez, Christophe, Lazaro, Estibaliz, Truchetet, Marie-Elise, Bonnet, Fabrice, Pellegrin, Isabelle, Thiébaut, Rodolphe, Blanco, Patrick, Duffau, Pierre, Hôpital Saint-André, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Composantes innées de la réponse immunitaire et différenciation (CIRID), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS), Hôpital Pellegrin, and CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin
Subjects: IDLIC, MORPH3Eus, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, ComputingMilieux_MISCELLANEOUS, SISTM
Abstract: International audience
Published: 2020

130. Ribavirin for treating Lassa fever: A systematic review of pre-clinical studies and implications for human dosing

Author: Alex P. Salam, Alexandre Duvignaud, Marie Jaspard, Denis Malvy, Miles Carroll, Joel Tarning, Piero L. Olliaro, Peter W. Horby, University of Oxford, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Admin, Oskar, Global Health in the Global South (GHiGS), Institut de Recherche pour le Développement (IRD)- Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: viruses, Public Health, Environmental and Occupational Health, virus diseases, Virus Replication, Antiviral Agents, Lassa Fever, Infectious Diseases, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Research Design, [SDV.SP.PHARMA] Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Ribavirin, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Humans, Lassa virus
Abstract: International audience; Ribavirin is currently the standard of care for treating Lassa fever. However, the human clinical trial data supporting its use suffer from several serious flaws that render the results and conclusions unreliable. We performed a systematic review of available pre-clinical data and human pharmacokinetic data on ribavirin in Lassa. In in-vitro studies, the EC50 of ribavirin ranged from 0.6 μg/ml to 21.72 μg/ml and the EC90 ranged from 1.5 μg/ml to 29 μg/ml. The mean EC50 was 7 μg/ml and the mean EC90 was 15 μg/ml. Human PK data in patients with Lassa fever was sparse and did not allow for estimation of concentration profiles or pharmacokinetic parameters. Pharmacokinetic modelling based on healthy human data suggests that the concentration profiles of current ribavirin regimes only exceed the mean EC50 for less than 20% of the time and the mean EC90 for less than 10% of the time, raising the possibility that the current ribavirin regimens in clinical use are unlikely to reliably achieve serum concentrations required to inhibit Lassa virus replication. The results of this review highlight serious issues with the evidence, which, by today standards, would be unlikely to support the transition of ribavirin from pre-clinical studies to human clinical trials. Additional pre-clinical studies are needed before embarking on expensive and challenging clinical trials of ribavirin in Lassa fever.
Published: 2022

131. Bayesian mixture models for cytometry data analysis

Author: Boris P. Hejblum, Lin Lin, Pennsylvania State University (Penn State), Penn State System, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Hejblum, Boris
Subjects: Statistics and Probability, [SDV.IMM] Life Sciences [q-bio]/Immunology, Computer science, Bayesian probability, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, symbols.namesake, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Bayesian hierarchical modeling, 0101 mathematics, Cluster analysis, [SDV.BC] Life Sciences [q-bio]/Cellular Biology, 030304 developmental biology, [STAT.AP]Statistics [stat]/Applications [stat.AP], 0303 health sciences, Markov chain Monte Carlo, Mixture model, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], SISTM, Statistics::Computation, ComputingMethodologies_PATTERNRECOGNITION, symbols, [SDV.IMM]Life Sciences [q-bio]/Immunology, Biological system, Cytometry
Abstract: International audience; Bayesian mixture models are increasingly used for model‐based clustering and the follow‐up analysis on the clusters identified. As such, they are of particular interest for analyzing cytometry data where unsupervised clustering and association studies are often part of the scientific questions. Cytometry data are large quantitative data measured in a multidimensional space that typically ranges from a few dimensions to several dozens, and which keeps increasing due to innovative high‐throughput biotechonologies. We present several recent parametric and nonparametric Bayesian mixture modeling approaches, and describe advantages and limitations of these models under different research context for cytometry data analysis. We also acknowledge current computational challenges associated with the use of Bayesian mixture models for analyzing cytometry data, and we draw attention to recent developments in advanced numerical algorithms for estimating large Bayesian mixture models, which we believe have the potential to make Bayesian mixture model more applicable to new types of single‐cell data with higher dimensions.
Published: 2020

132. Robust and Efficient Optimization Using a Marquardt-Levenberg Algorithm with R Package marqLevAlg

Author: Viviane Philipps, Boris,P. Hejblum, Mélanie Prague, Daniel Commenges, Cécile Proust-Lima, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), This work was funded by French National Research Agency [grant number ANR-18-CE36-0004-01 for project DyMES] and [grant number ANR-2010-PRPS-006 for project MOBYDIQ]., ANR-18-CE36-0004,DyMES,Modèles Dynamiques pour les Etudes Epidémiologiques Longitudinales sur les Maladies Chroniques(2018), ANR-17-CE01-0013,MOBYDICK,Biodiversité des Ecosystèmes Marins et Dynamique du Carbone dans le secteur de Kerguelen : approche intégrée(2017), Hejblum, Boris, APPEL À PROJETS GÉNÉRIQUE 2018 - Modèles Dynamiques pour les Etudes Epidémiologiques Longitudinales sur les Maladies Chroniques - - DyMES2018 - ANR-18-CE36-0004 - AAPG2018 - VALID, and Biodiversité des Ecosystèmes Marins et Dynamique du Carbone dans le secteur de Kerguelen : approche intégrée - - MOBYDICK2017 - ANR-17-CE01-0013 - AAPG2017 - VALID
Subjects: FOS: Computer and information sciences, Statistics and Probability, Optimization, Parallel computing, Numerical Analysis, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Marquardt-Levenberg, Statistics - Computation, Newton-Raphson, Statistics, Probability and Uncertainty, Convergence criteria, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Computation (stat.CO)
Abstract: Implementations in R of classical general-purpose algorithms for local optimization generally have two major limitations which cause difficulties in applications to complex problems: too loose convergence criteria and too long calculation time. By relying on a Marquardt-Levenberg algorithm (MLA), a Newton-like method particularly robust for solving local optimization problems, we provide with marqLevAlg package an efficient and general-purpose local optimizer which (i) prevents convergence to saddle points by using a stringent convergence criterion based on the relative distance to minimum/maximum in addition to the stability of the parameters and of the objective function; and (ii) reduces the computation time in complex settings by allowing parallel calculations at each iteration. We demonstrate through a variety of cases from the literature that our implementation reliably and consistently reaches the optimum (even when other optimizers fail), and also largely reduces computational time in complex settings through the example of maximum likelihood estimation of different sophisticated statistical models., 20 pages, 4 figures
Published: 2020

133. Predicting Progression to Advanced Age-Related Macular Degeneration from Clinical, Genetic, and Lifestyle Factors Using Machine Learning

Author: Soufiane Ajana, Audrey Cougnard-Grégoire, Johanna M. Colijn, Bénédicte M.J. Merle, Timo Verzijden, Paulus T.V.M. de Jong, Albert Hofman, Johannes R. Vingerling, Boris P. Hejblum, Jean-François Korobelnik, Magda A. Meester-Smoor, Marius Ueffing, Hélène Jacqmin-Gadda, Caroline C.W. Klaver, Cécile Delcourt, Erkin I. Acar, Blanca Arango-Gonzalez, Angela Armento, Franz Badura, Vaibhav Bhatia, Shomi S. Bhattacharya, Marc Biarnés, Anna Borrell, Sofia M. Calado, Sascha Dammeier, Anita de Breuk, Berta De la Cerda, Anneke I. den Hollander, Francisco J. Diaz-Corrales, Sigrid Diether, Eszter Emri, Tanja Endermann, Lucia L. Ferraro, Míriam Garcia, Thomas J. Heesterbeek, Sabina Honisch, Carel B. Hoyng, Ellen Kilger, Elod Kortvely, Claire Lastrucci, Hanno Langen, Imre Lengyel, Phil Luthert, Jordi Monés, Everson Nogoceke, Tunde Peto, Frances M. Pool, Eduardo Rodriguez-Bocanegra, Luis Serrano, Jose Sousa, Eric Thee, Karl U. Ulrich Bartz-Schmidt, Markus Zumbansen, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Amsterdam [Amsterdam] (UvA), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, The EYE-RISK project was supported by the European Union’s Horizon 2020 Research and Innovation Programme (grant n°: 634479). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands, the Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam, Rotterdam, The Netherlands. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Additionally, the ophthalmic research within the Rotterdam Study was supported by the following foundations: Oogfonds, Bartiméus Sonneheerdt Vereniging, LandelijkeStichting voor Blinden en Slechtzienden, Algemene Nederlandse Vereniging Ter Voorkoming Van Blindheid, Novartis Foundation, and MaculaFonds, which contributed through UitZicht (grant nos.: 2015-36 and 2016-19). The Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires (ALIENOR) Study was funded by Laboratoires Théa, Fondation Voir et Entendre, Retina France, Agence Nationale de la Recherche (ANR-2010-PRSP-011 VISA), Programme Hospitalier de Recherche Clinique (PHRC) (ECLAIR project-2012), CFSR Recherche, the French Speaking Retina Specialists’ Club and Caisse Nationale pour la Solidarité et l’Autonomie. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Laboratoires Théa participated in the design of the Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires (ALIENOR) Study, but none of the sponsors of this study participated in the collection, management, statistical analysis, or interpretation of the data, or in the preparation, review, or approval of the present manuscript., European Project: 634479,H2020,H2020-PHC-2014-two-stage,EYE-RISK(2015), Hejblum, Boris, Exploring the combined role of genetic and non-genetic factors for developing Age-Related Macular Degeneration: A systems level analysis of disease subgroups, risk factors, and pathways - EYE-RISK - - H20202015-05-01 - 2019-04-30 - 634479 - VALID, Ophthalmology, Epidemiology, Netherlands Institute for Neuroscience (NIN), and Vaccine Research Institute [Créteil, France] (VRI)
Subjects: Male, computer.software_genre, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Machine Learning, Rotterdam Study, Macular Degeneration, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], Risk Factors, Cumulative incidence, ComputingMilieux_MISCELLANEOUS, 0303 health sciences, education.field_of_study, [STAT.AP]Statistics [stat]/Applications [stat.AP], Smoking, Middle Aged, 3. Good health, Phenotype, Area Under Curve, Disease Progression, Female, Cohort study, Genotype, Population, Clinical Decision-Making, Retinal Drusen, Machine learning, 03 medical and health sciences, medicine, Genetics, Humans, education, Life Style, Survival analysis, 030304 developmental biology, Aged, Nutrition, Receiver operating characteristic, business.industry, Age-related macular degeneration, Macular degeneration, Models, Theoretical, medicine.disease, Lifestyle, Personalized medicine, Confidence interval, eye diseases, Ophthalmology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, 030221 ophthalmology & optometry, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, business, Prediction, computer
Abstract: Contains fulltext : 245098.pdf (Publisher’s version ) (Closed access) PURPOSE: Current prediction models for advanced age-related macular degeneration (AMD) are based on a restrictive set of risk factors. The objective of this study was to develop a comprehensive prediction model applying a machine learning algorithm allowing selection of the most predictive risk factors automatically. DESIGN: Two population-based cohort studies. PARTICIPANTS: The Rotterdam Study I (RS-I; training set) included 3838 participants 55 years of age or older, with a median follow-up period of 10.8 years, and 108 incident cases of advanced AMD. The Antioxydants, Lipids Essentiels, Nutrition et Maladies Oculaires (ALIENOR) study (test set) included 362 participants 73 years of age or older, with a median follow-up period of 6.5 years, and 33 incident cases of advanced AMD. METHODS: The prediction model used the bootstrap least absolute shrinkage and selection operator (LASSO) method for survival analysis to select the best predictors of incident advanced AMD in the training set. Predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). MAIN OUTCOME MEASURES: Incident advanced AMD (atrophic, neovascular, or both), based on standardized interpretation of retinal photographs. RESULTS: The prediction model retained (1) age, (2) a combination of phenotypic predictors (based on the presence of intermediate drusen, hyperpigmentation in one or both eyes, and Age-Related Eye Disease Study simplified score), (3) a summary genetic risk score based on 49 single nucleotide polymorphisms, (4) smoking, (5) diet quality, (6) education, and (7) pulse pressure. The cross-validated AUC estimation in RS-I was 0.92 (95% confidence interval [CI], 0.88-0.97) at 5 years, 0.92 (95% CI, 0.90-0.95) at 10 years, and 0.91 (95% CI, 0.88-0.94) at 15 years. In ALIENOR, the AUC reached 0.92 at 5 years (95% CI, 0.87-0.98). In terms of calibration, the model tended to underestimate the cumulative incidence of advanced AMD for the high-risk groups, especially in ALIENOR. CONCLUSIONS: This prediction model reached high discrimination abilities, paving the way toward making precision medicine for AMD patients a reality in the near future.
Published: 2020

134. Comparison of AUC in clinical trials with follow up censoring: Application to HIV therapeutic vaccines

Author: Alexandre, Marie, Prague, Mélanie, Lévy, Yves, Rodolphe, Thiebaut, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute [Créteil, France] (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université Bordeaux Segalen - Bordeaux 2, and Alexandre, Marie
Subjects: [STAT.ME] Statistics [stat]/Methodology [stat.ME], [STAT.ME]Statistics [stat]/Methodology [stat.ME], ComputingMilieux_MISCELLANEOUS
Abstract: International audience
Published: 2020

135. IEEE/ACM Transactions on Computational Biology and Bioinformatics

Author: Sadok Ben Yahia, Souad Bouasker, Wissem Inoubli, Gayo Diallo, Bordeaux population health (BPH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB), Université de Tunis El Manar (UTM), Tallinn University of Technology (TTÜ), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Association rule learning, medicine.drug_class, Rarity, 0206 medical engineering, Breast Neoplasms, 02 engineering and technology, Biology, Bioinformatics, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Machine Learning, Correlation, Breast cancer, Pregnancy, Gene expression, Genetics, medicine, Data Mining, Humans, Gene, Differentially-expressed genes, Apache Spark, Applied Mathematics, ERIAS, Computational Biology, Cancer, medicine.disease, Distributed computing, 3. Good health, Pregnancy associated breast cancer, Association rule, Estrogen, Female, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Transcriptome, Pregnancy Complications, Neoplastic, Algorithms, 020602 bioinformatics, Biotechnology
Abstract: Online ahead of print; International audience; Each year breast-cancer (BC) is the most common invasive cancer in women, causing a considerable death rate. Given that, BC is classified as a hormone-dependent cancer, when it collides with pregnancy, different questions may arise for which there are still no convincing answers. To deal with this issue, two new frameworks are proposed within this paper: CORAM and DIST-CORAM. The former is the first unified framework dedicated to the extraction of a generic basis of Correlated-Rare association rules from gene expression data. The proposed approach has been successfully applied on a breast-cancer Gene Expression Matrix (GSE1379) with very promising results. The latter, the DIST-CORAM approach, is a big-data processing system based on Apache spark, which deals with correlation mining from streams of micro-array pregnancy associated breast-cancer (PABC). It is successfully applied on the (GSE31192) gene expression matrix (GEM). The correlated patterns of gene-sets affirm that PABC exhibits heightened aggressiveness compared to cancers for Non-PABC women. In fact, the high levels of estrogen and progesterone hormones unfortunately contribute to the tumor aggressiveness and the proliferation of the cancer.
Published: 2020

136. Long-lasting severe immune dysfunction in Ebola virus disease survivors

Author: Wiedemann, Aurélie, Foucat, Emile, Hocini, Hakim, Lefebvre, Cécile, Hejblum, Boris P., Durand, Mélany, Krüger, Miriam, Keita, Alpha Kabinet, Ayouba, Ahidjo, Mély, Stéphane, Fernandez, José-Carlos, Touré, Abdoulaye, Fourati, Slim, Lévy-Marchal, Claire, Raoul, Hervé, Delaporte, Eric, Koivogui, Lamine, Thiébaut, Rodolphe, Lacabaratz, Christine, Lévy, Yves, Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Santé publique, Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Recherches Translationnelles sur le VIH et les maladies infectieuses endémiques er émergentes (TransVIHMI), Institut de Recherche pour le Développement (IRD)-Université de Yaoundé I-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Université Gamal Abdel Nasser de Conakry, Laboratoire P4 - Jean Mérieux, Centre Européen de Virologie/Immunologie-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Santé Publique [Conakry, Guinée] (INSP), Ministère de la Santé [Conakry, Guinea], CHU Henri Mondor, Pôle de Recherche Clinique [Paris] (PRC), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), CHU Bordeaux [Bordeaux], This work was supported by INSERM and by the Investissements d’Avenir program, Vaccine Research Institute (VRI), managed by the ANR under reference ANR-10-LABX-77-01., PostEboGui Study Group, ANR-10-LABX-0077,VRI,Initiative for the creation of a Vaccine Research Institute(2010), Bodescot, Myriam, Laboratoires d'excellence - Initiative for the creation of a Vaccine Research Institute - - VRI2010 - ANR-10-LABX-0077 - LABX - VALID, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Universtié Yaoundé 1 [Cameroun]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), ANR-10-LABX-0077/10-LABX-0077,VRI,Initiative for the creation of a Vaccine Research Institute(2010), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB), Laboratoire P4 Jean Mérieux-Inserm [Lyon] (Unité de service 3), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Européen de Recherche en Virologie et Immunologie [Lyon] (Tour Inserm CERVI), Groupe Henri Mondor-Albert Chenevier, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Institut de Recherche pour le Développement (IRD)-Université de Yaoundé I-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)-Université Montpellier 1 (UM1), Institut de Recherche pour le Développement (IRD)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Universtié Yaoundé 1 [Cameroun]-Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD)-Université Montpellier 1 (UM1)-Université de Montpellier (UM), Institut national de la santé publique (INSP), Recherches Translationnelles sur le VIH et les maladies infectieuses endémiques et émergentes (TransVIHMI), and CHU Henri Mondor [Créteil]
Subjects: Adult, Genetic Markers, Male, [SDV.IMM] Life Sciences [q-bio]/Immunology, T-Lymphocytes, Immunology, Antibodies, Viral, Lymphocyte Activation, Antiviral Agents, [SDV.IMM.II]Life Sciences [q-bio]/Immunology/Innate immunity, Article, Young Adult, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Humans, Survivors, Immunological disorders, Inflammation, [SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology, B-Lymphocytes, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, Hemorrhagic Fever, Ebola, Ebolavirus, SISTM, Immune System Diseases, [SDV.IMM.IA]Life Sciences [q-bio]/Immunology/Adaptive immunology, Immunoglobulin G, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Cytokines, [SDV.IMM]Life Sciences [q-bio]/Immunology, Female, Infection, Transcriptome
Abstract: Long-term follow up studies from Ebola virus disease (EVD) survivors (EBOV_S) are lacking. Here, we evaluate immune and gene expression profiles in 35 Guinean EBOV_S from the last West African outbreak, a median of 23 months (IQR [18–25]) after discharge from treatment center. Compared with healthy donors, EBOV_S exhibit increases of blood markers of inflammation, intestinal tissue damage, T cell and B cell activation and a depletion of circulating dendritic cells. All survivors have EBOV-specific IgG antibodies and robust and polyfunctional EBOV-specific memory T-cell responses. Deep sequencing of the genes expressed in blood reveals an enrichment in ‘inflammation’ and ‘antiviral’ pathways. Integrated analyses identify specific immune markers associated with the persistence of clinical symptoms. This study identifies a set of biological and genetic markers that could be used to define a signature of “chronic Ebola virus disease (CEVD)”., Patients who have recovered from Ebola virus can have ongoing health problems. Here, the authors show that 35 Guinean survivors of the last West African Ebola epidemic have a chronic disease with high inflammatory cytokine expression and other markers of immune activation as well as evidence of intestinal tissue damage nearly two years after their release from hospital.
Published: 2020

137. A Conceptual Discussion About the Basic Reproduction Number of Severe Acute Respiratory Syndrome Coronavirus 2 in Healthcare Settings

Author: Laura Temime, Marie-Paule Gustin, P. Vanhems, Rodolphe Thiébaut, Lulla Opatowski, Didier Guillemot, Niccolò Buetti, Pascal Crépey, David R M Smith, Audrey Duval, Jean-Ralph Zahar, Conservatoire National des Arts et Métiers [CNAM] (CNAM), Centre International de Recherche en Infectiologie - UMR (CIRI), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Hôpital Paul Brousse, Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, Institut Pasteur [Paris], This work was funded, in part, by the French government through the National Research Agency project SPHINX (17-CE36–0008–01) and Fondation de France project MOD-COV. D. S. is also supported by a Canadian Institutes for Health Research doctoral foreign study award (164263)., and ANR-17-CE36-0008,SPHINx,Diffusion de pathogènes au sein des réseaux de soins : une étude de modélisation(2017)
Subjects: 0301 basic medicine, Microbiology (medical), 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), modelling, 03 medical and health sciences, Hospital, 0302 clinical medicine, Nursing, Health care, Pandemic, Humans, Medicine, Transmission, 030212 general & internal medicine, Pandemics, SARS-CoV-2, business.industry, Brief Report, Modeling, COVID-19, Basic reproduction number, 3. Good health, AcademicSubjects/MED00290, 030104 developmental biology, Infectious Diseases, Healthcare settings, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, Delivery of Health Care
Abstract: To date, no specific estimate of R0 for SARS-CoV-2 is available for healthcare settings. Using interindividual contact data, we highlight that R0 estimates from the community cannot translate directly to healthcare settings, with pre-pandemic R0 values ranging 1.3–7.7 in 3 illustrative healthcare institutions. This has implications for nosocomial COVID-19 control.
Published: 2020
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138. NutriSem: A Semantics-Driven Approach to Calculating Nutritional Value of Recipes

Author: Rabia Azzi, Sylvie Desprès, Gayo Diallo, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Álvaro Rocha, Hojjat Adeli, Luís Paulo Reis, Sandra Costanzo, Irena Orovic, Fernando Moreira, Rocha, Á, Adeli, H, Reis, L P, Costanzo, S, Orovic, I, and Moreira, F
Subjects: Text corpus, Food recipes, 030309 nutrition & dietetics, Computer science, media_common.quotation_subject, Value (computer science), 02 engineering and technology, computer.software_genre, Semantics, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 03 medical and health sciences, Resource (project management), 0202 electrical engineering, electronic engineering, information engineering, Quality (business), media_common, 2. Zero hunger, Knowledge graph, 020203 distributed computing, 0303 health sciences, business.industry, ERIAS, Recipe, Nutritional score computation, Lexical pattern, Table (database), [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, business, computer, Natural language processing
Abstract: International audience; The proliferation of recipes and other food information on the Web makes it difficult to identify recipes and foods for people who want to eat healthily. There are various tools related to calculating recipes nutritional values (NVs) but often the results obtained for the same recipe are varied. In this article we present NutriSem, a framework which allows automating the nutritional qualification of cooking recipes. It consists of four steps: (i) lexical enrichment of terms denoting ingredients; (ii) generating of nutritional calculus from lexical pattern and composition table requests; (iii) calculation and allocation of the final score; (iv) translation of the calculated score into a graphical scale. The core of the approach is based on mappings established between text corpora (cooking recipes) and structured data (food composition tables). A Knowledge Graph resource is used to enhance the quality of the mappings and therefore allow a better nutritional qualification of a given recipe.
Published: 2020

139. ESTIMATING R0 OF SARS-COV-2 IN HEALTHCARE SETTINGS

Author: Marie-Paule Gustin, Rodolphe Thiébaut, Philippe Vanhems, Lulla Opatowski, Niccolò Buetti, Jean-Ralph Zahar, Pascal Crépey, Didier Guillemot, Laura Temime, David R M Smith, Audrey Duval, Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Laboratoire des pathogènes émergents -- Emerging Pathogens Laboratory (LPE-Fondation Mérieux), Centre International de Recherche en Infectiologie (CIRI), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), Epidémiologie et modélisation de la résistance aux antimicrobiens - Epidemiology and modelling of bacterial escape to antimicrobials (EMAE), Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was funded in part by the French government through the National Research Agency projects SPHINX (# 17-CE36-0008-01) and MOD-COV. DS is also supported by a Canadian Institutes for Health Research doctoral foreign study award (Funding Reference Number 164263)., ANR-17-CE36-0008,SPHINx,Diffusion de pathogènes au sein des réseaux de soins : une étude de modélisation(2017), Centre International de Recherche en Infectiologie - UMR (CIRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP)
Subjects: 0303 health sciences, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19, medicine.disease, Modelling, Hospital, 03 medical and health sciences, Basic reproduc tion number, 0302 clinical medicine, Healthcare settings, Health care, Transmission, Medicine, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, 030212 general & internal medicine, Medical emergency, Nosocomial, business, 030304 developmental biology
Abstract: To date, no specific estimate of R0 for SARS-CoV-2 is available for healthcare settings. Using inter-individual contact data, we highlight that R0 estimates from the community cannot translate directly to healthcare settings, with pre-pandemic R0 values ranging 1.3-7.7 in three illustrative healthcare institutions. This has implications for nosocomial Covid-19 control.
Published: 2020

140. Correlation between blood telomere length and CD4+ CD8+ T-cell subsets changes 96 weeks after initiation of antiretroviral therapy in HIV-1–positive individuals

Author: Mathieu Chalouni, Javier Rodriguez-Centeno, Assia Samri, Julian Blanco, Natalia Stella-Ascariz, Cedrick Wallet, Hernando Knobel, David Zucman, Belen Alejos Ferreras, Brigitte Autran, Rodolphe Thiebaut, François Raffi, Jose Ramon Arribas, NEAT 001/ANRS 143 Trial Study Group, Red Temática Cooperativa de Investigación en Sida (España), Fondo de Investigaciones Sanitarias, European Regional Development Fund (ERDF/FEDER), Janssen Cilag S.A., Merck KGaA, Instituto de Salud Carlos III, European Regional Development Fund, Bodescot, Myriam, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hospital La Paz Institute for Health Research [Madrid, Espagne], Centre d'Immunologie et des Maladies Infectieuses (CIMI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Germans Trias i Pujol University Hospital [Badalona, Barcelona, Spain] (GTPUH), Epidemiologie-Biostatistique [Bordeaux], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux Ségalen [Bordeaux 2], Hospital del Mar [Barcelone, Espagne], Service de Médecine Interne [Suresnes], Hôpital Foch [Suresnes], Institute of Health Carlos III, Infectious Diseases Department [Nantes], Université de Nantes (UN), This work was supported by NEAT-ID Foundation (not for profit private foundation to promote research and education projects in the HIV field), Red Tematica Cooperativa de Investigacion en Sida, and Fondo de Investigaciones Sanitarias (supported by FEDER funds, grant number PI13/01467) The NEAT 001/ANRS 143 trial was supported by Gilead Sciences, Janssen Pharmaceuticals, and Merck Laboratories. French National Institute for Health and Medical Research–France Recherche Nord and Sud Sida-HIV Hepatites (Inserm-ANRS) was the sponsor and a founder of the trial., NEAT 001/ANRS 143 Trial Study Group, Hospital Universitario La Paz, Institut d’Investigació Germans Trias i Pujol = Germans Trias i Pujol Research Institute (IGTP), IMIM-Hospital del Mar, Generalitat de Catalunya, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre hospitalier universitaire de Nantes (CHU Nantes), Centre d'Immunologie et de Maladies Infectieuses (CIMI), and Germans Trias i Pujol University Hospital [Badalone, Espagne]
Subjects: 0301 basic medicine, CD4-Positive T-Lymphocytes, Male, Physiology, HIV Infections, CD38, CD8-Positive T-Lymphocytes, Lymphocyte Activation, Recomendaciones en el manejo de la pandemia por coronavirus SARS-CoV-2 (Covid-19) en pacientes con trasplante renal, Memory T cells, Correlation, White Blood Cells, 0302 clinical medicine, Animal Cells, T-Lymphocyte Subsets, Antiretroviral Therapy, Highly Active, HIV Seropositivity, Medicine and Health Sciences, Medicine, Cytotoxic T cell, Public and Occupational Health, 030212 general & internal medicine, Immunologia, Telomere Length, [SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Multidisciplinary, Effector, Chromosome Biology, T Cells, Antiretrovirals, Middle Aged, Telomere, Viral Load, Vaccination and Immunization, 3. Good health, SISTM, Body Fluids, Telomeres, Blood, Anti-Retroviral Agents, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, [SDV.IMM]Life Sciences [q-bio]/Immunology, Infectious diseases, Female, Cellular Types, Anatomy, Research Article, Adult, Chromosome Structure and Function, [SDV.IMM] Life Sciences [q-bio]/Immunology, Science, Immune Cells, Immunology, Antiretroviral Therapy, Cytotoxic T cells, Viral diseases, Limfòcits, Chromosomes, Immunophenotyping, 03 medical and health sciences, Immune system, Antiviral Therapy, VIH (Virus), Humans, Blood Cells, business.industry, Biology and Life Sciences, Cell Biology, Antiretroviral therapy, ADP-ribosyl Cyclase 1, CD4 Lymphocyte Count, 030104 developmental biology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, HIV-1, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Preventive Medicine, business, Immunologic Memory, CD8
Abstract: In 31 participants who started first-line antiretroviral therapy in the NEAT 001/ANRS 143 clinical trial, we found after 96 weeks a statistically significant increase in blood telomere length (TL) of 0.04 (T/S Ratio) (p = 0.03). This increase was positively correlated with both the change in the percentage of CD4+ T-cells and with the decrease of CD38+ molecules on Central Memory CD8+ and negatively correlated with the change in the percentage of CD4+ Effector Memory cells. Increase in TL could be an expression of immune reconstitution and the associated decrease in immune activation. We acknowledge for the low statistical power due to the small sample size and the potential for false positive results due to multiple testing. Hence, further studies are needed to confirm these observations. This work was supported by NEAT-ID Foundation (not for profit private foundation to promote research and education projects in the HIV field); Red Temática Cooperativa de Investigación en Sida; and Fondo de Investigaciones Sanitarias (supported by FEDER funds; grant number PI13/01467) The NEAT 001/ANRS 143 trial was supported by Gilead Sciences, Janssen Pharmaceuticals, and Merck Laboratories. French National Institute for Health and Medical Research–France Recherche Nord and Sud Sida- HIV Hepatites (Inserm-ANRS) was the sponsor and a founder of the trial. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Sí
Published: 2020

141. Respiratory mycobiome and suggestion of inter-kingdom network during acute pulmonary exacerbation in cystic fibrosis

Author: Perrine, Soret, Louise-Eva, Vandenborght, Florence, Francis, Noémie, Coron, Raphael, Enaud, Marta, Avalos, Thierry, Schaeverbeke, Patrick, Berger, Michael, Fayon, Rodolphe, Thiebaut, Laurence, Delhaes, Dominique, Turck, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de recherche Cardio-Thoracique de Bordeaux [Bordeaux] (CRCTB), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut National de la Santé et de la Recherche Médicale (INSERM), Genoscreen [Lille], Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), CHU Bordeaux [Bordeaux], Aquitaine’s Care and Research organisation for inflammatory and Immune-Mediated diseases [CHU Bordeaux] (FHU ACRONIM), CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lille, Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Laurence Delhaes has received a research grant from 'Vaincre La Mucoviscidose' (RF20160501626), she is member of ESGHAMI and NGS-MycA working groups of ESCMID and ECCM respectively. Genoscreen Company provided support in the form of Louise-Eva Vandenborght’s salary (AST CT 2016-394)., The Mucofong Investigation Group, Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and Bodescot, Myriam
Subjects: 0301 basic medicine, Male, Mycobiota, Cystic Fibrosis, lcsh:Medicine, Cystic fibrosis, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, 0302 clinical medicine, RNA, Ribosomal, 16S, Respiratory function, lcsh:Science, Lung, Respiratory Tract Infections, [SDV.MP.MYC]Life Sciences [q-bio]/Microbiology and Parasitology/Mycology, Candida, Multidisciplinary, biology, Microbiota, High-Throughput Nucleotide Sequencing, SISTM, medicine.anatomical_structure, Aspergillus, Acute Disease, Disease Progression, Female, Malassezia, Infection, Adult, Article, Microbiology, Scedosporium, 03 medical and health sciences, Young Adult, Pseudomonas, medicine, Humans, lcsh:R, Sputum, Sequence Analysis, DNA, Translational research, biology.organism_classification, medicine.disease, [SDV.MP.MYC] Life Sciences [q-bio]/Microbiology and Parasitology/Mycology, 030104 developmental biology, 030228 respiratory system, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, lcsh:Q, Respiratory tract
Abstract: Lung infections play a critical role in cystic fibrosis (CF) pathogenesis. CF respiratory tract is now considered to be a polymicrobial niche and advances in high-throughput sequencing allowed to analyze its microbiota and mycobiota. However, no NGS studies until now have characterized both communities during CF pulmonary exacerbation (CFPE). Thirty-three sputa isolated from patients with and without CFPE were used for metagenomic high-throughput sequencing targeting 16S and ITS2 regions of bacterial and fungal rRNA. We built inter-kingdom network and adapted Phy-Lasso method to highlight correlations in compositional data. The decline in respiratory function was associated with a decrease in bacterial diversity. The inter-kingdom network revealed three main clusters organized around Aspergillus, Candida, and Scedosporium genera. Using Phy-Lasso method, we identified Aspergillus and Malassezia as relevantly associated with CFPE, and Scedosporium plus Pseudomonas with a decline in lung function. We corroborated in vitro the cross-domain interactions between Aspergillus and Streptococcus predicted by the correlation network. For the first time, we included documented mycobiome data into a version of the ecological Climax/Attack model that opens new lines of thoughts about the physiopathology of CF lung disease and future perspectives to improve its therapeutic management.
Published: 2020

142. PRIMVAC vaccine adjuvanted with Alhydrogel or GLA-SE to prevent placental malaria: a first-in-human, randomised, double-blind, placebo-controlled study

Author: SIRIMA, S. B., Richert, Laura, Chene, A., KONATE, A. T., CAMPION, Cecilia, Dechavanne, S., SEMBLAT, J. P., BENHAMOUDA, N., BAHUAUD, M., Loulergue, P., NEBIE, I., Kabore, M., KARGOUGOU, D., Barry, A., OUATTARA, S. M., BOILET, Valerie, Allais, Florence, Roguet, G., HAVELANGE, N., LOPEZ-PEREZ, E., KUPPERS, A., KONATE, E., Roussillon, Caroline, KANTE, Myriam, BELARBI, L., DIARRA, A., Henry, N., SOULAMA, I., Ouedraogo, A., Esperou, H., Leroy, O., Batteux, F., TARTOUR, E., VIEBIG, N. K., THIEBAUT, Rodolphe, Launay, O., Gamain, B., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], and Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: parasitic diseases, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, SISTM
Abstract: International audience; BackgroundPRIMVAC is a VAR2CSA-derived placental malaria vaccine candidate aiming to prevent serious clinical outcomes of Plasmodium falciparum infection during pregnancy. We assessed the safety and immunogenicity of PRIMVAC adjuvanted with Alhydrogel or glucopyranosyl lipid adjuvant in stable emulsion (GLA-SE) in French and Burkinabe women who were not pregnant.MethodsThis first-in-human, randomised, double-blind, placebo-controlled, dose escalation trial was done in two staggered phases, a phase 1A trial in 18–35-year-old women who were malaria naive in a hospital in France and a subsequent phase 1B trial in women who were naturally exposed to P falciparum and nulligravid in the clinical site of a research centre in Burkina Faso. Volunteers were recruited into four sequential cohorts receiving PRIMVAC intramuscularly at day 0, 28, and 56: two cohorts in France receiving 20 μg or 50 μg of PRIMVAC and then two in Burkina Faso receiving 50 μg or 100 μg of PRIMVAC. Volunteers were randomly assigned (1:1) to two groups (PRIMVAC adjuvanted with either Alhydrogel or GLA-SE) in France and randomly assigned (2:2:1) to three groups (PRIMVAC adjuvanted with either Alhydrogel, GLA-SE, or placebo) in Burkina Faso. Randomisation was centralised, using stratification by cohort and blocks of variable size, and syringes were masked by opaque labels. The primary endpoint was the proportion of participants with any grade 3 or higher adverse reaction to vaccination up until day 35. Safety at later time points as well as humoral and cellular immunogenicity were assessed in secondary endpoints. This trial is registered with ClinicalTrials.gov, NCT02658253.FindingsBetween April 19, 2016, and July 13, 2017, 68 women (18 in France, 50 in Burkina Faso) of 101 assessed for eligibility were included. No serious adverse event related to the vaccine occurred. PRIMVAC antibody titres increased with each dose and seroconversion was observed in all women vaccinated with PRIMVAC (n=57). PRIMVAC antibody titres reached a peak (geometric mean 11 843·0, optical density [OD] 1·0, 95% CI 7559·8–18 552·9 with 100 μg dose and GLA-SE) 1 week after the third vaccination (day 63). Compared with Alhydrogel, GLA-SE tended to improve the PRIMVAC antibody response (geometric mean 2163·5, OD 1·0, 95% CI 1315·7–3557·7 with 100 μg dose and Alhydrogel at day 63). 1 year after the last vaccination, 20 (71%) of 28 women who were vaccinated with PRIMVAC/Alhydrogel and 26 (93%) of 28 women who were vaccinated with PRIMVAC/GLA-SE still had anti-PRIMVAC antibodies, although antibody magnitude was markedly lower (452·4, OD 1·0, 95% CI 321·8–636·1 with 100 μg dose and GLA-SE). These antibodies reacted with native homologous VAR2CSA expressed by NF54-CSA infected erythrocytes (fold change from baseline at day 63 with 100 μg dose and GLA-SE: 10·74, 95% CI 8·36–13·79). Limited cross-recognition, restricted to sera collected from women that received the 100 μg PRIMVAC dose, was observed against heterologous VAR2CSA variants expressed by FCR3-CSA (fold change from baseline at day 63: 1·49, 95% CI 1·19–1·88) and 7G8-CSA infected erythrocytes (1·2, 1·08–1·34).InterpretationPRIMVAC adjuvanted with Alhydrogel or GLA-SE had an acceptable safety profile, was immunogenic, and induced functional antibodies reacting with the homologous VAR2CSA variant expressed by NF54-CSA infected erythrocytes. Cross-reactivity against heterologous VAR2CSA variants was limited and only observed in the higher dose group. An alternate schedule of immunisation, antigen dose, and combinations with other VAR2CSA-based vaccines are envisaged to improve the cross-reactivity against heterologous VAR2CSA variants.FundingBundesministerium für Bildung und Forschung, through Kreditanstalt für Wiederaufbau, Germany; Inserm, and Institut National de Transfusion Sanguine, France; Irish Aid, Department of Foreign Affairs and Trade, Ireland.
Published: 2020

143. Analyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect

Author: Jean-Daniel Lelièvre, Rodolphe Thiébaut, Aurélie Wiedemann, Edouard Lhomme, Christine Lacabaratz, Laura Richert, Boris P. Hejblum, Yves Levy, CHU de Bordeaux Pellegrin [Bordeaux], Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Hejblum, Boris
Subjects: 0301 basic medicine, Adult, Male, Computer science, T-Lymphocytes, Immunology, Datasets as Topic, HIV Infections, Computational biology, Bivariate analysis, Models, Biological, Statistical power, 03 medical and health sciences, 0302 clinical medicine, [SDV.IMM.VAC] Life Sciences [q-bio]/Immunology/Vaccinology, Immunogenicity, Vaccine, Antigen, Linear regression, Immunology and Allergy, Humans, Computer Simulation, HIV vaccine, Randomized Controlled Trials as Topic, AIDS Vaccines, Immunity, Cellular, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Immunogenicity, Subtraction, Flow Cytometry, Healthy Volunteers, 3. Good health, SISTM, Clinical trial, Benchmarking, 030104 developmental biology, Treatment Outcome, Research Design, HIV-1, Linear Models, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Female, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, [STAT.ME]Statistics [stat]/Methodology [stat.ME], 030215 immunology
Abstract: International audience; Evaluation of immunogenicity is a key step in the clinical development of novel vaccines. T-cell responses to vaccine candidates are typically assessed by intracellular cytokine staining (ICS) using multiparametric flow cytometry. A conventional statistical approach to analyze ICS data is to compare, between vaccine regimens or between baseline and post-vaccination of the same regimen depending on the trial design, the percentages of cells producing a cytokine of interest after ex vivo stimulation of peripheral blood mononuclear cells (PBMC) with vaccineantigens, after subtracting the non-specific response (of unstimulated cells) of each sample. Subtraction of the non-specific response is aimed at capturing the specific response to the antigen, but raises methodological issues related to measurement error and statistical power. We describe here a new statistical approach to analyze ICS data from vaccine trials. We propose a bivariate linear random-effect regression model for estimating the nonspecificand antigen-specific ICS responses. We benchmarked the performance of the model in terms of both bias and control of type-I and -II errors in comparison with conventional approaches, and applied it to simulated data as well as real pre- and post-vaccination data from two recent HIV vaccine trials (ANRS VRI01 in healthy volunteers and therapeutic VRI02 ANRS 149 LIGHT in HIV-infected participants). The model was as good as the conventional approaches (with or without subtraction of the non-specific response) in all simulation scenarios in terms of statistical performance, whereas the conventional approaches did not provide robust results across all scenarios. The proposed model estimated the T-cell responses to the antigens without any effect of the nonspecific response on the specific response, irrespective of the correlation between the nonspecific and specific responses. This novel method of analyzing T-cell immunogenicity data based on bivariate modelling allows consideration of all T-cell data and is more flexible than conventional methods, and so yields more detailed results and enables accurate interpretation of vaccine efficacy.
Published: 2020

144. Pre-Training a Neural Language Model Improves the Sample Efficiency of an Emergency Room Classification Model

Author: XU, Binbin, GIL-JARDINE, Cedric, THIESSARD, Frantz, TELLIER, Éric, AVALOS, Marta, LAGARDE, Emmanuel, Avalos, Marta, Roman Barták, Eric Bell, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Pellegrin, CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Association for the Advancement of Artificial Intelligence
Subjects: FOS: Computer and information sciences, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Computer Science - Machine Learning, [STAT.AP]Statistics [stat]/Applications [stat.AP], Computer Science - Computation and Language, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Computer Science - Artificial Intelligence, ERIAS, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], SISTM, Machine Learning (cs.LG), [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Artificial Intelligence (cs.AI), ComputingMethodologies_PATTERNRECOGNITION, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [STAT.AP] Statistics [stat]/Applications [stat.AP], IETO, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Computation and Language (cs.CL), [STAT.ME]Statistics [stat]/Methodology [stat.ME], [INFO.INFO-AU] Computer Science [cs]/Automatic Control Engineering
Abstract: To build a French national electronic injury surveillance system based on emergency room visits, we aim to develop a coding system to classify their causes from clinical notes in free-text. Supervised learning techniques have shown good results in this area but require a large amount of expert annotated dataset which is time consuming and costly to obtain. We hypothesize that the Natural Language Processing Transformer model incorporating a generative self-supervised pre-training step can significantly reduce the required number of annotated samples for supervised fine-tuning. In this preliminary study, we test our hypothesis in the simplified problem of predicting whether a visit is the consequence of a traumatic event or not from free-text clinical notes. Using fully re-trained GPT-2 models (without OpenAI pre-trained weights), we assess the gain of applying a self-supervised pre-training phase with unlabeled notes prior to the supervised learning task. Results show that the number of data required to achieve a ginve level of performance (AUC>0.95) was reduced by a factor of 10 when applying pre-training. Namely, for 16 times more data, the fully-supervised model achieved an improvement, Version of the published manuscript
Published: 2020

145. Health conditions and the risk of home injury in French adults: Results from a prospective study of the MAVIE cohort

Author: Dupuy, Contrand, Sztal-Kutas, Avalos, Lagarde, Rojas Castro, Orriols, Université de Bordeaux (UB), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Calyxis Pôle d'Expertise des Risques, This study was financed jointly by the Institut de recherche en santé publique (IReSP) [CONV 067-00187II], the Agence nationale de sécurité du medicament et des produits de santé [conv 2014S029], the Université de Bordeaux and the Région Nouvelle Aquitaine as part of the Cassiopée project [conv 2014-1R30504 -00003101]. MR is the recipient of an INSERM/Région Nouvelle Aquitaine doctoral grant and is affiliated to the Digital Health program funded by France’s Strategic Investment Programme. The MAVIE observatory is coordinated by the INSERM U1219-IETO team and Calyxis, pôle d’expertise du risque, with the support of the mutual insurance companies MAIF, MAAF, MACIF and Decathlon., and Avalos, Marta
Subjects: Pediatrics, Cohort Studies, Sciatica, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], Risk Factors, Vertigo, Back pain, 030212 general & internal medicine, Prospective Studies, Prospective cohort study, [STAT.CO]Statistics [stat]/Computation [stat.CO], [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], biology, Home Accident, Middle Aged, 3. Good health, Home injury, Cohort, community, Falls, medicine.symptom, [STAT.ME]Statistics [stat]/Methodology [stat.ME], Cohort study, Adult, medicine.medical_specialty, longitudinal, mixed methods, web-based, Dizziness, [STAT.CO] Statistics [stat]/Computation [stat.CO], 03 medical and health sciences, cohort study, medicine, Humans, Risk factor, Aged, business.industry, Prevention, Public Health, Environmental and Occupational Health, home, biology.organism_classification, Data information, Back Pain, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Relative risk, Wounds and Injuries, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, 030217 neurology & neurosurgery
Abstract: BackgroundHome injury (HI) is a significant cause of mortality and morbidity in adults of all ages. Health conditions significantly impact HI among old adults, but little is known for other adults.Study designProspective cohort study.ObjectiveWe assessed the associations between health-related factors and HI’s risk in a French study, the MAVIE (Mutualistes pour la recherche contre les Accidents de la VIE courante) cohort.MethodsPoisson mixed models were fitted using health-related data information (diseases, treatments and disabilities) at baseline and the number of injuries prospectively recorded during the follow-up, adjusting for significant sociodemographics and exposure to a range of home activities. Attributable fractions were estimated based on risk ratio (RR) estimations measured in the fully adjusted models.ResultsA total of 6146 dwelling adults aged 15 or older were followed up for 5.1 years on average. Vertigo or dizziness (RR=2.36, 95% CI 1.06 to 5.01) and sciatica or back pain (RR=1.49, 95% CI 1.08 to 2.05) were independently associated with an increased risk of HI. These two groups of conditions showed the most significant associations among people aged 15–49, whereas musculoskeletal diseases other than rachialgias and arthropathies were the most significant health-related risk factor in people aged 50 and older. Sciatica or back pain represented the highest burden of HIs in overall adults (8%) and among people aged 15–49 (12%).ConclusionOur results suggest that adults with musculoskeletal disorders and vertigo or dizziness symptoms have a higher risk of HI, regardless of age.
Published: 2020

146. A model for establishment, maintenance and reactivation of the immune response after vaccination against Ebola virus

Author: Balelli, Irene, Pasin, Chloé, Prague, Mélanie, Crauste, Fabien, Effelterre, Thierry Van, Bockstal, Viki, Solforosi, Laura, Thiébaut, Rodolphe, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Columbia University Medical Center (CUMC), Columbia University [New York], Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Janssen Pharmaceutica [Beerse], Janssen Vaccines & Prevention [Leiden], This work has received funding from the Innovative Medicines Initiative2 Joint Undertaking under Grant Agreement EBOVAC1 (No. 115854). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. This work was also supported by the Investissements d’Avenir program managed by the ANR under reference ANR-10-LABX-77., Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), This work has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement EBOVAC1 (N° 115854). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA. The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or writing the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. This work was also supported by the Investissements d’Avenir program managed by the ANR under reference ANR-10-LABX-77., Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), and Balelli, Irene
Subjects: Mechanistic modeling, Vaccination, [MATH] Mathematics [math], Immunological memory, SISTM, [SDV.IMM.VAC] Life Sciences [q-bio]/Immunology/Vaccinology, Heterologous vaccination, Calibration, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, [MATH]Mathematics [math], Sensitivity analysis, Ebola Virus, Identifiability analysis
Abstract: International audience; The 2014-2016 Ebola outbreak in West Africa has triggered accelerated development of several preventive vaccines against Ebola virus. Under the EBOVAC1 consortium, three phase I studies were carried out to assess safety and immunogenicity of a two-dose heterologous vaccination regimen developed by Janssen Vaccines and Prevention in collaboration with Bavarian Nordic. To describe the immune responses induced by the two-dose heterologous vaccine regimen, we propose a mechanistic ODE based model, which takes into account the role of immunological memory. We perform identifiability and sensitivity analysis of the proposed model to establish which kind of biological data are ideally needed in order to accurately estimate parameters, and additionally, which of those are non-identifiable based on the available data. Antibody concentrations data from phase I studies have been used to calibrate the model and show its ability in reproducing the observed antibody dynamics. Together with other factors, the establishment of an effective and reactive immunological memory is of pivotal importance for several prophylactic vaccines. We show that introducing a memory compartment in our calibrated model allows to evaluate the magnitude of the immune response induced by a booster dose and its long-term persistence afterwards.
Published: 2020

147. Population modeling of early COVID-19 epidemic dynamics in French regions and estimation of the lockdown impact on infection rate

Author: Annabelle Collin, Rodolphe Thiébaut, Quentin Clairon, Philippe Moireau, Boris P. Hejblum, Mélanie Prague, Linda Wittkop, Dan Dutartre, Prague, Mélanie, Université de Bordeaux (UB), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, CHU Bordeaux [Bordeaux], Service Expérimentation et Développement [Bordeaux] (SED), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), and This work is supported in part by Inria Mission COVID19, project GESTEPID.
Subjects: Coronavirus disease 2019 (COVID-19), Transmission rate, Population, [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], Epidemic dynamics, [MATH.MATH-DS] Mathematics [math]/Dynamical Systems [math.DS], Stochastic approximation, 03 medical and health sciences, 0302 clinical medicine, Population modeling, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Econometrics, 030212 general & internal medicine, education, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], 030304 developmental biology, Estimation, 0303 health sciences, education.field_of_study, Non-pharmaceutical intervention, SARS-CoV-2, COVID-19, [SDV.IMM.IMM]Life Sciences [q-bio]/Immunology/Immunotherapy, Infection rate, Compartmental model, Geography, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, France, [SDV.IMM.IMM] Life Sciences [q-bio]/Immunology/Immunotherapy
Abstract: We developed a multi-level model of the French COVID-19 epidemic at the regional level. We rely on a global extended Susceptible-Exposed-Infectious-Recovered (SEIR) mechanistic model as a simplified representation of the average epidemic process, with the addition of region specific random effects. Combining several French public datasets on the early dynamics of the epidemic, we estimate region-specific key parameters conditionally on this mechanistic model through Stochastic Approximation Expectation Maximization (SAEM) optimization usingMonolixsoftware. We thus estimate the basic reproductive numbers by region before lockdown (with a national average at 2.81 with 95% Confidence Interval [2.58; 3.07]), attack rates (i.e. percentages of infected people) over time per region which range between 1.9% and 9.9% as of May 11th, 2020, and the impact of nationwide lockdown on the infection rate which decreased the transmission rate by 76% towards reproductive numbers ranging from 0.63 to 0.73 at the end of lockdown across regions. These results confirm the low population immunity, the strong effect of the lockdown on the dynamics of the epidemics and the need for further intervention when lifting the lockdown to avoid an epidemic rebound.
Published: 2020

148. Immune Alterations in a Patient with SARS-CoV-2-Related Acute Respiratory Distress Syndrome

Author: Bouadma, Lila, WIEDEMANN, A., PATRIER, J., SURENAUD, M., WICKY, P. H., FOUCAT, E., DIEHL, J. L., Hejblum, Boris P., SINNAH, F., DE MONTMOLLIN, E., Lacabaratz, C., THIEBAUT, Rodolphe, Timsit, J. F., Levy, Y., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract: International audience; We report a longitudinal analysis of the immune response associated with a fatal case of COVID-19 in Europe. This patient exhibited a rapid evolution towards multiorgan failure. SARS-CoV-2 was detected in multiple nasopharyngeal, blood, and pleural samples, despite antiviral and immunomodulator treatment. Clinical evolution in the blood was marked by an increase (2–3-fold) in differentiated effector T cells expressing exhaustion (PD-1) and senescence (CD57) markers, an expansion of antibody-secreting cells, a 15-fold increase in γδ T cell and proliferating NK-cell populations, and the total disappearance of monocytes, suggesting lung trafficking. In the serum, waves of a pro-inflammatory cytokine storm, Th1 and Th2 activation, and markers of T cell exhaustion, apoptosis, cell cytotoxicity, and endothelial activation were observed until the fatal outcome. This case underscores the need for well-designed studies to investigate complementary approaches to control viral replication, the source of the hyperinflammatory status, and immunomodulation to target the pathophysiological response. The investigation was conducted as part of an overall French clinical cohort assessing patients with COVID-19 and registered in clinicaltrials.gov under the following number: NCT04262921.
Published: 2020

149. Optimal priming of poxvirus vector (NYVAC)-based HIV vaccine regimens for T cell responses requires three DNA injections. Results of the randomized multicentre EV03/ANRS VAC20 Phase I/II Trial

Author: Jean-Daniel Lelièvre, Ralf Wagner, Hans Wolf, Pierre-Alexandre Bart, Bernd Salzberger, Nicole L. Yates, Georgia D. Tomaras, Yves Levy, Aurélie Wiedemann, Rodolphe Thiébaut, Raphael Gottardo, Wolfgang Stöhr, David M. Koelle, Sheena McCormack, Véronique Rieux, Song Ding, Giuseppe Pantaleo, Christine Lacabaratz, Kim Ellefsen-Lavoie, Odile Launay, Bryan T. Mayer, David C. Montefiori, Geneviève Chêne, Mathieu Surenaud, Jonathan Weber, DARMIGNY, SANDRINE, Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), CHU Henri Mondor, Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), University College of London [London] (UCL), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Imperial College London, University of Washington [Seattle], Universität Regensburg (UR), Duke University Medical Center, Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), EuroVacc Foundation (EVF), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and CHU Henri Mondor [Créteil]
Subjects: RNA viruses, Male, Physiology, HIV Antigens, [SDV]Life Sciences [q-bio], Antibody Response, Priming (immunology), CD8-Positive T-Lymphocytes, Pathology and Laboratory Medicine, Biochemistry, White Blood Cells, Immunodeficiency Viruses, Animal Cells, 1108 Medical Microbiology, Immune Physiology, Medicine and Health Sciences, Vaccines, DNA, Clinical endpoint, Cytotoxic T cell, Enzyme-Linked Immunoassays, HIV vaccine, Biology (General), Immune Response, ComputingMilieux_MISCELLANEOUS, AIDS Vaccines, Vaccines, Innate Immune System, 0303 health sciences, Immune System Proteins, biology, T Cells, ELISPOT, 030302 biochemistry & molecular biology, env Gene Products, Human Immunodeficiency Virus, T-Lymphocytes, Helper-Inducer, Middle Aged, 3. Good health, [SDV] Life Sciences [q-bio], Infectious Diseases, medicine.anatomical_structure, Medical Microbiology, 1107 Immunology, Viral Pathogens, Viruses, Cytokines, Female, Cellular Types, Pathogens, Antibody, Research Article, 0605 Microbiology, Adult, Infectious Disease Control, Adolescent, QH301-705.5, Immune Cells, T cell, Genetic Vectors, Immunology, Research and Analysis Methods, Microbiology, Antibodies, Interferon-gamma, 03 medical and health sciences, Virology, Retroviruses, Genetics, medicine, Humans, Immunoassays, Microbial Pathogens, Molecular Biology, 030304 developmental biology, Blood Cells, business.industry, Poxviridae, Lentivirus, Organisms, Biology and Life Sciences, Proteins, HIV, Cell Biology, Molecular Development, RC581-607, Regimen, Immune System, Immunologic Techniques, biology.protein, Parasitology, Immunologic diseases. Allergy, business, Developmental Biology
Abstract: DNA vectors have been widely used as a priming of poxvirus vaccine in prime/boost regimens. Whether the number of DNA impacts qualitatively or quantitatively the immune response is not fully explored. With the aim to reinforce T-cell responses by optimizing the prime-boost regimen, the multicentric EV03/ANRS VAC20 phase I/II trial, randomized 147 HIV-negative volunteers to either 3xDNA plus 1xNYVAC (weeks 0, 4, 8 plus 24; n = 74) or to 2xDNA plus 2xNYVAC (weeks 0, 4 plus 20, 24; n = 73) groups. T-cell responses (IFN-γ ELISPOT) to at least one peptide pool were higher in the 3xDNA than the 2xDNA groups (91% and 80% of vaccinees) (P = 0.049). In the 3xDNA arm, 26 (37%) recipients developed a broader T-cell response (Env plus at least to one of the Gag, Pol, Nef pools) than in the 2xDNA (15; 22%) arms (primary endpoint; P = 0.047) with a higher magnitude against Env (at week 26) (P, Author summary Development of a safe and effective HIV-1 vaccine would undoubtedly be the best solution for the ultimate control of the worldwide AIDS pandemic. To date, only one large phase III trial (RV144 Thai study) showed a partial and modest protection against HIV infection. This result raised hope in the field and encouraged the development of vaccines or strategies in order to improve vaccine efficacy. Several vaccine strategies designed to elicit broad HIV-specific T cells and/or neutralizing antibodies to prevent HIV-1 transmission are under evaluation. Among diverse candidate vaccines, the safety and immunogenicity of multi-gene DNA-based and Pox-virus derived vaccines have been evaluated in several clinical studies. The present study was designed to optimize the combination of these two vaccines with the aim of determining the optimal number of DNA primes for a poxvirus-based HIV vaccine regimen. We show here that the prime boost combination is highly immunogenic and that the number of DNA primes induces differentially T cell and antibody responses. A better priming of poxvirus-based vaccine regimens for T cells is obtained with 3 DNA injections. Our results contribute and extend data of several preclinical studies pointing out the potential interest of DNA as a prime capable not only of improving immune responses but also of imprinting the long-term responses to boost vaccines.
Published: 2020

150. Public Health and Epidemiology Informatics: Recent Research Trends Moving toward Public Health Data Science

Author: Cossin, Sébastien, Thiébaut, Rodolphe, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Ethics, Public health, International Medical Informatics Association, Surveillance, Epidemiology, Medical informatics, ERIAS, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Data science, SISTM
Abstract: International audience; Objectives: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics. Methods: PubMed searches of 2019 literature concerning public health and epidemiology informatics were conducted and the returned references were reviewed by the two section editors to select 14 candidate best papers. These papers were then peer-reviewed by external reviewers to allow the Editorial Committee a curated selection of the best papers. Results: Among the 835 references retrieved from PubMed, two were finally selected as best papers. The first best paper leverages satellite images and deep learning to identify remote rural communities in low-income countries; the second paper describes the development of a worldwide human disease surveillance system based on near real-time news data from the GDELT project. Internet data and electronic health records are still widely used to detect and monitor disease activity. Identifying and targeting specific audiences for public health interventions is a growing subject of interest. Conclusions: The ever-increasing amount of data available offers endless opportunities to develop methods and tools that could assist public health surveillance and intervention belonging to the growing field of public health Data Science. The transition from proofs of concept to real world applications and adoption by health authorities remains a difficult leap to make.
Published: 2020

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