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2. Dynamics of Long-Term Patient-Reported Quality of Life and Health Behaviors After Adjuvant Breast Cancer Chemotherapy

Author

Di Meglio, Antonio, Havas, Julie, Gbenou, Arnauld S, Martin, Elise, El-Mouhebb, Mayssam, Pistilli, Barbara, Menvielle, Gwenn, Dumas, Agnes, Everhard, Sibille, Martin, Anne-Laure, Cottu, Paul H, Lerebours, Florence, Coutant, Charles, Lesur, Anne, Tredan, Olivier, Soulie, Patrick, Vanlemmens, Laurence, Joly, Florence, Delaloge, Suzette, Ganz, Patricia A, André, Fabrice, Partridge, Ann H, Jones, Lee W, Michiels, Stefan, and Vaz-Luis, Ines

Subjects
Breast Cancer, Prevention, Clinical Research, Behavioral and Social Science, Cancer, Good Health and Well Being, Breast Neoplasms, Chemotherapy, Adjuvant, Female, Health Behavior, Humans, Patient Reported Outcome Measures, Quality of Life, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeWe aimed to characterize long-term quality of life (QOL) trajectories among patients with breast cancer treated with adjuvant chemotherapy and to identify related patterns of health behaviors.MethodsFemale stage I-III breast cancer patients receiving chemotherapy in CANTO (CANcer TOxicity; ClinicalTrials.gov identifier: NCT01993498) were included. Trajectories of QOL (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-C30 Summary Score) and associations with trajectory group membership were identified by iterative estimations of group-based trajectory models and multivariable multinomial logistic regression, respectively.ResultsFour trajectory groups were identified (N = 4,131): excellent (51.7%), very good (31.7%), deteriorating (10.0%), and poor (6.6%) QOL. The deteriorating trajectory group reported fairly good baseline QOL (mean [95% CI], 78.3/100 [76.2 to 80.5]), which significantly worsened at year-1 (58.1/100 [56.4 to 59.9]) and never recovered to pretreatment values through year-4 (61.1/100 [59.0 to 63.3]) postdiagnosis. Healthy behaviors were associated with better performing trajectory groups. Obesity (adjusted odds ratio [aOR] v lean, 1.51 [95% CI, 1.28 to 1.79]; P < .0001) and current smoking (aOR v never, 1.52 [95% CI, 1.27 to 1.82]; P < .0001) at diagnosis were associated with membership to the deteriorating group, which was also characterized by a higher prevalence of patients with excess body weight and insufficient physical activity through year-4 and by frequent exposure to tobacco smoking during chemotherapy. Additional factors associated with membership to the deteriorating group included younger age (aOR, 1-year decrement 1.01 [95% CI, 1.01 to 1.02]; P = .043), comorbidities (aOR v no, 1.22 [95% CI, 1.06 to 1.40]; P = .005), lower income (aOR v wealthier households, 1.21 [95% CI, 1.07 to 1.37]; P = .002), and endocrine therapy (aOR v no, 1.14 [95% CI, 1.01 to 1.30]; P = .047).ConclusionThis latent-class analysis identified some patients with upfront poor QOL and a high-risk cluster with severe, persistent postchemotherapy QOL deterioration. Screening relevant patient-level characteristics may inform tailored interventions to mitigate the detrimental impact of chemotherapy and preserve QOL, including early addressal of behavioral concerns and provision of healthy lifestyle support programs.

Published
2022

3. Long-Term Longitudinal Patterns of Patient-Reported Fatigue After Breast Cancer: A Group-Based Trajectory Analysis

Author

Vaz-Luis, Ines, Di Meglio, Antonio, Havas, Julie, El-Mouhebb, Mayssam, Lapidari, Pietro, Presti, Daniele, Soldato, Davide, Pistilli, Barbara, Dumas, Agnes, Menvielle, Gwenn, Charles, Cecile, Everhard, Sibille, Martin, Anne-Laure, Cottu, Paul H, Lerebours, Florence, Coutant, Charles, Dauchy, Sarah, Delaloge, Suzette, Lin, Nancy U, Ganz, Patricia A, Partridge, Ann H, André, Fabrice, and Michiels, Stefan

Subjects
Prevention, Clinical Research, Cancer, Breast Cancer, Rehabilitation, Breast Neoplasms, Fatigue, Female, Humans, Longitudinal Studies, Patient Reported Outcome Measures, Prospective Studies, Quality of Life, Survivors, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeFatigue is recognized as one of the most burdensome and long-lasting adverse effects of cancer and cancer treatment. We aimed to characterize long-term fatigue trajectories among breast cancer survivors.MethodsWe performed a detailed longitudinal analysis of fatigue using a large ongoing national prospective clinical study (CANcer TOxicity, ClinicalTrials.gov identifier: NCT01993498) of patients with stage I-III breast cancer treated from 2012 to 2015. Fatigue was assessed at diagnosis and year 1, 2, and 4 postdiagnosis. Baseline clinical, sociodemographic, behavioral, tumor-related, and treatment-related characteristics were available. Trajectories of fatigue and risk factors of trajectory-group membership were identified by iterative estimates of group-based trajectory models.ResultsThree trajectory groups were identified for severe global fatigue (n = 4,173). Twenty-one percent of patients were in the high-risk group, having risk estimates of severe global fatigue of 94.8% (95% CI, 86.6 to 100.0) at diagnosis and 64.6% (95% CI, 59.2 to 70.1) at year 4; 19% of patients clustered in the deteriorating group with risk estimates of severe global fatigue of 13.8% (95% CI, 6.7 to 20.9) at diagnosis and 64.5% (95% CI, 57.3 to 71.8) at year 4; 60% were in the low-risk group with risk estimates of 3.6% (95% CI, 2.5 to 4.7) at diagnosis and 9.6% (95% CI, 7.5 to 11.7) at year 4. The distinct dimensions of fatigue clustered in different trajectory groups than those identified by severe global fatigue, being differentially affected by sociodemographic, clinical, and treatment-related factors.ConclusionOur findings highlight the multidimensional nature of cancer-related fatigue and the complexity of its risk factors. This study helps to identify patients with increased risk of severe fatigue and to inform personalized interventions to ameliorate this problem.

Published
2022

4. Development and Validation of a Predictive Model of Severe Fatigue After Breast Cancer Diagnosis: Toward a Personalized Framework in Survivorship Care

Author

Di Meglio, Antonio, Havas, Julie, Soldato, Davide, Presti, Daniele, Martin, Elise, Pistilli, Barbara, Menvielle, Gwenn, Dumas, Agnes, Charles, Cecile, Everhard, Sibille, Martin, Anne-Laure, Coutant, Charles, Tarpin, Carole, Vanlemmens, Laurence, Levy, Christelle, Rigal, Olivier, Delaloge, Suzette, Lin, Nancy U, Ganz, Patricia A, Partridge, Ann H, André, Fabrice, Michiels, Stefan, and Vaz-Luis, Ines

Subjects
Behavioral and Social Science, Clinical Research, Breast Cancer, Cancer, Prevention, Good Health and Well Being, Breast Neoplasms, Cancer Survivors, Female, Humans, Quality of Life, Survivors, Survivorship, Clinical Sciences, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeFatigue is common and troublesome among breast cancer survivors; however, limited tools exist to predict its risk.Patients and methodsParticipants with stage I-III breast cancer were prospectively included from CANTO (ClinicalTrials.gov identifier: NCT01993498), collecting longitudinal data at diagnosis (before the initiation of any cancer treatment) and 1 (T1), 2 (T2), and 4 (T3) years after diagnosis. The main outcome was severe global fatigue at T2 (score ≥ 40/100, European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-C30). Analyses at T3 were exploratory. Secondary outcomes included physical, emotional, and cognitive fatigue (EORTC Quality of Life Questionnaire-FA12). Multivariable logistic regression models retained associations with severe fatigue by bootstrapped Augmented Backward Elimination. Validation methods included 10-fold internal cross-validation, overoptimism-corrected area under the receiver operating characteristic curves, and external validation.ResultsAmong 5,640, 5,000, and 3,400 patients at T1, T2, and T3, respectively, the prevalence of post-treatment severe global fatigue was 35.6%, 34.0%, and 31.5% in the development cohort. Retained risk factors for severe global fatigue at T2 were severe pretreatment fatigue (adjusted odds ratio v no 3.191 [95% CI, 2.704 to 3.767]); younger age (for 1-year decrement 1.015 [1.009 to 1.022]), higher body mass index (for unit increment 1.025 [1.012 to 1.038]), current smoking behavior (v never 1.552 [1.291 to 1.866]), worse anxiety (v noncase 1.265 [1.073 to 1.492]), insomnia (for unit increment 1.005 [1.003 to 1.007]), and pain at diagnosis (for unit increment 1.014 [1.010 to 1.017]), with an area under the receiver operating characteristic curve of 0.73 (95% CI, 0.72 to 0.75). Receipt of hormonal therapy was a risk factor for severe fatigue at T3 (v no 1.448 [1.165 to 1.799]). Dimension-specific risk factors included body mass index for physical fatigue and emotional distress for emotional and cognitive fatigue.ConclusionWe propose a predictive model to assess fatigue among breast cancer survivors, within a personalized survivorship care framework. This may help clinicians to provide early management interventions or to correct modifiable risk factors and offer more tailored monitoring and education to patients at risk of severe post-treatment fatigue.

Published
2022

5. Change in the value of work after breast cancer: evidence from a prospective cohort

Author

Caumette, Elsa, Di Meglio, Antonio, Vaz-Luis, Inès, Charles, Cécile, Havas, Julie, de Azua, Garazi Ruiz, Martin, Elise, Vanlemmens, Laurence, Delaloge, Suzette, Everhard, Sibille, Martin, Anne-Laure, Merimeche, Asma Dhaini, Rigal, Olivier, Coutant, Charles, Fournier, Marion, Jouannaud, Christelle, Soulie, Patrick, Cottu, Paul-Henri, Tredan, Olivier, Menvielle, Gwenn, and Dumas, Agnès

Published
2023
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6. Why do apprentices smoke much more than high school students? Understanding educational disparities in smoking with a Oaxaca-blinder decomposition analysis

Author

Chyderiotis, Sandra, Benmarhnia, Tarik, Spilka, Stanislas, Beck, François, Andler, Raphaël, Legleye, Stéphane, and Menvielle, Gwenn

Subjects
Public Health, Health Sciences, Pediatric, Tobacco, Tobacco Smoke and Health, Substance Misuse, Prevention, Cardiovascular, Stroke, Cancer, Good Health and Well Being, Adolescent, Adolescent Behavior, Cigarette Smoking, Cross-Sectional Studies, Educational Status, Female, France, Humans, Male, Socioeconomic Factors, Students, Adolescence, Education, Apprenticeship, Health disparities, Smoking, Decomposition analysis, Oaxaca-blinder, Public Health and Health Services, Epidemiology, Health services and systems, Public health
Abstract

BackgroundEducational disparities in daily smoking begin during adolescence and can lead to educational disparities in health among adults. In particular, vocational students including apprentices have higher daily smoking rates compared to non-vocational students. This study aimed to identify the determinants of the gap in daily smoking between French apprentices and high school students aged 17 in 2008 and in 2017.MethodsWe used data from a cross-sectional repeated survey representative of all French adolescents aged 17 in 2008 and 2017. We conducted a non-linear extension of the Oaxaca-Blinder decomposition technique and included the following variables: sociodemographic and familial characteristics, parental smoking, cannabis and alcohol use, suicidal attempt, grade repetition and money received.ResultsDaily smoking was about two times higher among French apprentices compared to high school students in 2008. This gap did not decrease between 2008 and 2017. Differences in measured characteristics between the two groups explained this gap partly, from 28.6 to 51.2%. Cannabis and alcohol use, money received and parental smoking contributed the most to the daily smoking gap.ConclusionsPrevention programs could target cannabis and alcohol use as well as parental smoking to help decrease educational disparities in smoking status among French adolescents.

Published
2020

7. Prediction of Breast Cancer Treatment-Induced Fatigue by Machine Learning Using Genome Wide Association Data

Author

Lee, Sangkyu, Deasy, Joseph O, Oh, Jung Hun, Di Meglio, Antonio, Dumas, Agnes, Menvielle, Gwenn, Charles, Cecile, Boyault, Sandrine, Rousseau, Marina, Besse, Celine, Thomas, Emilie, Boland, Anne, Cottu, Paul, Tredan, Olivier, Levy, Christelle, Martin, Anne-Laure, Everhard, Sibille, Ganz, Patricia A, Partridge, Ann, Michiels, Stefan, Deleuze, Jean-François, Andre, Fabrice, and Vaz-Luis, Ines

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Cancer, Genetics, Human Genome, Breast Cancer, Good Health and Well Being, Oncology and carcinogenesis
Abstract

BackgroundWe aimed at predicting fatigue after breast cancer treatment using machine learning on clinical covariates and germline genome-wide data.MethodsWe accessed germline genome-wide data of 2799 early-stage breast cancer patients from the Cancer Toxicity study (NCT01993498). The primary endpoint was defined as scoring zero at diagnosis and higher than quartile 3 at 1 year after primary treatment completion on European Organization for Research and Treatment of Cancer quality-of-life questionnaires for Overall Fatigue and on the multidimensional questionnaire for Physical, Emotional, and Cognitive fatigue. First, we tested univariate associations of each endpoint with clinical variables and genome-wide variants. Then, using preselected clinical (false discovery rate < 0.05) and genomic (P

Published
2020

9. Facing points of view: Representations on adjuvant endocrine therapy of premenopausal patients after breast cancer and their healthcare providers in France. The FOR-AD study

Author

Roche, Nicolas, Le Provost, Jean-Bernard, Borinelli-Franzoi, Maria-Alice, Boinon, Diane, Martin, Elise, Menvielle, Gwenn, Dumas, Agnès, Rivera, Sofia, Conversano, Angelica, Matias, Margarida, Viansone, Alessandro, Di Meglio, Antonio, Delaloge, Suzette, Vaz-Duarte-Luis, Ines-Maria, Pistilli, Barbara, and Fasse, Léonor

Published
2023
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10. Joint effects of intensity and duration of cigarette smoking on the risk of head and neck cancer: A bivariate spline model approach

Author

Di Credico, Gioia, Edefonti, Valeria, Polesel, Jerry, Pauli, Francesco, Torelli, Nicola, Serraino, Diego, Negri, Eva, Luce, Daniele, Stucker, Isabelle, Matsuo, Keitaro, Brennan, Paul, Vilensky, Marta, Fernandez, Leticia, Curado, Maria Paula, Menezes, Ana, Daudt, Alexander W, Koifman, Rosalina, Wunsch-Filho, Victor, Holcatova, Ivana, Ahrens, Wolfgang, Lagiou, Pagona, Simonato, Lorenzo, Richiardi, Lorenzo, Healy, Claire, Kjaerheim, Kristina, Conway, David I, Macfarlane, Tatiana V, Thomson, Peter, Agudo, Antonio, Znaor, Ariana, Rios, Leonardo F Boaventura, Toporcov, Tatiana N, Franceschi, Silvia, Herrero, Rolando, Muscat, Joshua, Olshan, Andrew F, Zevallos, Jose P, La Vecchia, Carlo, Winn, Deborah M, Sturgis, Erich M, Li, Guojun, Fabianova, Eleonora, Lissowska, Jolanda, Mates, Dana, Rudnai, Peter, Shangina, Oxana, Swiatkowska, Beata, Moysich, Kirsten, Zhang, Zuo-Feng, Morgenstern, Hal, Levi, Fabio, Smith, Elaine, Lazarus, Philip, Bosetti, Cristina, Garavello, Werner, Kelsey, Karl, McClean, Michael, Ramroth, Heribert, Chen, Chu, Schwartz, Stephen M, Vaughan, Thomas L, Zheng, Tongzhang, Menvielle, Gwenn, Boccia, Stefania, Cadoni, Gabriella, Hayes, Richard B, Purdue, Mark, Gillison, Maura, Schantz, Stimson, Yu, Guo-Pei, Brenner, Hermann, D'Souza, Gypsyamber, Gross, Neil D, Chuang, Shu-Chun, Boffetta, Paolo, Hashibe, Mia, Lee, Yuan-Chin Amy, and Dal Maso, Luigino

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Tobacco Smoke and Health, Substance Misuse, Tobacco, Dental/Oral and Craniofacial Disease, Rare Diseases, Cancer, 2.2 Factors relating to the physical environment, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Case-Control Studies, Cigarette Smoking, Female, Head and Neck Neoplasms, Humans, Male, Middle Aged, Risk Factors, Bivariate spline models, Cigarette smoking duration, Cigarette smoking intensity, Head and neck cancer, INHANCE, Laryngeal cancer, Oral cavity and pharyngeal cancers, Dentistry, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

ObjectivesThis study aimed at re-evaluating the strength and shape of the dose-response relationship between the combined (or joint) effect of intensity and duration of cigarette smoking and the risk of head and neck cancer (HNC). We explored this issue considering bivariate spline models, where smoking intensity and duration were treated as interacting continuous exposures.Materials and methodsWe pooled individual-level data from 33 case-control studies (18,260 HNC cases and 29,844 controls) participating in the International Head and Neck Cancer Epidemiology (INHANCE) consortium. In bivariate regression spline models, exposures to cigarette smoking intensity and duration (compared with never smokers) were modeled as a linear piecewise function within a logistic regression also including potential confounders. We jointly estimated the optimal knot locations and regression parameters within the Bayesian framework.ResultsFor oral-cavity/pharyngeal (OCP) cancers, an odds ratio (OR) >5 was reached after 30 years in current smokers of ∼20 or more cigarettes/day. Patterns of OCP cancer risk in current smokers differed across strata of alcohol intensity. For laryngeal cancer, ORs >20 were found for current smokers of ≥20 cigarettes/day for ≥30  years. In former smokers who quit ≥10  years ago, the ORs were approximately halved for OCP cancers, and ∼1/3 for laryngeal cancer, as compared to the same levels of intensity and duration in current smokers.ConclusionReferring to bivariate spline models, this study better quantified the joint effect of intensity and duration of cigarette smoking on HNC risk, further stressing the need of smoking cessation policies.

Published
2019

13. Determinants of use of oral complementary-alternative medicine among women with early breast cancer: a focus on cancer-related fatigue

Author

Lapidari, Pietro, Djehal, Nardjes, Havas, Julie, Gbenou, Arnauld, Martin, Elise, Charles, Cecile, Dauchy, Sarah, Pistilli, Barbara, Cadeau, Claire, Bertaut, Aurélie, Everhard, Sibille, Martin, Anne-Laure, Coutant, Charles, Cottu, Paul, Menvielle, Gwenn, Dumas, Agnes, Andre, Fabrice, Michiels, Stefan, Vaz-Luis, Ines, and Di Meglio, Antonio

Published
2021
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20. Magnitude and Temporal Variations of Socioeconomic Inequalities in the Quality of Life After Early Breast Cancer: Results From the Multicentric French CANTO Cohort.

Author

Sandoval, José Luis, Franzoi, Maria Alice, di Meglio, Antonio, Ferreira, Arlindo R., Viansone, Alessandro, André, Fabrice, Martin, Anne-Laure, Everhard, Sibille, Jouannaud, Christelle, Fournier, Marion, Rouanet, Philippe, Vanlemmens, Laurence, Dhaini-Merimeche, Asma, Sauterey, Baptiste, Cottu, Paul, Levy, Christelle, Stringhini, Silvia, Guessous, Idris, Vaz-Luis, Ines, and Menvielle, Gwenn

Published
2024
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21. Body weight and return to work among survivors of early-stage breast cancer

Author

Di Meglio, Antonio, Menvielle, Gwenn, Dumas, Agnes, Gbenou, Arnauld, Pinto, Sandrine, Bovagnet, Thomas, Martin, Elise, Ferreira, Arlindo R., Vanlemmens, Laurence, Arsene, Olivier, Ibrahim, Mahmoud, Wassermann, Johanna, Martin, Anne Laure, Lemonnier, Jerome, Del Mastro, Lucia, Jones, Lee W., Partridge, Ann H., Ligibel, Jennifer A., Andre, Fabrice, Michiels, Stefan, and Vaz Luis, Ines

Published
2020
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26. Estimating and explaining the effect of education and income on head and neck cancer risk: INHANCE consortium pooled analysis of 31 case‐control studies from 27 countries

Author

Conway, David I, Brenner, Darren R, McMahon, Alex D, Macpherson, Lorna MD, Agudo, Antonio, Ahrens, Wolfgang, Bosetti, Cristina, Brenner, Hermann, Castellsague, Xavier, Chen, Chu, Curado, Maria Paula, Curioni, Otávio A, Dal Maso, Luigino, Daudt, Alexander W, de Gois Filho, José F, D'Souza, Gypsyamber, Edefonti, Valeria, Fabianova, Eleonora, Fernandez, Leticia, Franceschi, Silvia, Gillison, Maura, Hayes, Richard B, Healy, Claire M, Herrero, Rolando, Holcatova, Ivana, Jayaprakash, Vijayvel, Kelsey, Karl, Kjaerheim, Kristina, Koifman, Sergio, La Vecchia, Carlo, Lagiou, Pagona, Lazarus, Philip, Levi, Fabio, Lissowska, Jolanta, Luce, Daniele, Macfarlane, Tatiana V, Mates, Dana, Matos, Elena, McClean, Michael, Menezes, Ana M, Menvielle, Gwenn, Merletti, Franco, Morgenstern, Hal, Moysich, Kirsten, Müller, Heiko, Muscat, Joshua, Olshan, Andrew F, Purdue, Mark P, Ramroth, Heribert, Richiardi, Lorenzo, Rudnai, Peter, Schantz, Stimson, Schwartz, Stephen M, Shangina, Oxana, Simonato, Lorenzo, Smith, Elaine, Stucker, Isabelle, Sturgis, Erich M, Szeszenia‐Dabrowska, Neonila, Talamini, Renato, Thomson, Peter, Vaughan, Thomas L, Wei, Qingyi, Winn, Deborah M, Wunsch‐Filho, Victor, Yu, Guo‐Pei, Zhang, Zuo‐Feng, Zheng, Tongzhang, Znaor, Ariana, Boffetta, Paolo, Chuang, Shu‐Chun, Ghodrat, Marianoosh, Lee, Yuan‐Chin Amy, Hashibe, Mia, and Brennan, Paul

Subjects
Behavioral and Social Science, Tobacco, Dental/Oral and Craniofacial Disease, Tobacco Smoke and Health, Cancer, Prevention, Substance Misuse, Basic Behavioral and Social Science, Reduced Inequalities, Good Health and Well Being, Alcohol Drinking, Case-Control Studies, Education, Female, Follow-Up Studies, Global Health, Head and Neck Neoplasms, Humans, Income, Male, Meta-Analysis as Topic, Middle Aged, Prognosis, Risk Factors, Smoking, Socioeconomic Factors, head and neck cancer, socioeconomic inequalities, epidemiology, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Low socioeconomic status has been reported to be associated with head and neck cancer risk. However, previous studies have been too small to examine the associations by cancer subsite, age, sex, global region and calendar time and to explain the association in terms of behavioral risk factors. Individual participant data of 23,964 cases with head and neck cancer and 31,954 controls from 31 studies in 27 countries pooled with random effects models. Overall, low education was associated with an increased risk of head and neck cancer (OR = 2.50; 95% CI = 2.02 - 3.09). Overall one-third of the increased risk was not explained by differences in the distribution of cigarette smoking and alcohol behaviors; and it remained elevated among never users of tobacco and nondrinkers (OR = 1.61; 95% CI = 1.13 - 2.31). More of the estimated education effect was not explained by cigarette smoking and alcohol behaviors: in women than in men, in older than younger groups, in the oropharynx than in other sites, in South/Central America than in Europe/North America and was strongest in countries with greater income inequality. Similar findings were observed for the estimated effect of low versus high household income. The lowest levels of income and educational attainment were associated with more than 2-fold increased risk of head and neck cancer, which is not entirely explained by differences in the distributions of behavioral risk factors for these cancers and which varies across cancer sites, sexes, countries and country income inequality levels.

Published
2015

31. Trends in health inequalities in 27 European countries

Author

Mackenbach, Johan P., Valverde, José Rubio, Artnik, Barbara, Bopp, Matthias, Brønnum-Hansen, Henrik, Deboosere, Patrick, Kalediene, Ramune, Kovács, Katalin, Leinsalu, Mall, Martikainen, Pekka, Menvielle, Gwenn, Regidor, Enrique, Rychtaříková, Jitka, Rodriguez-Sanz, Maica, Vineis, Paolo, White, Chris, Wojtyniak, Bogdan, Hu, Yannan, and Nusselder, Wilma J.

Published
2018

37. Sustainable return to work among breast cancer survivors

Author

Ruiz de Azua, Garazi, primary, Kousignian, Isabelle, additional, Vaz‐Luis, Ines, additional, Di Meglio, Antonio, additional, Caumette, Elsa, additional, Havas, Julie, additional, Martin, Elise, additional, Martin, Anne‐Laure, additional, Querel, Ophelie, additional, Vanlemmens, Laurence, additional, Pistilli, Barbara, additional, Coutant, Charles, additional, Cottu, Paul Henri, additional, Merimeche, Asma Dhaini, additional, Lerebours, Florence, additional, Tredan, Olivier, additional, Jouannaud, Christelle, additional, Levy, Christelle, additional, Dumas, Agnes, additional, and Menvielle, Gwenn, additional

Published
2023
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41. Laryngeal Cancer Risks in Workers Exposed to Lung Carcinogens: Exposure–Effect Analyses Using a Quantitative Job Exposure Matrix

Author

Hall, Amy L., Kromhout, Hans, Schüz, Joachim, Peters, Susan, Portengen, Lützen, Vermeulen, Roel, Agudo, Antonio, Ahrens, Wolfgang, Boffetta, Paolo, Brennan, Paul, Canova, Cristina, Conway, David I., Curado, Maria Paula, Daudt, Alexander W., Fernandez, Leticia, Hashibe, Mia, Healy, Claire M., Holcatova, Ivana, Kjaerheim, Kristina, Koifman, Rosalina, Lagiou, Pagona, Luce, Danièle, Macfarlane, Gary J., Menezes, Ana, Menvielle, Gwenn, Polesel, Jerry, Ramroth, Heribert, Richiardi, Lorenzo, Stücker, Isabelle, Thomson, Peter, Vilensky, Marta, Wunsch-Filho, Victor, Yuan-Chin, Amy Lee, Znaor, Ariana, Straif, Kurt, and Olsson, Ann

Published
2020
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42. Quantifying the mediating effects of smoking and occupational exposures in the relation between education and lung cancer: the ICARE study

Author

Menvielle, Gwenn, Franck, Jeanna-eve, Radoï, Loredana, Sanchez, Marie, Févotte, Joëlle, Guizard, Anne-Valérie, Stücker, Isabelle, Luce, Danièle, Woronoff, Anne-Sophie, Guizard, Anne-Valérie, Schmaus, Annie, Buemi, Antoine, Danzon, Arlette, Lapotre-Ledoux, Benedicte, Tretarre, Brigitte, Pilorget, Corinne, Luce, Danièle, Cyr, Diane, Marrer, Émilie, Lamkarkach, Farida, Guida, Florence, Molinie, Florence, Menvielle, Gwenn, Stücker, Isabelle, Févotte, Joëlle, Radoï, Loredana, Colonna, Marc, Sanchez, Marie, Carton, Matthieu, Velten, Michel, Raverdy, Nicole, Gaye, Oumar, Bercelli, Paolo, Delafosse, Patricia, Bara, Simona, Cénée, Sylvie, and ICARE study group

Published
2016
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48. Welding, a risk factor of lung cancer: the ICARE study

Author

Matrat, Mireille, Guida, Florence, Mattei, Francesca, Cénée, Sylvie, Cyr, Diane, Févotte, Joëlle, Sanchez, Marie, Menvielle, Gwenn, Radoï, Loredana, Schmaus, Annie, Woronoff, Anne-Sophie, Luce, Danièle, and Stücker, Isabelle

Published
2016

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