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3. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study.

Author

Ostropolets, Anna, Albogami, Yasser, Conover, Mitchell, Banda, Juan, Baumgartner, William, Blacketer, Clair, Desai, Priyamvada, DuVall, Scott, Fortin, Stephen, Gilbert, James, Golozar, Asieh, Ide, Joshua, Kanter, Andrew, Kern, David, Kim, Chungsoo, Lai, Lana, Li, Chenyu, Liu, Feifan, Lynch, Kristine, Minty, Evan, Neves, Maria, Ng, Ding, Obene, Tontel, Pera, Victor, Pratt, Nicole, Rao, Gowtham, Rappoport, Nadav, Reinecke, Ines, Saroufim, Paola, Shoaibi, Azza, Simon, Katherine, Swerdel, Joel, Voss, Erica, Weaver, James, Zhang, Linying, Hripcsak, George, Ryan, Patrick, and Suchard, Marc

Subjects
credibility, observational data, open science, reproducibility, Humans, Research Personnel, Databases, Factual
Abstract

OBJECTIVE: Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations variability on patient characteristics. MATERIALS AND METHODS: Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. RESULTS: On average, the teams interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. CONCLUSIONS: Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Published
2023

4. Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab: An Observational Health Data Sciences and Informatics Network Study

Author

Cai, Cindy X., Nishimura, Akihiko, Bowring, Mary G., Westlund, Erik, Tran, Diep, Ng, Jia H., Nagy, Paul, Cook, Michael, McLeggon, Jody-Ann, DuVall, Scott L., Matheny, Michael E., Golozar, Asieh, Ostropolets, Anna, Minty, Evan, Desai, Priya, Bu, Fan, Toy, Brian, Hribar, Michelle, Falconer, Thomas, Zhang, Linying, Lawrence-Archer, Laurence, Boland, Michael V., Goetz, Kerry, Hall, Nathan, Shoaibi, Azza, Reps, Jenna, Sena, Anthony G., Blacketer, Clair, Swerdel, Joel, Jhaveri, Kenar D., Lee, Edward, Gilbert, Zachary, Zeger, Scott L., Crews, Deidra C., Suchard, Marc A., Hripcsak, George, and Ryan, Patrick B.

Published
2024
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5. Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer: A Systematic Review

Author

Lawlor, Ailbhe, Lin, Carol, Gómez Rivas, Juan, Ibáñez, Laura, Abad López, Pablo, Willemse, Peter-Paul, Imran Omar, Muhammad, Remmers, Sebastiaan, Cornford, Philip, Rajwa, Pawel, Nicoletti, Rossella, Gandaglia, Giorgio, Yuen-Chun Teoh, Jeremy, Moreno Sierra, Jesús, Golozar, Asieh, Bjartell, Anders, Evans-Axelsson, Susan, N'Dow, James, Zong, Jihong, Ribal, Maria J., Roobol, Monique J., Van Hemelrijck, Mieke, and Beyer, Katharina

Published
2024
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6. Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data

Author

Gandaglia, Giorgio, Pellegrino, Francesco, Golozar, Asieh, De Meulder, Bertrand, Abbott, Thomas, Achtman, Ariel, Imran Omar, Muhammad, Alshammari, Thamir, Areia, Carlos, Asiimwe, Alex, Beyer, Katharina, Bjartell, Anders, Campi, Riccardo, Cornford, Philip, Falconer, Thomas, Feng, Qi, Gong, Mengchun, Herrera, Ronald, Hughes, Nigel, Hulsen, Tim, Kinnaird, Adam, Lai, Lana Y.H., Maresca, Gianluca, Mottet, Nicolas, Oja, Marek, Prinsen, Peter, Reich, Christian, Remmers, Sebastiaan, Roobol, Monique J., Sakalis, Vasileios, Seager, Sarah, Smith, Emma J., Snijder, Robert, Steinbeisser, Carl, Thurin, Nicolas H., Hijazy, Ayman, van Bochove, Kees, Van den Bergh, Roderick C.N., Van Hemelrijck, Mieke, Willemse, Peter-Paul, Williams, Andrew E., Zounemat Kermani, Nazanin, Evans-Axelsson, Susan, Briganti, Alberto, and N'Dow, James

Published
2024
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7. Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Author

Kostka, Kristin, Duarte-Salles, Talita, Prats-Uribe, Albert, Sena, Anthony G, Pistillo, Andrea, Khalid, Sara, Lai, Lana YH, Golozar, Asieh, Alshammari, Thamir M, Dawoud, Dalia M, Nyberg, Fredrik, Wilcox, Adam B, Andryc, Alan, Williams, Andrew, Ostropolets, Anna, Areia, Carlos, Jung, Chi Young, Harle, Christopher A, Reich, Christian G, Blacketer, Clair, Morales, Daniel R, Dorr, David A, Burn, Edward, Roel, Elena, Tan, Eng Hooi, Minty, Evan, DeFalco, Frank, de Maeztu, Gabriel, Lipori, Gigi, Alghoul, Hiba, Zhu, Hong, Thomas, Jason A, Bian, Jiang, Park, Jimyung, Roldán, Jordi Martínez, Posada, Jose D, Banda, Juan M, Horcajada, Juan P, Kohler, Julianna, Shah, Karishma, Natarajan, Karthik, Lynch, Kristine E, Liu, Li, Schilling, Lisa M, Recalde, Martina, Spotnitz, Matthew, Gong, Mengchun, Matheny, Michael E, Valveny, Neus, Weiskopf, Nicole G, Shah, Nigam, Alser, Osaid, Casajust, Paula, Park, Rae Woong, Schuff, Robert, Seager, Sarah, DuVall, Scott L, You, Seng Chan, Song, Seokyoung, Fernández-Bertolín, Sergio, Fortin, Stephen, Magoc, Tanja, Falconer, Thomas, Subbian, Vignesh, Huser, Vojtech, Ahmed, Waheed-Ul-Rahman, Carter, William, Guan, Yin, Galvan, Yankuic, He, Xing, Rijnbeek, Peter R, Hripcsak, George, Ryan, Patrick B, Suchard, Marc A, and Prieto-Alhambra, Daniel

Subjects
Clinical Research, Infectious Diseases, Prevention, 2.4 Surveillance and distribution, Aetiology, Good Health and Well Being, OHDSI, OMOP CDM, descriptive epidemiology, real world data, real world evidence, open science, Clinical Sciences, Public Health and Health Services
Abstract

PurposeRoutinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Patients and methodsWe conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.ResultsWe aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.ConclusionWe constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.

Published
2022

8. Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study

Author

Reyes, Carlen, Pistillo, Andrea, Fernández-Bertolín, Sergio, Recalde, Martina, Roel, Elena, Puente, Diana, Sena, Anthony G, Blacketer, Clair, Lai, Lana, Alshammari, Thamir M, Ahmed, Waheed-UI-Rahman, Alser, Osaid, Alghoul, Heba, Areia, Carlos, Dawoud, Dalia, Prats-Uribe, Albert, Valveny, Neus, de Maeztu, Gabriel, Redó, Luisa Sorlí, Roldan, Jordi Martinez, Montesinos, Inmaculada Lopez, Schilling, Lisa M, Golozar, Asieh, Reich, Christian, Posada, Jose D, Shah, Nigam, You, Seng Chan, Lynch, Kristine E, DuVall, Scott L, Matheny, Michael E, Nyberg, Fredrik, Ostropolets, Anna, Hripcsak, George, Rijnbeek, Peter R, Suchard, Marc A, Ryan, Patrick, Kostka, Kristin, and Duarte-Salles, Talita

Subjects
Clinical Research, Cardiovascular, Aetiology, 2.4 Surveillance and distribution, Good Health and Well Being, COVID-19, COVID-19 Testing, Cohort Studies, Comorbidity, Female, Hospitalization, Humans, Hypertension, Middle Aged, Retrospective Studies, SARS-CoV-2, epidemiology, hypertension, Clinical Sciences, Public Health and Health Services, Other Medical and Health Sciences
Abstract

ObjectiveTo characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.Design and settingThis is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020.ParticipantsTwo non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days.OutcomesDemographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported.ResultsWe identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension.ConclusionsCOVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.

Published
2021

9. COVID-19 in patients with autoimmune diseases: characteristics and outcomes in a multinational network of cohorts across three countries

Author

Tan, Eng Hooi, Sena, Anthony G, Prats-Uribe, Albert, You, Seng Chan, Ahmed, Waheed-Ul-Rahman, Kostka, Kristin, Reich, Christian, Duvall, Scott L, Lynch, Kristine E, Matheny, Michael E, Duarte-Salles, Talita, Bertolin, Sergio Fernandez, Hripcsak, George, Natarajan, Karthik, Falconer, Thomas, Spotnitz, Matthew, Ostropolets, Anna, Blacketer, Clair, Alshammari, Thamir M, Alghoul, Heba, Alser, Osaid, Lane, Jennifer CE, Dawoud, Dalia M, Shah, Karishma, Yang, Yue, Zhang, Lin, Areia, Carlos, Golozar, Asieh, Recalde, Martina, Casajust, Paula, Jonnagaddala, Jitendra, Subbian, Vignesh, Vizcaya, David, Lai, Lana YH, Nyberg, Fredrik, Morales, Daniel R, Posada, Jose D, Shah, Nigam H, Gong, Mengchun, Vivekanantham, Arani, Abend, Aaron, Minty, Evan P, Suchard, Marc, Rijnbeek, Peter, Ryan, Patrick B, and Prieto-Alhambra, Daniel

Subjects
Infectious Diseases, Lung, Emerging Infectious Diseases, Pneumonia & Influenza, Clinical Research, Influenza, Autoimmune Disease, Cardiovascular, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Autoimmune Diseases, COVID-19, Cohort Studies, Female, Hospitalization, Humans, Influenza, Human, Male, Middle Aged, Prevalence, Prognosis, Republic of Korea, SARS-CoV-2, Spain, United States, Young Adult, autoimmune condition, mortality, hospitalization, open science, Observational Health Data Sciences and Informatics, Observational Medical Outcomes Partnership, Clinical Sciences, Immunology, Public Health and Health Services, Arthritis & Rheumatology
Abstract

ObjectivePatients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.MethodsA multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center [USA, Optum (USA), Department of Veterans Affairs (USA), Information System for Research in Primary Care-Hospitalization Linked Data (Spain) and claims data from IQVIA Open Claims (USA) and Health Insurance and Review Assessment (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalized between January and June 2020 with COVID-19, and similar patients hospitalized with influenza in 2017-18 were included. Outcomes were death and complications within 30 days of hospitalization.ResultsWe studied 133 589 patients diagnosed and 48 418 hospitalized with COVID-19 with prevalent autoimmune diseases. Most patients were female, aged ≥50 years with previous comorbidities. The prevalence of hypertension (45.5-93.2%), chronic kidney disease (14.0-52.7%) and heart disease (29.0-83.8%) was higher in hospitalized vs diagnosed patients with COVID-19. Compared with 70 660 hospitalized with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2-4.3% vs 6.32-24.6%).ConclusionCompared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.

Published
2021

10. Characteristics and Outcomes of Over 300,000 Patients with COVID-19 and History of Cancer in the United States and SpainCharacteristics of 300,000 COVID-19 Individuals with Cancer

Author

Roel, Elena, Pistillo, Andrea, Recalde, Martina, Sena, Anthony G, Fernández-Bertolín, Sergio, Aragón, Maria, Puente, Diana, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Areia, Carlos, Blacketer, Clair, Carter, William, Casajust, Paula, Culhane, Aedin C, Dawoud, Dalia, DeFalco, Frank, DuVall, Scott L, Falconer, Thomas, Golozar, Asieh, Gong, Mengchun, Hester, Laura, Hripcsak, George, Tan, Eng Hooi, Jeon, Hokyun, Jonnagaddala, Jitendra, Lai, Lana YH, Lynch, Kristine E, Matheny, Michael E, Morales, Daniel R, Natarajan, Karthik, Nyberg, Fredrik, Ostropolets, Anna, Posada, José D, Prats-Uribe, Albert, Reich, Christian G, Rivera, Donna R, Schilling, Lisa M, Soerjomataram, Isabelle, Shah, Karishma, Shah, Nigam H, Shen, Yang, Spotniz, Matthew, Subbian, Vignesh, Suchard, Marc A, Trama, Annalisa, Zhang, Lin, Zhang, Ying, Ryan, Patrick B, Prieto-Alhambra, Daniel, Kostka, Kristin, and Duarte-Salles, Talita

Subjects
Biomedical and Clinical Sciences, Health Services and Systems, Health Sciences, Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Patient Safety, Infectious Diseases, Rare Diseases, Hematology, Cancer, Urologic Diseases, Prevention, Clinical Research, Aetiology, 2.4 Surveillance and distribution, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, COVID-19, Child, Cohort Studies, Comorbidity, Databases, Factual, Female, Hospitalization, Humans, Immunosuppression Therapy, Influenza, Human, Male, Middle Aged, Neoplasms, Outcome Assessment, Health Care, Pandemics, Prevalence, Risk Factors, SARS-CoV-2, Spain, United States, Young Adult, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundWe described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza.MethodsWe conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes.ResultsWe included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events.ConclusionsPatients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent.ImpactThis study provides epidemiologic characteristics that can inform clinical care and etiologic studies.

Published
2021

11. Use of repurposed and adjuvant drugs in hospital patients with covid-19: multinational network cohort study.

Author

Prats-Uribe, Albert, Sena, Anthony G, Lai, Lana Yin Hui, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Areia, Carlos, Carter, William, Casajust, Paula, Dawoud, Dalia, Golozar, Asieh, Jonnagaddala, Jitendra, Mehta, Paras P, Gong, Mengchun, Morales, Daniel R, Nyberg, Fredrik, Posada, Jose D, Recalde, Martina, Roel, Elena, Shah, Karishma, Shah, Nigam H, Schilling, Lisa M, Subbian, Vignesh, Vizcaya, David, Zhang, Lin, Zhang, Ying, Zhu, Hong, Liu, Li, Cho, Jaehyeong, Lynch, Kristine E, Matheny, Michael E, You, Seng Chan, Rijnbeek, Peter R, Hripcsak, George, Lane, Jennifer Ce, Burn, Edward, Reich, Christian, Suchard, Marc A, Duarte-Salles, Talita, Kostka, Kristin, Ryan, Patrick B, and Prieto-Alhambra, Daniel

Subjects
Humans, Ceftriaxone, Azithromycin, Ritonavir, Hydroxychloroquine, Fluoroquinolones, Adrenal Cortex Hormones, Enoxaparin, Vitamin D, Drug Combinations, Treatment Outcome, Chemotherapy, Adjuvant, Cohort Studies, Safety, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Infant, Infant, Newborn, Inpatients, United States, China, Spain, Female, Male, Young Adult, Republic of Korea, Electronic Health Records, Drug Repositioning, Lopinavir, Administrative Claims, Healthcare, COVID-19, SARS-CoV-2, Administrative Claims, Healthcare, and over, Chemotherapy, Adjuvant, Preschool, Newborn, General & Internal Medicine, Clinical Sciences, Public Health and Health Services
Abstract

ObjectiveTo investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents.DesignMultinational network cohort study.SettingHospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea.Participants303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020.Main outcome measuresPrescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19.ResultsOf the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from

Published
2021

12. Effect of Statin Use on Inflammation and Immune Activation Biomarkers in HIV-Infected Persons on Effective Antiretroviral Therapy

Author

Hussain, Shehnaz K, Golozar, Asieh, Widney, Daniel P, Rappocciolo, Giovanna, Penugonda, Sudhir, Bream, Jay H, Martínez-Maza, Otoniel, and Jacobson, Lisa P

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Immunology, HIV/AIDS, Heart Disease, Infectious Diseases, Cardiovascular, Clinical Research, Cancer, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Inflammatory and immune system, Infection, Good Health and Well Being, Biomarkers, Cohort Studies, HIV Infections, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Inflammation, Longitudinal Studies, Male, statins, inflammation, immune activation, HIV, cytokine, Clinical Sciences, Virology, Clinical sciences
Abstract

Immune activation and inflammation are hallmarks of chronic HIV infection and are etiologically linked to major causes of morbidity and mortality among HIV-infected persons, including coronary artery disease and cancer. Systemic immune activation is dampened, but not resolved, with use of combination antiretroviral therapy (cART). Statins are cardioprotective drugs that also appear to have immunomodulatory and anti-inflammatory properties. We sought to understand the association between statin use, cART, and levels of circulating immune markers in a longitudinal cohort study. From 2004 to 2009, statin use was ascertained in male participants of the Multicenter AIDS Cohort Study (MACS) using interviewer-administered questionnaires. Twenty-four circulating markers of immune activation and inflammation were measured in archived serial samples from a subset of cohort members using multiplex assays. Propensity-adjusted generalized gamma models were used to compare biomarkers' distributions by statin use, and multivariable linear regression models were used to assess the effect of initiating statin on these biomarkers. Overall, 1,031 cART-exposed individuals with HIV infection were included in this study. Statin use was reported by 31.5% of cART-exposed participants. Compared to nonstatin users on cART, statin users on cART had lower levels of IP-10, IL-10, and IL-12p70, and the effect of statin use was decreased in participants using lipophilic statins (atorvastatin, simvastatin, fluvastatin, or lovastatin); these results were statistically significant (p

Published
2021

13. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study.

Author

Burn, Edward, You, Seng Chan, Sena, Anthony G, Kostka, Kristin, Abedtash, Hamed, Abrahão, Maria Tereza F, Alberga, Amanda, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Aragon, Maria, Areia, Carlos, Banda, Juan M, Cho, Jaehyeong, Culhane, Aedin C, Davydov, Alexander, DeFalco, Frank J, Duarte-Salles, Talita, DuVall, Scott, Falconer, Thomas, Fernandez-Bertolin, Sergio, Gao, Weihua, Golozar, Asieh, Hardin, Jill, Hripcsak, George, Huser, Vojtech, Jeon, Hokyun, Jing, Yonghua, Jung, Chi Young, Kaas-Hansen, Benjamin Skov, Kaduk, Denys, Kent, Seamus, Kim, Yeesuk, Kolovos, Spyros, Lane, Jennifer CE, Lee, Hyejin, Lynch, Kristine E, Makadia, Rupa, Matheny, Michael E, Mehta, Paras P, Morales, Daniel R, Natarajan, Karthik, Nyberg, Fredrik, Ostropolets, Anna, Park, Rae Woong, Park, Jimyung, Posada, Jose D, Prats-Uribe, Albert, Rao, Gowtham, Reich, Christian, Rho, Yeunsook, Rijnbeek, Peter, Schilling, Lisa M, Schuemie, Martijn, Shah, Nigam H, Shoaibi, Azza, Song, Seokyoung, Spotnitz, Matthew, Suchard, Marc A, Swerdel, Joel N, Vizcaya, David, Volpe, Salvatore, Wen, Haini, Williams, Andrew E, Yimer, Belay B, Zhang, Lin, Zhuk, Oleg, Prieto-Alhambra, Daniel, and Ryan, Patrick

Subjects
Humans, Pneumonia, Viral, Coronavirus Infections, Hospitalization, Prevalence, Cohort Studies, Age Factors, Comorbidity, Sex Factors, Adult, Aged, Aged, 80 and over, Middle Aged, United States, Spain, Female, Male, Influenza, Human, Young Adult, Republic of Korea, Pandemics, COVID-19, and over, Influenza, Human, Pneumonia, Viral
Abstract

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

Published
2020

14. The Impact of the COVID-19 Pandemic on Incidence and Short-Term Survival for Common Solid Tumours in the United Kingdom: A Cohort Analysis

Author

Barclay, Nicola, primary, Burkard, Theresa, additional, Burn, Edward, additional, Delmestri, Antonella, additional, Miquel Dominguez, Andrea, additional, Golozar, Asieh, additional, Guarner-Argente, Carlos, additional, Avilés-Jurado, Francesc, additional, Man, Wai Yi, additional, Roselló Serrano, Àlvar, additional, Rosen, Andreas, additional, Tan, Eng Hooi, additional, Tietzova, Ilona, additional, Prieto Alhambra, Daniel, additional, and Newby, Danielle, additional

Published
2024
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16. MP14-08 REAL-WORD CLINICAL CHARACTERIZATION OF METASTATIC HORMONE SENSITIVE PROSTATE CANCER: DATA FROM THE EUROPEAN NETWORK OF EXCELLENCE FOR BIG DATA IN PROSTATE CANCER (PIONEER)

Author

Nicoletti, Rossella, primary, Rivas, Juan Gomez, additional, Ibáñez, Laura, additional, Steinbeisserc, Carl, additional, de Meulder, Bertrand, additional, France, Lyon, additional, Golozar, Asieh, additional, Axelsson, Susan Evans, additional, Snijder, Robert, additional, Bjartell, Anders, additional, Cornford, Philip, additional, Van Hemelrijck, Mieke, additional, Beyer, Katharina, additional, Willemse, Peter-Paul, additional, Murtola, Teemu, additional, Robool, Monique J., additional, Sierra, Jesus Moreno, additional, Campi, Riccardo, additional, Gacci, Mauro, additional, Mottet, Nicolas, additional, Merseburger, Axel, additional, and Ndow, James, additional

Published
2024
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17. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Author

Rajwa, Pawel, primary, Borkowetz, Angelika, additional, Abbott, Thomas, additional, Alberti, Andrea, additional, Bjartell, Anders, additional, Brash, James T., additional, Campi, Riccardo, additional, Chilelli, Andrew, additional, Conover, Mitchell, additional, Constantinovici, Niculae, additional, Davies, Eleanor, additional, De Meulder, Bertrand, additional, Eid, Sherrine, additional, Gacci, Mauro, additional, Golozar, Asieh, additional, Hafeez, Haroon, additional, Haque, Samiul, additional, Hijazy, Ayman, additional, Hulsen, Tim, additional, Josefsson, Andreas, additional, Khalid, Sara, additional, Kolde, Raivo, additional, Kotik, Daniel, additional, Kurki, Samu, additional, Lambrecht, Mark, additional, Leung, Chi-Ho, additional, Moreno, Julia, additional, Nicoletti, Rossella, additional, Nieboer, Daan, additional, Oja, Marek, additional, Palanisamy, Soundarya, additional, Prinsen, Peter, additional, Reich, Christian, additional, Raffaele Resta, Giulio, additional, Ribal, Maria J., additional, Gómez Rivas, Juan, additional, Smith, Emma, additional, Snijder, Robert, additional, Steinbeisser, Carl, additional, Vandenberghe, Frederik, additional, Cornford, Philip, additional, Evans-Axelsson, Susan, additional, N'Dow, James, additional, and Willemse, Peter-Paul M., additional

Published
2024
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18. MP14-09 DEVELOPMENT OF A PREDICTION MODEL OF SURVIVAL AMONGST PATIENTS WITH METASTATIC HORMONE SENSITIVE PROSTATE CANCER (MHSPC) USING BIG DATA: INTERIM RESULTS FROM THE EUROPEAN NETWORK OF EXCELLENCE FOR BIG DATA IN PROSTATE CANCER (PIONEER)

Author

Nicoletti, Rossella, primary, Rivas, Juan Gomez, additional, Ibáñez, Laura, additional, Steinbeisserc, Carl, additional, de Meulder, Bertrand, additional, Golozar, Asieh, additional, Axelsson, Susan Evans, additional, Snijder, Robert, additional, Bjartell, Anders, additional, Cornford, Philip, additional, Van Hemelrijck, Mieke, additional, Beyer, Katharina, additional, Willemse, Peter-Paul, additional, Murtola, Teemu, additional, Robool, Monique J., additional, Sierra, Jesus Moreno, additional, Campi, Riccardo, additional, Gacci, Mauro, additional, Mottet, Nicolas, additional, Merseburger, Axel, additional, Ndow, James, additional, and Nicoletti, Rossella, additional

Published
2024
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19. Research protocol for an observational health data analysis to assess the applicability of randomized controlled trials focusing on newly diagnosed metastatic prostate cancer using real-world data: PIONEER IMI’s “big data for better outcomes” program

Author

Gandaglia, Giorgio, primary, Pellegrino, Francesco, additional, De Meulder, Bertrand, additional, Hijazy, Ayman, additional, Abbott, Thomas, additional, Golozar, Asieh, additional, Nicoletti, Rossella, additional, Gomez-Rivas, Juan, additional, Steinbeisser, Carl, additional, Evans-Axelsson, Susan, additional, Briganti, Alberto, additional, and N’Dow, James, additional

Published
2024
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20. Similar risk of kidney failure among patients with blinding diseases who receive ranibizumab, aflibercept, and bevacizumab: an OHDSI Network Study

Author

Cai, Cindy X., primary, Nishimura, Akihiko, additional, Bowring, Mary G., additional, Westlund, Erik, additional, Tran, Diep, additional, Ng, Jia H., additional, Nagy, Paul, additional, Cook, Michael, additional, McLeggon, Jody-Ann, additional, DuVall, Scott L., additional, Matheny, Michael E., additional, Golozar, Asieh, additional, Ostropolets, Anna, additional, Minty, Evan, additional, Desai, Priya, additional, Bu, Fan, additional, Toy, Brian, additional, Hribar, Michelle, additional, Falconer, Thomas, additional, Zhang, Linying, additional, Lawrence-Archer, Laurence, additional, Boland, Michael V., additional, Goetz, Kerry, additional, Hall, Nathan, additional, Shoaibi, Azza, additional, Reps, Jenna, additional, Sena, Anthony G., additional, Blacketer, Clair, additional, Swerdel, Joel, additional, Jhaveri, Kenar .D., additional, Lee, Edward, additional, Gilbert, Zachary, additional, Zeger, Scott L., additional, Crews, Deidra C., additional, Suchard, Marc A., additional, Hripcsak, George, additional, and Ryan, Patrick B., additional

Published
2024
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21. Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom

Author

Recalde, Martina, Roel, Elena, Pistillo, Andrea, Sena, Anthony G., Prats-Uribe, Albert, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alshammari, Thamir M., Alser, Osaid, Areia, Carlos, Burn, Edward, Casajust, Paula, Dawoud, Dalia, DuVall, Scott L., Falconer, Thomas, Fernández-Bertolín, Sergio, Golozar, Asieh, Gong, Mengchun, Lai, Lana Yin Hui, Lane, Jennifer C. E., Lynch, Kristine E., Matheny, Michael E., Mehta, Paras P., Morales, Daniel R., Natarjan, Karthik, Nyberg, Fredrik, Posada, Jose D., Reich, Christian G., Rijnbeek, Peter R., Schilling, Lisa M., Shah, Karishma, Shah, Nigam H., Subbian, Vignesh, Zhang, Lin, Zhu, Hong, Ryan, Patrick, Prieto-Alhambra, Daniel, Kostka, Kristin, and Duarte-Salles, Talita

Published
2021
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22. Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management:A PIONEER Analysis Based on Big Data

Author

Gandaglia, Giorgio, Pellegrino, Francesco, Golozar, Asieh, De Meulder, Bertrand, Abbott, Thomas, Achtman, Ariel, Imran Omar, Muhammad, Alshammari, Thamir, Areia, Carlos, Asiimwe, Alex, Beyer, Katharina, Bjartell, Anders, Campi, Riccardo, Cornford, Philip, Falconer, Thomas, Feng, Qi, Gong, Mengchun, Herrera, Ronald, Hughes, Nigel, Hulsen, Tim, Kinnaird, Adam, Lai, Lana Y.H., Maresca, Gianluca, Mottet, Nicolas, Oja, Marek, Prinsen, Peter, Reich, Christian, Remmers, Sebastiaan, Roobol, Monique J., Sakalis, Vasileios, Seager, Sarah, Smith, Emma J., Snijder, Robert, Steinbeisser, Carl, Thurin, Nicolas H., Hijazy, Ayman, van Bochove, Kees, Van den Bergh, Roderick C.N., Van Hemelrijck, Mieke, Willemse, Peter Paul, Williams, Andrew E., Zounemat Kermani, Nazanin, Evans-Axelsson, Susan, Briganti, Alberto, N'Dow, James, Gandaglia, Giorgio, Pellegrino, Francesco, Golozar, Asieh, De Meulder, Bertrand, Abbott, Thomas, Achtman, Ariel, Imran Omar, Muhammad, Alshammari, Thamir, Areia, Carlos, Asiimwe, Alex, Beyer, Katharina, Bjartell, Anders, Campi, Riccardo, Cornford, Philip, Falconer, Thomas, Feng, Qi, Gong, Mengchun, Herrera, Ronald, Hughes, Nigel, Hulsen, Tim, Kinnaird, Adam, Lai, Lana Y.H., Maresca, Gianluca, Mottet, Nicolas, Oja, Marek, Prinsen, Peter, Reich, Christian, Remmers, Sebastiaan, Roobol, Monique J., Sakalis, Vasileios, Seager, Sarah, Smith, Emma J., Snijder, Robert, Steinbeisser, Carl, Thurin, Nicolas H., Hijazy, Ayman, van Bochove, Kees, Van den Bergh, Roderick C.N., Van Hemelrijck, Mieke, Willemse, Peter Paul, Williams, Andrew E., Zounemat Kermani, Nazanin, Evans-Axelsson, Susan, Briganti, Alberto, and N'Dow, James

Abstract

BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics.OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data.DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146).OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data.RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent.CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and

Published
2024

23. Research protocol for an observational health data analysis on the adverse events of systemic treatment in patients with metastatic hormone-sensitive prostate cancer : big data analytics using the PIONEER platform

Author

Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter-Paul M., Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter-Paul M.

Abstract

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Published
2024
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24. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Author

MS Urologische Oncologie, Cancer, Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T, Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J, Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter-Paul M, MS Urologische Oncologie, Cancer, Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T, Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J, Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter-Paul M

Published
2024

25. Predictive Models for Assessing Patients’ Response to Treatment in Metastatic Prostate Cancer:A Systematic Review

Author

Lawlor, Ailbhe, Lin, Carol, Gómez Rivas, Juan, Ibáñez, Laura, Abad López, Pablo, Willemse, Peter Paul, Imran Omar, Muhammad, Remmers, Sebastiaan, Cornford, Philip, Rajwa, Pawel, Nicoletti, Rossella, Gandaglia, Giorgio, Yuen-Chun Teoh, Jeremy, Moreno Sierra, Jesús, Golozar, Asieh, Bjartell, Anders, Evans-Axelsson, Susan, N'Dow, James, Zong, Jihong, Ribal, Maria J., Roobol, Monique J., Van Hemelrijck, Mieke, Beyer, Katharina, Lawlor, Ailbhe, Lin, Carol, Gómez Rivas, Juan, Ibáñez, Laura, Abad López, Pablo, Willemse, Peter Paul, Imran Omar, Muhammad, Remmers, Sebastiaan, Cornford, Philip, Rajwa, Pawel, Nicoletti, Rossella, Gandaglia, Giorgio, Yuen-Chun Teoh, Jeremy, Moreno Sierra, Jesús, Golozar, Asieh, Bjartell, Anders, Evans-Axelsson, Susan, N'Dow, James, Zong, Jihong, Ribal, Maria J., Roobol, Monique J., Van Hemelrijck, Mieke, and Beyer, Katharina

Abstract

Background and objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients’ response to treatment. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.

Published
2024

26. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer:Big Data Analytics Using the PIONEER Platform

Author

Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter Paul M., Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter Paul M.

Abstract

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Published
2024

29. Extending the OMOP Common Data Model and Standardized Vocabularies to Support Observational Cancer Research

Author

Belenkaya, Rimma, Gurley, Michael J., Golozar, Asieh, Dymshyts, Dmitry, Miller, Robert T., Williams, Andrew E., Ratwani, Shilpa, Siapos, Anastasios, Korsik, Vladislav, Warner, Jeremy, Campbell, W. Scott, Rivera, Donna, Banokina, Tatiana, Modina, Elizaveta, Bethusamy, Shantha, Stewart, Henry Morgan, Patel, Meera, Chen, Ruijun, Falconer, Thomas, Park, Rae Woong, You, Seng Chan, Jeon, Hokyun, Shin, Soe Jeong, and Reich, Christian

Published
2021
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30. Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data

Author

Gandaglia, Giorgio, primary, Pellegrino, Francesco, additional, Golozar, Asieh, additional, De Meulder, Bertrand, additional, Abbott, Thomas, additional, Achtman, Ariel, additional, Imran Omar, Muhammad, additional, Alshammari, Thamir, additional, Areia, Carlos, additional, Asiimwe, Alex, additional, Beyer, Katharina, additional, Bjartell, Anders, additional, Campi, Riccardo, additional, Cornford, Philip, additional, Falconer, Thomas, additional, Feng, Qi, additional, Gong, Mengchun, additional, Herrera, Ronald, additional, Hughes, Nigel, additional, Hulsen, Tim, additional, Kinnaird, Adam, additional, Lai, Lana Y.H., additional, Maresca, Gianluca, additional, Mottet, Nicolas, additional, Oja, Marek, additional, Prinsen, Peter, additional, Reich, Christian, additional, Remmers, Sebastiaan, additional, Roobol, Monique J., additional, Sakalis, Vasileios, additional, Seager, Sarah, additional, Smith, Emma J., additional, Snijder, Robert, additional, Steinbeisser, Carl, additional, Thurin, Nicolas H., additional, Hijazy, Ayman, additional, van Bochove, Kees, additional, Van den Bergh, Roderick C.N., additional, Van Hemelrijck, Mieke, additional, Willemse, Peter-Paul, additional, Williams, Andrew E., additional, Zounemat Kermani, Nazanin, additional, Evans-Axelsson, Susan, additional, Briganti, Alberto, additional, and N'Dow, James, additional

Published
2023
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31. Research protocol to identify progression and death amongst patients with metastatic hormone-sensitive prostate cancer treated with available treatments: PIONEER IMI's "big data for better outcomes" program.

Author

Gomez Rivas, Juan, Nicoletti, Rossella, Ibáñez, Laura, Steinbeisser, Carl, de Meulder, Bertrand, Golozar, Asieh, Evans Axelsson, Susan, Snijder, Robert, Bjartell, Anders, Cornford, Philip, Van Hemelrijck, Mieke, Beyer, Katharina, Willemse, Peter-Paul, Murtola, Teemu, Roobol, Monique J., Moreno-Sierra, Jesús, Campi, Riccardo, Gacci, Mauro, Mottet, Nicolas, and Merseburger, Axel

Published
2023
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32. Research protocol to identify progression and death amongst patients with metastatic hormone-sensitive prostate cancer treated with available treatments: PIONEER IMI's 'big data for better outcomes' program

Author

MS Urologische Oncologie, Cancer, Gomez Rivas, Juan, Nicoletti, Rossella, Ibáñez, Laura, Steinbeisser, Carl, de Meulder, Bertrand, Golozar, Asieh, Axelsson, Susan Evans, Snijder, Robert, Bjartell, Anders, Cornford, Philip, Van Hemelrijck, Mieke, Beyer, Katharina, Willemse, Peter-Paul, Murtola, Teemu, Roobol, Monique J, Moreno-Sierra, Jesús, Campi, Riccardo, Gacci, Mauro, Mottet, Nicolas, Merseburger, Axel, Ndow, James, MS Urologische Oncologie, Cancer, Gomez Rivas, Juan, Nicoletti, Rossella, Ibáñez, Laura, Steinbeisser, Carl, de Meulder, Bertrand, Golozar, Asieh, Axelsson, Susan Evans, Snijder, Robert, Bjartell, Anders, Cornford, Philip, Van Hemelrijck, Mieke, Beyer, Katharina, Willemse, Peter-Paul, Murtola, Teemu, Roobol, Monique J, Moreno-Sierra, Jesús, Campi, Riccardo, Gacci, Mauro, Mottet, Nicolas, Merseburger, Axel, and Ndow, James

Published
2023

33. Food preparation methods, drinking water source, and esophageal squamous cell carcinoma in the high-risk area of Golestan, Northeast Iran

Author

Golozar, Asieh, Etemadi, Arash, Kamangar, Farin, Malekshah, Akbar Fazeltabar, Islami, Farhad, Nasrollahzadeh, Dariush, Abedi-Ardekani, Behnoosh, Khoshnia, Masoud, Pourshams, Akram, Semnani, Shahriar, Marjani, Haji Amin, Shakeri, Ramin, Sotoudeh, Masoud, Brennan, Paul, Taylor, Philip, Boffetta, Paolo, Abnet, Christian, Dawsey, Sanford, and Malekzadeh, Reza

Published
2016

38. Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Author

Kostka,Kristin, Duarte-Salles,Talita, Prats-Uribe,Albert, Sena,Anthony G, Pistillo,Andrea, Khalid,Sara, Lai,Lana YH, Golozar,Asieh, Alshammari,Thamir M, Dawoud,Dalia M, Nyberg,Fredrik, Wilcox,Adam B, Andryc,Alan, Williams,Andrew, Ostropolets,Anna, Areia,Carlos, Jung,Chi Young, Harle,Christopher A, Reich,Christian G, Blacketer,Clair, Morales,Daniel R, Dorr,David A, Burn,Edward, Roel,Elena, Tan,Eng Hooi, Minty,Evan, DeFalco,Frank, de Maeztu,Gabriel, Lipori,Gigi, Alghoul,Heba, Zhu,Hong, Thomas,Jason A, Bian,Jiang, Park,Jimyung, Martínez Roldán,Jordi, Posada,Jose D, Banda,Juan M, Horcajada,Juan P, Kohler,Julianna, Shah,Karishma, Natarajan,Karthik, Lynch,Kristine E, Liu,Li, Schilling,Lisa M, Recalde,Martina, Spotnitz,Matthew, Gong,Mengchun, Matheny,Michael E, Valveny,Neus, Weiskopf,Nicole G, Shah,Nigam, Alser,Osaid, Casajust,Paula, Park,Rae Woong, Schuff,Robert, Seager,Sarah, DuVall,Scott L, You,Seng Chan, Song,Seokyoung, Fernández-Bertolín,Sergio, Fortin,Stephen, Magoc,Tanja, Falconer,Thomas, Subbian,Vignesh, Huser,Vojtech, Ahmed,Waheed-Ul-Rahman, Carter,William, Guan,Yin, Galvan,Yankuic, He,Xing, Rijnbeek,Peter R, Hripcsak,George, Ryan,Patrick B, Suchard,Marc A, Prieto-Alhambra,Daniel, Kostka,Kristin, Duarte-Salles,Talita, Prats-Uribe,Albert, Sena,Anthony G, Pistillo,Andrea, Khalid,Sara, Lai,Lana YH, Golozar,Asieh, Alshammari,Thamir M, Dawoud,Dalia M, Nyberg,Fredrik, Wilcox,Adam B, Andryc,Alan, Williams,Andrew, Ostropolets,Anna, Areia,Carlos, Jung,Chi Young, Harle,Christopher A, Reich,Christian G, Blacketer,Clair, Morales,Daniel R, Dorr,David A, Burn,Edward, Roel,Elena, Tan,Eng Hooi, Minty,Evan, DeFalco,Frank, de Maeztu,Gabriel, Lipori,Gigi, Alghoul,Heba, Zhu,Hong, Thomas,Jason A, Bian,Jiang, Park,Jimyung, Martínez Roldán,Jordi, Posada,Jose D, Banda,Juan M, Horcajada,Juan P, Kohler,Julianna, Shah,Karishma, Natarajan,Karthik, Lynch,Kristine E, Liu,Li, Schilling,Lisa M, Recalde,Martina, Spotnitz,Matthew, Gong,Mengchun, Matheny,Michael E, Valveny,Neus, Weiskopf,Nicole G, Shah,Nigam, Alser,Osaid, Casajust,Paula, Park,Rae Woong, Schuff,Robert, Seager,Sarah, DuVall,Scott L, You,Seng Chan, Song,Seokyoung, Fernández-Bertolín,Sergio, Fortin,Stephen, Magoc,Tanja, Falconer,Thomas, Subbian,Vignesh, Huser,Vojtech, Ahmed,Waheed-Ul-Rahman, Carter,William, Guan,Yin, Galvan,Yankuic, He,Xing, Rijnbeek,Peter R, Hripcsak,George, Ryan,Patrick B, Suchard,Marc A, and Prieto-Alhambra,Daniel

Abstract

Kristin Kostka,1,2 Talita Duarte-Salles,3 Albert Prats-Uribe,4 Anthony G Sena,5,6 Andrea Pistillo,3 Sara Khalid,4 Lana YH Lai,7 Asieh Golozar,8,9 Thamir M Alshammari,10 Dalia M Dawoud,11 Fredrik Nyberg,12 Adam B Wilcox,13,14 Alan Andryc,5 Andrew Williams,15 Anna Ostropolets,16 Carlos Areia,17 Chi Young Jung,18 Christopher A Harle,19 Christian G Reich,1,2 Clair Blacketer,5,6 Daniel R Morales,20 David A Dorr,21 Edward Burn,3,4 Elena Roel,3,22 Eng Hooi Tan,4 Evan Minty,23 Frank DeFalco,5 Gabriel de Maeztu,24 Gigi Lipori,19 Hiba Alghoul,25 Hong Zhu,26 Jason A Thomas,13 Jiang Bian,19 Jimyung Park,27 Jordi Martínez Roldán,28 Jose D Posada,29 Juan M Banda,30 Juan P Horcajada,31 Julianna Kohler,32 Karishma Shah,33 Karthik Natarajan,16,34 Kristine E Lynch,35,36 Li Liu,37 Lisa M Schilling,38 Martina Recalde,3,22 Matthew Spotnitz,14 Mengchun Gong,39 Michael E Matheny,40,41 Neus Valveny,42 Nicole G Weiskopf,21 Nigam Shah,29 Osaid Alser,43 Paula Casajust,42 Rae Woong Park,27,44 Robert Schuff,21 Sarah Seager,1 Scott L DuVall,35,36 Seng Chan You,45 Seokyoung Song,46 Sergio Fernández-Bertolín,3 Stephen Fortin,5 Tanja Magoc,19 Thomas Falconer,16 Vignesh Subbian,47 Vojtech Huser,48 Waheed-Ul-Rahman Ahmed,33,49 William Carter,38 Yin Guan,50 Yankuic Galvan,19 Xing He,19 Peter R Rijnbeek,6 George Hripcsak,16,34 Patrick B Ryan,5,16 Marc A Suchard,51 Daniel Prieto-Alhambra4 1IQVIA, Cambridge, MA, USA; 2OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA; 3Fundació Institut Universitari per a la recerca a l’Atenció Primà ria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 4Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK; 5Janssen Research & Development, Titusville, NJ, USA; 6Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands; 7School of Medical Sciences, University of Manchester, Manchester, UK; 8Regeneron Pharmaceuticals, Tarrytown, NY, USA; 9Department of Epidemiolo

Published
2022

39. Unraveling COVID-19:A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Author

Kostka, Kristin, Duarte-Salles, Talita, Prats-Uribe, Albert, Sena, Anthony G., Pistillo, Andrea, Khalid, Sara, Lai, Lana Y.H., Golozar, Asieh, Alshammari, Thamir M., Dawoud, Dalia M., Nyberg, Fredrik, Wilcox, Adam B., Andryc, Alan, Williams, Andrew, Ostropolets, Anna, Areia, Carlos, Jung, Chi Young, Harle, Christopher A., Reich, Christian G., Blacketer, Clair, Morales, Daniel R., Dorr, David A., Burn, Edward, Roel, Elena, Tan, Eng Hooi, Minty, Evan, De Falco, Frank, De Maeztu, Gabriel, Lipori, Gigi, Alghoul, Hiba, Zhu, Hong, Thomas, Jason A., Bian, Jiang, Park, Jimyung, Roldán, Jordi Martínez, Posada, Jose D., Banda, Juan M., Horcajada, Juan P., Kohler, Julianna, Shah, Karishma, Natarajan, Karthik, Lynch, Kristine E., Liu, Li, Schilling, Lisa M., Recalde, Martina, Spotnitz, Matthew, Gong, Mengchun, Matheny, Michael E., Valveny, Neus, Weiskopf, Nicole G., Shah, Nigam, Alser, Osaid, Casajust, Paula, Park, Rae Woong, Schuff, Robert, Seager, Sarah, Du Vall, Scott L., You, Seng Chan, Song, Seokyoung, Fernández-Bertolín, Sergio, Fortin, Stephen, Magoc, Tanja, Falconer, Thomas, Subbian, Vignesh, Huser, Vojtech, Ahmed, Waheed Ul Rahman, Carter, William, Guan, Yin, Galvan, Yankuic, He, Xing, Rijnbeek, Peter R., Hripcsak, George, Ryan, Patrick B., Suchard, Marc A., Prieto-Alhambra, Daniel, Kostka, Kristin, Duarte-Salles, Talita, Prats-Uribe, Albert, Sena, Anthony G., Pistillo, Andrea, Khalid, Sara, Lai, Lana Y.H., Golozar, Asieh, Alshammari, Thamir M., Dawoud, Dalia M., Nyberg, Fredrik, Wilcox, Adam B., Andryc, Alan, Williams, Andrew, Ostropolets, Anna, Areia, Carlos, Jung, Chi Young, Harle, Christopher A., Reich, Christian G., Blacketer, Clair, Morales, Daniel R., Dorr, David A., Burn, Edward, Roel, Elena, Tan, Eng Hooi, Minty, Evan, De Falco, Frank, De Maeztu, Gabriel, Lipori, Gigi, Alghoul, Hiba, Zhu, Hong, Thomas, Jason A., Bian, Jiang, Park, Jimyung, Roldán, Jordi Martínez, Posada, Jose D., Banda, Juan M., Horcajada, Juan P., Kohler, Julianna, Shah, Karishma, Natarajan, Karthik, Lynch, Kristine E., Liu, Li, Schilling, Lisa M., Recalde, Martina, Spotnitz, Matthew, Gong, Mengchun, Matheny, Michael E., Valveny, Neus, Weiskopf, Nicole G., Shah, Nigam, Alser, Osaid, Casajust, Paula, Park, Rae Woong, Schuff, Robert, Seager, Sarah, Du Vall, Scott L., You, Seng Chan, Song, Seokyoung, Fernández-Bertolín, Sergio, Fortin, Stephen, Magoc, Tanja, Falconer, Thomas, Subbian, Vignesh, Huser, Vojtech, Ahmed, Waheed Ul Rahman, Carter, William, Guan, Yin, Galvan, Yankuic, He, Xing, Rijnbeek, Peter R., Hripcsak, George, Ryan, Patrick B., Suchard, Marc A., and Prieto-Alhambra, Daniel

Abstract

Purpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three nonmutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: More women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwi

Published
2022

40. Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Author

Kostka, Kristin, primary, Duarte-Salles, Talita, additional, Prats-Uribe, Albert, additional, Sena, Anthony G, additional, Pistillo, Andrea, additional, Khalid, Sara, additional, Lai, Lana YH, additional, Golozar, Asieh, additional, Alshammari, Thamir M, additional, Dawoud, Dalia M, additional, Nyberg, Fredrik, additional, Wilcox, Adam B, additional, Andryc, Alan, additional, Williams, Andrew, additional, Ostropolets, Anna, additional, Areia, Carlos, additional, Jung, Chi Young, additional, Harle, Christopher A, additional, Reich, Christian G, additional, Blacketer, Clair, additional, Morales, Daniel R, additional, Dorr, David A, additional, Burn, Edward, additional, Roel, Elena, additional, Tan, Eng Hooi, additional, Minty, Evan, additional, DeFalco, Frank, additional, de Maeztu, Gabriel, additional, Lipori, Gigi, additional, Alghoul, Heba, additional, Zhu, Hong, additional, Thomas, Jason A, additional, Bian, Jiang, additional, Park, Jimyung, additional, Martínez Roldán, Jordi, additional, Posada, Jose D, additional, Banda, Juan M, additional, Horcajada, Juan P, additional, Kohler, Julianna, additional, Shah, Karishma, additional, Natarajan, Karthik, additional, Lynch, Kristine E, additional, Liu, Li, additional, Schilling, Lisa M, additional, Recalde, Martina, additional, Spotnitz, Matthew, additional, Gong, Mengchun, additional, Matheny, Michael E, additional, Valveny, Neus, additional, Weiskopf, Nicole G, additional, Shah, Nigam, additional, Alser, Osaid, additional, Casajust, Paula, additional, Park, Rae Woong, additional, Schuff, Robert, additional, Seager, Sarah, additional, DuVall, Scott L, additional, You, Seng Chan, additional, Song, Seokyoung, additional, Fernández-Bertolín, Sergio, additional, Fortin, Stephen, additional, Magoc, Tanja, additional, Falconer, Thomas, additional, Subbian, Vignesh, additional, Huser, Vojtech, additional, Ahmed, Waheed-Ul-Rahman, additional, Carter, William, additional, Guan, Yin, additional, Galvan, Yankuic, additional, He, Xing, additional, Rijnbeek, Peter R, additional, Hripcsak, George, additional, Ryan, Patrick B, additional, Suchard, Marc A, additional, and Prieto-Alhambra, Daniel, additional

Published
2022
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41. Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe

Author

Morales, Daniel R., primary, Ostropolets, Anna, additional, Lai, Lana, additional, Sena, Anthony, additional, Duvall, Scott, additional, Suchard, Marc, additional, Verhamme, Katia, additional, Rjinbeek, Peter, additional, Posada, Joe, additional, Ahmed, Waheed, additional, Alshammary, Thamer, additional, Alghoul, Heba, additional, Alser, Osaid, additional, Areia, Carlos, additional, Blacketer, Clair, additional, Burn, Edward, additional, Casajust, Paula, additional, You, Seng Chan, additional, Dawoud, Dalia, additional, Golozar, Asieh, additional, Gong, Menchung, additional, Jonnagaddala, Jitendra, additional, Lynch, Kristine, additional, Matheny, Michael, additional, Minty, Evan, additional, Nyberg, Fredrik, additional, Uribe, Albert, additional, Recalde, Martina, additional, Reich, Christian, additional, Scheumie, Martijn, additional, Shah, Karishma, additional, Shah, Nigam, additional, Schilling, Lisa, additional, Vizcaya, David, additional, Zhang, Lin, additional, Hripcsak, George, additional, Ryan, Patrick, additional, Prieto-Alhambra, Daniel, additional, Durate-Salles, Talita, additional, and Kostka, Kristin, additional

Published
2022
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43. Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe.

Author

Morales, Daniel R., Ostropolets, Anna, Lai, Lana, Sena, Anthony, Duvall, Scott, Suchard, Marc, Verhamme, Katia, Rjinbeek, Peter, Posada, Joe, Ahmed, Waheed, Alshammary, Thamer, Alghoul, Heba, Alser, Osaid, Areia, Carlos, Blacketer, Clair, Burn, Edward, Casajust, Paula, You, Seng Chan, Dawoud, Dalia, and Golozar, Asieh

Subjects
COVID-19, ASTHMATICS, ADULT respiratory distress syndrome, COUGH
Abstract

Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma. Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients ('diagnosed' and 'hospitalized') based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions. Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6–8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7–6.8) to 18.5% (95% CI 18.2–18.8) in the diagnosed cohort and 5.2% (95% CI 4.0–6.8) to 20.5% (95% CI 18.6–22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8–2.4) to 16.9% (95% CI 13.8–20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15–30% of hospitalized COVID-19 asthma patients. Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients. KEY MESSAGES Asthma prevalence in COVID-19 patients varied internationally (5.2–20.5%).The prevalence of asthma exacerbation at presentation with COVID-19 in diagnosed and hospitalized patients was low.Comorbidities were common in COVID-19 patients with asthma. Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Thirty-Day Outcomes of Children and Adolescents With COVID-19: An International Experience

Author

Duarte-Salles, Talita, primary, Vizcaya, David, additional, Pistillo, Andrea, additional, Casajust, Paula, additional, Sena, Anthony G., additional, Lai, Lana Yin Hui, additional, Prats-Uribe, Albert, additional, Ahmed, Waheed-Ul-Rahman, additional, Alshammari, Thamir M., additional, Alghoul, Heba, additional, Alser, Osaid, additional, Burn, Edward, additional, You, Seng Chan, additional, Areia, Carlos, additional, Blacketer, Clair, additional, DuVall, Scott, additional, Falconer, Thomas, additional, Fernandez-Bertolin, Sergio, additional, Fortin, Stephen, additional, Golozar, Asieh, additional, Gong, Mengchun, additional, Tan, Eng Hooi, additional, Huser, Vojtech, additional, Iveli, Pablo, additional, Morales, Daniel R., additional, Nyberg, Fredrik, additional, Posada, Jose D., additional, Recalde, Martina, additional, Roel, Elena, additional, Schilling, Lisa M., additional, Shah, Nigam H., additional, Shah, Karishma, additional, Suchard, Marc A., additional, Zhang, Lin, additional, Zhang, Ying, additional, Williams, Andrew E., additional, Reich, Christian G., additional, Hripcsak, George, additional, Rijnbeek, Peter, additional, Ryan, Patrick, additional, Kostka, Kristin, additional, and Prieto-Alhambra, Daniel, additional

Published
2021
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46. Epidemiological and clinical characteristics of cancer patients with COVID-19: A systematic review and meta-analysis of global data

Author

Kong, Xiangyi, primary, Qi, Yihang, additional, Huang, Junjie, additional, Zhao, Yang, additional, Zhan, Yongle, additional, Qin, Xuzhen, additional, Qi, Zhihong, additional, Atanda, Adejare (Jay), additional, Zhang, Lei, additional, Wang, Jing, additional, Fang, Yi, additional, Jia, Peng, additional, Golozar, Asieh, additional, Zhang, Lin, additional, and Jiang, Yu, additional

Published
2021
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47. Characteristics and Outcomes of Over 300,000 Patients with COVID-19 and History of Cancer in the United States and Spain.

Author

Roel, Elena, Roel, Elena, Pistillo, Andrea, Recalde, Martina, Sena, Anthony G, Fernández-Bertolín, Sergio, Aragón, Maria, Puente, Diana, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Areia, Carlos, Blacketer, Clair, Carter, William, Casajust, Paula, Culhane, Aedin C, Dawoud, Dalia, DeFalco, Frank, DuVall, Scott L, Falconer, Thomas, Golozar, Asieh, Gong, Mengchun, Hester, Laura, Hripcsak, George, Tan, Eng Hooi, Jeon, Hokyun, Jonnagaddala, Jitendra, Lai, Lana YH, Lynch, Kristine E, Matheny, Michael E, Morales, Daniel R, Natarajan, Karthik, Nyberg, Fredrik, Ostropolets, Anna, Posada, José D, Prats-Uribe, Albert, Reich, Christian G, Rivera, Donna R, Schilling, Lisa M, Soerjomataram, Isabelle, Shah, Karishma, Shah, Nigam H, Shen, Yang, Spotniz, Matthew, Subbian, Vignesh, Suchard, Marc A, Trama, Annalisa, Zhang, Lin, Zhang, Ying, Ryan, Patrick B, Prieto-Alhambra, Daniel, Kostka, Kristin, Duarte-Salles, Talita, Roel, Elena, Roel, Elena, Pistillo, Andrea, Recalde, Martina, Sena, Anthony G, Fernández-Bertolín, Sergio, Aragón, Maria, Puente, Diana, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Areia, Carlos, Blacketer, Clair, Carter, William, Casajust, Paula, Culhane, Aedin C, Dawoud, Dalia, DeFalco, Frank, DuVall, Scott L, Falconer, Thomas, Golozar, Asieh, Gong, Mengchun, Hester, Laura, Hripcsak, George, Tan, Eng Hooi, Jeon, Hokyun, Jonnagaddala, Jitendra, Lai, Lana YH, Lynch, Kristine E, Matheny, Michael E, Morales, Daniel R, Natarajan, Karthik, Nyberg, Fredrik, Ostropolets, Anna, Posada, José D, Prats-Uribe, Albert, Reich, Christian G, Rivera, Donna R, Schilling, Lisa M, Soerjomataram, Isabelle, Shah, Karishma, Shah, Nigam H, Shen, Yang, Spotniz, Matthew, Subbian, Vignesh, Suchard, Marc A, Trama, Annalisa, Zhang, Lin, Zhang, Ying, Ryan, Patrick B, Prieto-Alhambra, Daniel, Kostka, Kristin, and Duarte-Salles, Talita

Abstract

BackgroundWe described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza.MethodsWe conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes.ResultsWe included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events.ConclusionsPatients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent.ImpactThis study provides epidemiologic characteristics that can inform clinical care and etiologic studies.

Published
2021

48. Use of repurposed and adjuvant drugs in hospital patients with covid-19:Multinational network cohort study

Author

Prats-Uribe, Albert, Sena, Anthony G., Lai, Lana Yin Hui, Ahmed, Waheed Ul Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M., Areia, Carlos, Carter, William, Casajust, Paula, Dawoud, Dalia, Golozar, Asieh, Jonnagaddala, Jitendra, Mehta, Paras P., Gong, Mengchun, Morales, Daniel R., Nyberg, Fredrik, Posada, Jose D., Recalde, Martina, Roel, Elena, Shah, Karishma, Shah, Nigam H., Schilling, Lisa M., Subbian, Vignesh, Vizcaya, David, Zhang, Lin, Zhang, Ying, Zhu, Hong, Liu, Li, Cho, Jaehyeong, Lynch, Kristine E., Matheny, Michael E., You, Seng Chan, Rijnbeek, Peter R., Hripcsak, George, Lane, Jennifer C.E., Burn, Edward, Reich, Christian, Suchard, Marc A., Duarte-Salles, Talita, Kostka, Kristin, Ryan, Patrick B., Prieto-Alhambra, Daniel, Prats-Uribe, Albert, Sena, Anthony G., Lai, Lana Yin Hui, Ahmed, Waheed Ul Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M., Areia, Carlos, Carter, William, Casajust, Paula, Dawoud, Dalia, Golozar, Asieh, Jonnagaddala, Jitendra, Mehta, Paras P., Gong, Mengchun, Morales, Daniel R., Nyberg, Fredrik, Posada, Jose D., Recalde, Martina, Roel, Elena, Shah, Karishma, Shah, Nigam H., Schilling, Lisa M., Subbian, Vignesh, Vizcaya, David, Zhang, Lin, Zhang, Ying, Zhu, Hong, Liu, Li, Cho, Jaehyeong, Lynch, Kristine E., Matheny, Michael E., You, Seng Chan, Rijnbeek, Peter R., Hripcsak, George, Lane, Jennifer C.E., Burn, Edward, Reich, Christian, Suchard, Marc A., Duarte-Salles, Talita, Kostka, Kristin, Ryan, Patrick B., and Prieto-Alhambra, Daniel

Abstract

Objective To investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents. Design Multinational network cohort study. Setting Hospital electronic health records from the United States, Spain, and China, and nationwide claims data from South Korea. Participants 303 264 patients admitted to hospital with covid-19 from January 2020 to December 2020. Main outcome measures Prescriptions or dispensations of any drug on or 30 days after the date of hospital admission for covid-19. Results Of the 303 264 patients included, 290 131 were from the US, 7599 from South Korea, 5230 from Spain, and 304 from China. 3455 drugs were identified. Common repurposed drugs were hydroxychloroquine (used in from <5 (<2%) patients in China to 2165 (85.1%) in Spain), azithromycin (from 15 (4.9%) in China to 1473 (57.9%) in Spain), combined lopinavir and ritonavir (from 156 (<2%) in the VA-OMOP US to 2,652 (34.9%) in South Korea and 1285 (50.5%) in Spain), and umifenovir (0% in the US, South Korea, and Spain and 238 (78.3%) in China). Use of adjunctive drugs varied greatly, with the five most used treatments being enoxaparin, fluoroquinolones, ceftriaxone, vitamin D, and corticosteroids. Hydroxychloroquine use increased rapidly from March to April 2020 but declined steeply in May to June and remained low for the rest of the year. The use of dexamethasone and corticosteroids increased steadily during 2020. Conclusions Multiple drugs were used in the first few months of the covid-19 pandemic, with substantial geographical and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed drugs. Antithrombotics, antibiotics, H2 receptor antagonists, and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of covid-19.

Published
2021

49. Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension:A multinational cohort study

Author

Reyes, Carlen, Pistillo, Andrea, Fernández-Bertolín, Sergio, Recalde, Martina, Roel, Elena, Puente, Diana, Sena, Anthony G., Blacketer, Clair, Lai, Lana, Alshammari, Thamir M., Ahmed, Waheed Ui Rahman, Alser, Osaid, Alghoul, Heba, Areia, Carlos, Dawoud, Dalia, Prats-Uribe, Albert, Valveny, Neus, De Maeztu, Gabriel, Sorlí Redó, Luisa, Martinez Roldan, Jordi, Lopez Montesinos, Inmaculada, Schilling, Lisa M., Golozar, Asieh, Reich, Christian, Posada, Jose D., Shah, Nigam, You, Seng Chan, Lynch, Kristine E., Duvall, Scott L., Matheny, Michael E., Nyberg, Fredrik, Ostropolets, Anna, Hripcsak, George, Rijnbeek, Peter R., Suchard, Marc A., Ryan, Patrick, Kostka, Kristin, Duarte-Salles, Talita, Reyes, Carlen, Pistillo, Andrea, Fernández-Bertolín, Sergio, Recalde, Martina, Roel, Elena, Puente, Diana, Sena, Anthony G., Blacketer, Clair, Lai, Lana, Alshammari, Thamir M., Ahmed, Waheed Ui Rahman, Alser, Osaid, Alghoul, Heba, Areia, Carlos, Dawoud, Dalia, Prats-Uribe, Albert, Valveny, Neus, De Maeztu, Gabriel, Sorlí Redó, Luisa, Martinez Roldan, Jordi, Lopez Montesinos, Inmaculada, Schilling, Lisa M., Golozar, Asieh, Reich, Christian, Posada, Jose D., Shah, Nigam, You, Seng Chan, Lynch, Kristine E., Duvall, Scott L., Matheny, Michael E., Nyberg, Fredrik, Ostropolets, Anna, Hripcsak, George, Rijnbeek, Peter R., Suchard, Marc A., Ryan, Patrick, Kostka, Kristin, and Duarte-Salles, Talita

Abstract

Objective To characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients. Design and setting This is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020. Participants Two non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days. Outcomes Demographics, comorbidities and 30-day outcomes (hospitalisation and death for the diagnosed' cohort and adverse events and death for the hospitalised' cohort) were reported. Results We identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypert

Published
2021

50. Thirty-day outcomes of children and adolescents with COVID-19:An international experience

Author

Duarte-Salles, Talita, Vizcaya, David, Pistillo, Andrea, Casajust, Paula, Sena, Anthony G., Hui Lai, Lana Yin, Prats-Uribe, Albert, Ahmed, Waheed Ul Rahman, Alshammari, Thamir M., Alghoul, Heba, Alser, Osaid, Burn, Edward, You, Seng Chan, Areia, Carlos, Blacketer, Clair, DuVall, Scott, Falconer, Thomas, Fernandez-Bertolin, Sergio, Fortin, Stephen, Golozar, Asieh, Gong, Mengchun, Tan, Eng Hooi, Huser, Vojtech, Iveli, Pablo, Morales, Daniel R., Nyberg, Fredrik, Posada, Jose D., Recalde, Martina, Roel, Elena, Schilling, Lisa M., Shah, Nigam H., Shah, Karishma, Suchard, Marc A., Zhang, Lin, Zhang, Ying, Williams, Andrew E., Reich, Christian G., Hripcsak, George, Rijnbeek, Peter, Ryan, Patrick, Kostka, Kristin, Prieto-Alhambra, Daniel, Duarte-Salles, Talita, Vizcaya, David, Pistillo, Andrea, Casajust, Paula, Sena, Anthony G., Hui Lai, Lana Yin, Prats-Uribe, Albert, Ahmed, Waheed Ul Rahman, Alshammari, Thamir M., Alghoul, Heba, Alser, Osaid, Burn, Edward, You, Seng Chan, Areia, Carlos, Blacketer, Clair, DuVall, Scott, Falconer, Thomas, Fernandez-Bertolin, Sergio, Fortin, Stephen, Golozar, Asieh, Gong, Mengchun, Tan, Eng Hooi, Huser, Vojtech, Iveli, Pablo, Morales, Daniel R., Nyberg, Fredrik, Posada, Jose D., Recalde, Martina, Roel, Elena, Schilling, Lisa M., Shah, Nigam H., Shah, Karishma, Suchard, Marc A., Zhang, Lin, Zhang, Ying, Williams, Andrew E., Reich, Christian G., Hripcsak, George, Rijnbeek, Peter, Ryan, Patrick, Kostka, Kristin, and Prieto-Alhambra, Daniel

Abstract

OBJECTIVES: To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children and adolescents diagnosed or hospitalized with coronavirus disease 2019 (COVID-19) and to compare them in secondary analyses with patients diagnosed with previous seasonal influenza in 2017–2018. METHODS: International network cohort using real-world data from European primary care records (France, Germany, and Spain), South Korean claims and US claims, and hospital databases. We included children and adolescents diagnosed and/or hospitalized with COVID-19 at age <18 between January and June 2020. We described baseline demographics, comorbidities, symptoms, 30-day in-hospital treatments, and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome, multisystem inflammatory syndrome in children, and death. RESULTS: A total of 242 158 children and adolescents diagnosed and 9769 hospitalized with COVID-19 and 2 084 180 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were more common among those hospitalized with versus diagnosed with COVID-19. Dyspnea, bronchiolitis, anosmia, and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital prevalent treatments for COVID-19 included repurposed medications (<10%) and adjunctive therapies: systemic corticosteroids (6.8%–7.6%), famotidine (9.0%–28.1%), and antithrombotics such as aspirin (2.0%–21.4%), heparin (2.2%–18.1%), and enoxaparin (2.8%–14.8%). Hospitalization was observed in 0.3% to 1.3% of the cohort diagnosed with COVID-19, with undetectable (n < 5 per database) 30-day fatality. Thirty-day outcomes including pneumonia and hypoxemia were more frequent in COVID-19 than influenza. CONCLUSIONS: Despite negligible fatality, complications including hospitalization, hypoxemia, and pneumonia were more frequent in children and adolescents with COVID-19 than with inf

Published
2021

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