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STREAMLINE: AN AUTOMATED MACHINE LEARNING PIPELINE FOR BIOMEDICINE APPLIED TO EXAMINE THE UTILITY OF PHOTOGRAPHY-BASED PHENOTYPES FOR OSA PREDICTION ACROSS INTERNATIONAL SLEEP CENTERS

arXiv

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arXiv 2023年

作者： Urbanowicz, Ryan J. Bandhey, Harsh Keenan, Brendan T. Maislin, Greg Hwang, Sy Mowery, Danielle L. Lynch, Shannon M. Mazzotti, Diego R. Han, Fang Li, Qing Yun Penzel, Thomas Tufik, Sergio Bittencourt, Lia Gislason, Thorarinn de Chazal, Philip Singh, Bhajan McArdle, Nigel Chen, Ning-Hung Pack, Allan Schwab, Richard J. Cistulli, Peter A. Magalang, Ulysses J. Department of Computational Biomedicine Cedars Sinai Medical Center Los AngelesCA United States Division of Sleep Medicine Department of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Biomedical Informatics University of Pennsylvania PhiladelphiaPA United States Department of Biostatistics Epidemiology and Informatics University of Pennsylvania PhiladelphiaPA United States Cancer Prevention and Control Program Fox Chase Cancer Center PhiladelphiaPA United States Division of Medical Informatics Department of Internal Medicine University of Kansas LawrenceKS United States Division of Pulmonary Critical Care and Sleep Medicine Department of Internal Medicine University of Kansas LawrenceKS United States Division of Sleep Medicine Peking University People’s Hospital Beijing China Department of Respiratory and Critical Care Medicine Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Interdisciplinary Center of Sleep Medicine Charite University Hospital Berlin Germany Department of Psychobiology Federal University of Sao Paulo Sao Paulo Brazil Department of Sleep Medicine Landspitali University Hospital Reykjavik Iceland University of Iceland Faculty of Medicine Reykjavik Iceland Charles Perkins Center Faculty of Engineering University of Sydney Sydney Australia Department of Pulmonary Physiology and Sleep Medicine Sir Charles Gairdner Hospital Nedlands Australia University of Western Australia Crawley Australia Department of Pulmonary and Critical Care Medicine Sleep Center Linkou Chang Gung Memorial Hospital Taoyuan Taiwan Charles Perkins Centre Faculty of Medicine and Health University of Sydney Royal North Shore Hospital Sydney Australia Division of Pulmonary Critical Care and Sleep Medicine Department of Medicine Ohio State University Wexner Medical Center ColumbusOH United States 700 N. San Vicente Blvd. Pacific Design Center Suite G541E Los AngelesCA90069 United States

Objective: While machine learning (ML) includes a valuable array of tools for analyzing biomedical data with multivariate and complex underlying associations, significant time and expertise is required to assemble effective, rigorous, comparable, reproducible, and unbiased pipelines. Automated ML (AutoML) tools seek to facilitate ML application by automating a subset of analysis pipeline elements. In this study we develop and validate a Simple, Transparent, End-to-end Automated Machine Learning Pipeline (STREAMLINE) and apply it to investigate the added utility of photography-based phenotypes for predicting obstructive sleep apnea (OSA);a common and underdiagnosed condition associated with a variety of health, economic, and safety consequences. Methods: STREAMLINE is designed to tackle biomedical binary classification tasks while (1) avoiding common mistakes, (2) accommodating complex associations and common data challenges, and (3) allowing scalability, reproducibility, and model interpretation. It automates the majority of established, generalizable, and reliably automatable aspects of an ML analysis pipeline while incorporating cutting edge algorithms and providing opportunities for human-in-the-loop customization. We present a broadly refactored and extended release of STREAMLINE, validating and benchmarking performance across simulated and real-world datasets. Then we applied STREAMLINE to evaluate the utility of demographics (DEM), self-reported comorbidities (DX), symptoms (SYM), and photography-based craniofacial (CF) and intraoral (IO) anatomy measures in predicting ‘any OSA’ or ‘moderate/severe OSA’ using 3,111 participants from Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Results: Benchmarking analyses validated the efficacy of STREAMLINE across data simulations with increasingly complex patterns of association including epistatic interactions and genetic heterogeneity. OSA analyses identified a significant increase in ROC-AUC when adding CF t

关键词： Machine learning

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Highly processed foods intake is positively associated with pro-inflammatory potential of diet: cross-sectional analysis from the Moli-sani Study

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Nutrition, Metabolism and Cardiovascular Diseases 2021年第11期31卷 3253-3253页

作者： C. Mignogna S. Costanzo E. Ruggiero N. Shivappa J.R. Hebert S. Esposito A. Di Castelnuovo M. Persichillo C. Cerletti M.B. Donati G. De Gaetano L. Iacoviello M. Bonaccio Dep. Medicine and Surgery Research Center in Epidemiology and Preventive Medicine EPIMED University of Insubria Varese Italy Dep. Epidemiology and Prevention IRCCS NEUROMED Pozzilli Italy Cancer Prevention and Control Program Dep. Epidemiology and Biostatistics Arnold School of Public Health University of South Carolina Columbia US Dep. Nutrition Connecting Health Innovations LLC Columbia US Mediterranea Cardiocentro Napoli Italy

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Randomized trial of a community-based, culturally tailored intervention: High engagement among Latina breast cancer survivors

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cancer 2025年第11期131卷 e35842页

作者： Katarina E AuBuchon Claudia J Campos Galván Ysabel Duron Ivis Sampayo Migdalia Torres Alejandra Hurtado-de-Mendoza Charlene Kuo Christina Rush Maria Gloria Elliott Jennie Santiago Olympia Cepeda Laura A Logie Astrid Jimenez George Luta Kristi D Graves Cancer Prevention and Control Program Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington District of Columbia USA. Community Outreach and Engagement George Washington University Washington District of Columbia USA. Latino Cancer Institute San Jose California USA. LatinaSHARE New York New York USA. Red Door Community (formerly Gilda's Club New York City) New York New York USA. Department of Behavioral and Community Health School of Public Health University of Maryland Baltimore Maryland USA. Department of Psychiatry Massachusetts General Hospital Center for Health Outcomes and Interdisciplinary Research Harvard University Boston Massachusetts USA. Nueva Vida Inc Alexandria Virginia USA. Department of Biostatistics Bioinformatics and Biomathematics Georgetown University Washington District of Columbia USA.

BACKGROUND:A preliminary randomized controlled trial was conducted to evaluate the impact of a culturally tailored, group-based intervention for Latina breast cancer survivors (BCSs) and their caregivers on survivors' quality of life (QOL) compared to usual care services provided by community-based organizations. METHODS:This study randomized 136 Latina BCSs and 136 caregivers in Washington, DC; New York, New York; and San Jose, California to an eight-session culturally tailored coping and communication intervention (n = 70 dyads) or usual care support services via community-based organizations (n = 66 dyads). QOL domains (anxiety, depression, fatigue, physical functioning, and social functioning) were measured at baseline, immediately post-intervention, and 6 months post-intervention. RESULTS:Among the 70 dyads in the intervention, 71.4% (n = 50) attended five or more of the eight sessions, which demonstrated high engagement; 82% of participants were retained at 6 months. Results indicated clinically significant improvements in Latina BCSs' reports of anxiety and fatigue at 6 months postintervention compared to BCSs in usual care; however, after adjustment for multiple comparisons, results were not statistically significant. CONCLUSIONS:A culturally tailored, group-based intervention for Latina BCSs and their caregivers led to clinically relevant but not statistically significant improvements in survivors' anxiety and fatigue compared to usual services provided by community-based organizations. Interventions conducted in partnership with community-based organizations yield high engagement and retention; these types of collaborative approaches to psychosocial services have the potential to positively affect Latina BCSs' QOL.

关键词： Latina breast cancer caregiving community‐based research intervention survivorship

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Authors' Response

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Journal of the American College of Radiology : JACR 2022年第3期19卷 404-405页

作者： Erin A Hirsch Anna E Barón Betsy Risendal Jamie L Studts Melissa L New Stephen P Malkoski Division of Medical Oncology School of Medicine University of Colorado Anschutz Medical Campus Aurora Colorado. Electronic address: Erin.Hirsch@cuanschutz.edu. Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus Aurora Colorado. Department of Community and Behavioral Health Colorado School of Public Health University of Colorado Anschutz Medical Campus Aurora Colorado. Division of Medical Oncology and Cancer Prevention and Control Program University of Colorado Anschutz Medical Campus Aurora Colorado. Pulmonary Section Rocky Mountain Regional VA Medical Center Aurora Colorado and Division of Pulmonary Sciences and Critical Care Medicine University of Colorado Anschutz Medical Campus Aurora Colorado. Division of Pulmonary Sciences and Critical Care Medicine University of Colorado Anschutz Medical Campus Aurora Colorado Department of Medicine University of Washington WWAMI-Spokane Spokane Washington and Sound Critical Care Sacred Heart Medical Center Spokane Washington.

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I’am hiQ – A Novel Accuracy Index for Imputed Genotypes

Research Square

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Research Square 2021年

作者： Rosenberger, Albert Tozzi, Viola Hung, Rayjean J. Christiani, David C. Caporaso, Neil E. Liu, Geoffrey Bojesen, Stig E. Le Marchand, Loic Albanes, Demetrios Aldrich, Melinda C. Tardon, Adonina Fernández-Tardón, Guillermo Rennert, Gad Field, John K. Davies, Mike Liloglou, Triantafillos Kiemeney, Lambertus A. Lazarus, Philip Haugen, Aage Zienolddiny, Shanbeh Lam, Stephen Schabath, Matthew B. Andrew, Angeline S. Duell, Eric J. Arnold, Susanne M. Brunnsstöm, Hans Melander, Olle Goodman, Gary E. Chen, Chu Doherty, Jennifer A. Teare, Marion Dawn Cox, Angela Woll, Penella J. Risch, Angela Muley, Thomas R. Johansson, Mikael Brennan, Paul Landi, Maria Teresa Shete, Sanjay S. Amos, Christopher I. Bickeböller, Heike Department of Genetic Epidemiology University Medical Center Georg-August-University Göttingen Göttingen Germany Lunenfeld-Tanenbaum Research Institute Sinai Health System University of Toronto TorontoON Canada Department of Environmental Health Harvard T.H. Chan School of Public Health Massachusetts General Hospital Harvard Medical School BostonMA United States Division of Cancer Epidemiology and Genetics National Cancer Institute US National Institutes of Health BethesdaMD United States Medical Oncology and Medical Biophysics Princess Margaret Cancer Centre TorontoON Canada Medicine and Epidemiology Dalla Lana School of Public Health University of Toronto TorontoON Canada Department of Clinical Biochemistry Herlev and Gentofte Hospital Copenhagen University Hospital Copenhagen Denmark Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Copenhagen General Population Study Herlev and Gentofte Hospital Copenhagen Denmark Epidemiology Program University of Hawaii Cancer Center HonoluluHI United States Department of Thoracic Surgery Division of Epidemiology Vanderbilt University Medical Center NashvilleTN United States University of Oviedo ISPA and CIBERESP Faculty of Medicine Oviedo Spain Clalit National Cancer Control Center at Carmel Medical Center Technion Faculty of Medicine Haifa Israel Roy Castle Lung Cancer Research Programme The University of Liverpool Department of Molecular and Clinical Cancer Medicine Liverpool United Kingdom Departments of Health Evidence and Urology Radboud University Medical Center Nijmegen Netherlands Department of Pharmaceutical Sciences College of Pharmacy Washington State University SpokaneWA United States National Institute of Occupational Health Oslo Norway British Columbia Cancer Agency VancouverBC Canada Department of Cancer Epidemiology H. Lee Moffitt Cancer Center and Research Institute TampaFL United States Department of Epidemiology Geisel School of Medicine Dartmou

Background: Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper we introduce I’am hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. I’am (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results: Applying both measures to a large case-control sample of the International Lung cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for I’am and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of I’am and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion: We recommend using I’am hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data. © 2021, CC BY.

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A Practice Change to Eliminate Prophylactic Antibiotics for Elective Percutaneous Nephrostomy Tube Exchanges in Low-Risk Outpatients: A Retrospective Review on Risk for Infection

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Journal of Radiology Nursing 2019年第4期38卷 241-249页

作者： Brick, Jamie Michele Dail, Robin B. Priode, Kimberly Wirth, Michael Yamada, Ricardo University of South Carolina College of Nursing Columbia SC United States Associate Dean for Faculty Affairs and Professor University of South Carolina College of Nursing Columbia SC United States Clinical Assistant Professor University of South Carolina College of Nursing Columbia SC United States Research Assistant Professor College of Nursing and Department of Epidemiology and Biostatistics Cancer Prevention and Control Program University of South Carolina Columbia SC United States Assistant Professor Vascular and Interventional Radiology Medical University of South Carolina Charleston SC United States

The purpose of this project was to determine if evidence-based practice change related to antibiotic administration criteria for outpatients receiving percutaneous nephrostomy tube exchanges implemented by a medical center's Vascular and Interventional Radiology department impacted hospital admission rates for infection in these patients. The 2017 practice change was based on 2010 guidelines from the Society of Interventional Radiology (SIR), stating that outpatients with a low risk of acquiring infection did not need to receive a perioperative antibiotic, as evidence has shown prophylactic therapy has no significant effect on infection rates for this population. Using a retrospective review design, 1 year of data before and after the practice change were collected and analyzed using the repeated measures generalized estimating equation (GEE) model with a binomial output by Liang & Zeger. Fisher's exact test was used to evaluate demographic variables by level of risk of infection. Data included 493 procedural events for 126 outpatients. The mean number of events per patient was 3.91 (SD: 4.15;median: 2;interquartile range: 3). Admission and infection criteria within thirty days of the event and infection risk factors were collected for each patient. Age, sex, and race were the variables that had a significant relationship with risk level of infection. Due to sample size, the GEE model could not be run using risk level (high/low) to predict admissions before or after the practice change. The relationship between the number of risk factors (0-5) and the odds of admission for infection was the same regardless of the practice change (before: odds ratio [OR] = 2.17, 95% confidence interval [CI] = 1.19-3.95;after: OR = 1.9, 95% CI = 1.12-3.22, p_interaction =. 67). For every increase in a patient's number of risk factors, the odds of developing an infection would be expected to increase by almost 90% (OR = 1.9, 95% CI = 1.27-2.84). Although it was not possible t

关键词： Antibiotic stewardship Infection Interventional radiology Percutaneous nephrostomy Practice change

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The effects of the Multicultural Healthy Diet on cognitive decline & Alzheimer's disease risk: A randomized controlled trial in middle-aged adults

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The American journal of clinical nutrition 2025年

作者： Yasmin Mossavar-Rahmani Noorie Hyun Jonathan G Hakun Mindy J Katz Jelena M Pavlovic Henrik Zetterberg Zheng Wang Jasper B Yang Judith Wylie-Rosett James R Hebert Martin J Sliwinski Pamela A Shaw Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Electronic address: yasmin.mossavar-rahmani@einsteinmed.edu. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA Department of Biostatistics University of Washington Seattle WA. Department of Neurology The Pennsylvania State University College of Medicine Hershey PA Department of Psychology The Pennsylvania State University University Park PA Department of Public Health Sciences The Pennsylvania State University College of Medicine Hershey PA Center for Healthy Aging The Pennsylvania State University University Park PA. Department of Neurology Albert Einstein College of Medicine Bronx NY. Department of Neurology Albert Einstein College of Medicine & Montefiore Medical Center Bronx NY. Institute of Neuroscience and Physiology Dept. of Psychiatry and Neurochemistry University of Gothenburg Mölndal Sweden Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London UK UK Dementia Research Institute at UCL London UK Hong Kong Center for Neurodegenerative Diseases InnoHK Hong Kong China Wisconsin Alzheimer's Disease Research Center University of Wisconsin School of Medicine and Public Health University of Wisconsin-Madison Madison WI. Division of Biostatistics Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA. Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Department of Epidemiology and Biostatistics and Cancer Prevention and Control Program Arnold School of Public Health University of South Carolina Columbia SC Depart

BACKGROUND:Anti-inflammatory dietary patterns are associated with slower cognitive decline in older adults; however, little is known about effects of an anti-inflammatory dietary pattern in middle-age. OBJECTIVES:To adapt an anti-inflammatory diet to a multicultural setting and assess its impact on cognitive decline and Alzheimer's Disease risk and related dementias in healthy middle-aged adults. METHODS:We performed a phase II pilot randomized clinical trial in adults (40-65 years old; n=290) in Bronx, New York. Participants were assigned to follow either the Multicultural Healthy Diet (MHD) an anti-inflammatory diet, or usual diet (Comparison). Diet was evaluated using National cancer Institute's Automated Self-Administered 24-hr food records. The primary cognitive outcome was assessed at 9 months following randomization using a global composite score derived from three ambulatory cognitive assessments of visuospatial memory (Grid Memory), processing speed (Symbol Search) and short-term associative memory binding (Color Shapes). Secondary outcomes included performance on individual tests and association of dietary components with cognitive performance. RESULTS:At 9 month follow-up the MHD arm had a lower Dietary Inflammatory Index (DII) score based on self-reported diet, with an adjusted MHD minus Comparison difference of -0.64 (95% CI: -1.02, -0.27) and -0.94 (95% CI: -1.34, -0.54) for the DII and energy-adjusted DII scores respectively, indicating intervention participants had adhered to an anti-inflammatory dietary pattern. Group session and telephone contact completion averaged 93% and 72% respectively for the MHD arm. No statistically significant difference between arms was found in the primary outcome- cognitive global score change- from baseline: -0.06 (95% CI: -0.15, 0.04), p=0.259. CONCLUSIONS:The MHD was feasible and acceptable in this multicultural US cohort. While the influence of MHD at 9 months was non-significant based on the composite cognitive sco

关键词： Alzheimer’s disease and related dementias Diet assessment ambulatory cognitive monitoring cognitive function dietary inflammatory index multicultural healthy diet randomized controlled clinical trial

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A Nomogram To Predict The Overall Survival Of Breast cancer Patients And Guide The Postoperative Adjuvant Chemotherapy In China

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cancer management and research 2019年 11卷 10029-10039页

作者： Xin Wang Ziwei Feng Yubei Huang Haixin Li Ping Cui Dezheng Wang Hongji Dai Fangfang Song Hong Zheng Peishan Wang Xuchen Cao Lin Gu Jin Zhang Fengju Song Kexin Chen Department of Epidemiology and Biostatistics National Clinical Research Center for Cancer，Key Laboratory of Cancer Prevention and Therapy Tianjin Medical University Cancer Institute and Hospital Tianjin 300060 People's Republic of China. Department of Cancer Biobank Tianjin Medical University Cancer Institute and Hospital Tianjin 300060 People's Republic of China. Center for Non-Communicable Disease Control and Prevention Tianjin Centers for Disease Control and Prevention Tianjin 300011 People's Republic of China. The First Department of Breast Cancer National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy Tianjin Medical University Cancer Institute and Hospital Tianjin 300060 People's Republic of China. The Second Department of Breast Cancer National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy Tianjin Medical University Cancer Institute and Hospital Tianjin 300060 People's Republic of China. The Third Department of Breast Cancer National Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy Tianjin Medical University Cancer Institute and Hospital Tianjin 300060 People's Republic of China.

PURPOSE:We aim to construct a nomogram to predict breast cancer survival and guide postoperative adjuvant chemotherapy in China. PATIENTS AND METHODS:A total of 5,504 breast cancer patients from the Tianjin Breast cancer Cases Cohort were included. Multivariable Cox regression was used to investigate the factors associated with overall survival (OS) and a nomogram was constructed based on these prognostic factors. The nomogram was internal and external validated and the performance was evaluated by area under the curve (AUC) and calibration curve. The partial score was also constructed and stratified them into low, moderate and high-risk subgroups for death according to the tripartite grouping method. Multivariate Cox regression analysis and the propensity score matching method were respectively used to test the association between adjuvant chemotherapy and OS in different risk subgroups. RESULTS:Age, diameter, histological differentiation, lymph node metastasis, estrogen, and progesterone receptor were incorporated into the nomogram and validation results showed this nomogram was well-calibrated to predict the 3-year [AUC =74.1%; 95% confidence interval (CI): 70.1-78.0%] and 5-year overall survival [AUC =72.3%; 95% CI: 69.6-75.1%]. Adjuvant chemotherapy was negatively associated with death in high risk subgroup [Hazard Ratio (HR) = 0.54; 95% CI: 0.37-0.77; <0.001]. However, no significant association were found in groups with low (HR=1.47; 95% CI: 0.52-4.19; =0.47) and moderate risk (HR=0.78; 95% CI: 0.42-1.48; =0.45). The 1:1 PSM generated 822 pairs of well-matched patients and Kaplan-Meier showed the high-risk patients could benefit from chemotherapy, whereas low risk and moderate risk subjects did not appear to benefit from chemotherapy. CONCLUSION:Not all of the breast cancer patients benefit equally from chemotherapy. The nomogram could be used to evaluate the overall survival of breast cancer patients and predict the magnitude of benefit and guide adjuvant ch

关键词： adjuvant chemotherapy breast cancer cohort study prognostic prediction

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The dietary inflammatory index in women diagnosed with breast cancer after 12 months of dietary. Treatment with a Mediterranean diet low in glycemic index: data from DEDICA randomized controlled trial

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Nutrition, Metabolism and Cardiovascular Diseases 2021年第11期31卷 3256-3256页

作者： S. Vitale V. Mattioli N. Shivappa J.R. Hebert E. Palumbo G. Porciello C. Montagnese I. Calabrese R. Pica M. Prete A. Luongo M. Grimaldi A. Crispo L. Falzone M. Libra J. Polesel D. Serraino L. Poletto L.S.A. Augustin National Cancer Institute Istituto Nazionale Tumori IRCCS “Fondazione Giovanni Pascale” Naples Italy National Cancer Institute Centro di Riferimento Oncologico (CRO) IRCCS Epidemiology Unit Aviano Italy Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics Arnold School of Public Health University of South Carolina Columbia SC USA Department of Nutrition Connecting Health Innovations LLC Columbia SC USA Department of Clinical Medicine and Surgery Federico II University Naples Italy Department of Biomedical and Biotechnological Sciences Oncologic Clinical and General Pathology Section University of Catania Italy

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Correction to: Healthy lifestyle index and risk of pancreatic cancer in the Women's Health Initiative

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cancer causes & control : CCC 2023年第12期34卷 1157页

作者： Rita Peila Mace Coday Tracy E Crane Nazmus Saquib Aladdin H Shadyab Fred K Tabung Xiaochen Zhang Jean Wactawski-Wende Thomas E Rohan Department of Epidemiology and Population Health Albert Einstein College of Medicine 1300 Morris Park Avenue Bronx NY 10461 USA. rita.peila@***. Department of Preventive Medicine College of Medicine University of Tennessee Health Science Center Memphis TN USA. Behavioral Measurement and Interventions Cancer Prevention and Control Program University of Arizona Tucson AZ USA. College of Medicine at Sulaiman Al Rajhi University Al Bukayriyah Saudi Arabia. Herbert Wertheim School of Public Health and Human Longevity Science University of California San Diego La Jolla CA USA. Internal Medicine Division of Medical Oncology The Ohio State University College of Medicine and Comprehensive Cancer Center Columbus OH USA. Division of Epidemiology College of Public Health Comprehensive Cancer Center Ohio State University Columbus OH USA. Department of Epidemiology and Environmental Health School of Public Health University of Buffalo Buffalo NY USA. Department of Epidemiology and Population Health Albert Einstein College of Medicine 1300 Morris Park Avenue Bronx NY 10461 USA. thomas.rohan@***.

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