Literature DB >> 28069728

The Obesity Paradox in Survival after Cancer Diagnosis: Tools for Evaluation of Potential Bias.

Elizabeth Rose Mayeda1, M Maria Glymour2.   

Abstract

The effects of overweight or obesity on survival after cancer diagnosis are difficult to discern based on observational data because these associations reflect the net impact of both causal and spurious phenomena. We describe two sources of bias that might lead to underestimation of the effect of increased body weight on survival after cancer diagnosis: collider stratification bias and heterogeneity in disease bias. Given the mixed evidence on weight status, weight change, and postdiagnosis survival for cancer patients, systematic evaluation of alternative explanations is critical. The plausible magnitudes of these sources of bias can be quantified on the basis of expert knowledge about particular cancer types using simulation tools. We illustrate each type of bias, describe the assumptions researchers need make to evaluate the plausible magnitude of the bias, and provide a simple example of each bias using the setting of renal cancer. Findings from simulations, tailored to specific types of cancer, could help distinguish real from spurious effects of body weight on patient survival. Using these results can improve guidance for patients and providers about the relative importance of weight management after a diagnosis. Cancer Epidemiol Biomarkers Prev; 26(1); 17-20. ©2017 AACR. ©2017 American Association for Cancer Research.

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Year:  2017        PMID: 28069728      PMCID: PMC5858690          DOI: 10.1158/1055-9965.EPI-16-0559

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  16 in total

1.  Quantifying biases in causal models: classical confounding vs collider-stratification bias.

Authors:  Sander Greenland
Journal:  Epidemiology       Date:  2003-05       Impact factor: 4.822

2.  Commentary: selection bias as an explanation for the obesity paradox: just because it's possible doesn't mean it's plausible.

Authors:  M Maria Glymour; Eric Vittinghoff
Journal:  Epidemiology       Date:  2014-01       Impact factor: 4.822

3.  The Obesity Paradox in Cancer-Moving beyond BMI-Response.

Authors:  Shlomit Strulov Shachar; Grant R Williams
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-05-15       Impact factor: 4.254

4.  Implications of M bias in epidemiologic studies: a simulation study.

Authors:  Wei Liu; M Alan Brookhart; Sebastian Schneeweiss; Xiaojuan Mi; Soko Setoguchi
Journal:  Am J Epidemiol       Date:  2012-10-25       Impact factor: 4.897

5.  Obesity: The fat advantage.

Authors:  Sujata Gupta
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

6.  Body-mass index and mortality among 1.46 million white adults.

Authors:  Amy Berrington de Gonzalez; Patricia Hartge; James R Cerhan; Alan J Flint; Lindsay Hannan; Robert J MacInnis; Steven C Moore; Geoffrey S Tobias; Hoda Anton-Culver; Laura Beane Freeman; W Lawrence Beeson; Sandra L Clipp; Dallas R English; Aaron R Folsom; D Michal Freedman; Graham Giles; Niclas Hakansson; Katherine D Henderson; Judith Hoffman-Bolton; Jane A Hoppin; Karen L Koenig; I-Min Lee; Martha S Linet; Yikyung Park; Gaia Pocobelli; Arthur Schatzkin; Howard D Sesso; Elisabete Weiderpass; Bradley J Willcox; Alicja Wolk; Anne Zeleniuch-Jacquotte; Walter C Willett; Michael J Thun
Journal:  N Engl J Med       Date:  2010-12-02       Impact factor: 91.245

Review 7.  Should patients with chronic disease be told to gain weight? The obesity paradox and selection bias.

Authors:  Martín Lajous; Hailey R Banack; Jay S Kaufman; Miguel A Hernán
Journal:  Am J Med       Date:  2014-11-22       Impact factor: 4.965

8.  Prevalence of childhood and adult obesity in the United States, 2011-2012.

Authors:  Cynthia L Ogden; Margaret D Carroll; Brian K Kit; Katherine M Flegal
Journal:  JAMA       Date:  2014-02-26       Impact factor: 56.272

9.  Body size and renal cell cancer incidence in a large US cohort study.

Authors:  Kenneth F Adams; Michael F Leitzmann; Demetrius Albanes; Victor Kipnis; Steven C Moore; Arthur Schatzkin; Wong-Ho Chow
Journal:  Am J Epidemiol       Date:  2008-06-09       Impact factor: 4.897

10.  An epidemiologic and genomic investigation into the obesity paradox in renal cell carcinoma.

Authors:  A Ari Hakimi; Helena Furberg; Emily C Zabor; Anders Jacobsen; Nikolaus Schultz; Giovanni Ciriello; Nina Mikklineni; Brandon Fiegoli; Philip H Kim; Martin H Voss; Hui Shen; Peter W Laird; Chris Sander; Victor E Reuter; Robert J Motzer; James J Hsieh; Paul Russo
Journal:  J Natl Cancer Inst       Date:  2013-11-27       Impact factor: 13.506

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  8 in total

1.  Can Survival Bias Explain the Age Attenuation of Racial Inequalities in Stroke Incidence?: A Simulation Study.

Authors:  Elizabeth Rose Mayeda; Hailey R Banack; Kirsten Bibbins-Domingo; Adina Zeki Al Hazzouri; Jessica R Marden; Rachel A Whitmer; M Maria Glymour
Journal:  Epidemiology       Date:  2018-07       Impact factor: 4.822

2.  Explaining the Obesity Paradox: The Association between Body Composition and Colorectal Cancer Survival (C-SCANS Study).

Authors:  Bette J Caan; Jeffrey A Meyerhardt; Candyce H Kroenke; Stacey Alexeeff; Jingjie Xiao; Erin Weltzien; Elizabeth Cespedes Feliciano; Adrienne L Castillo; Charles P Quesenberry; Marilyn L Kwan; Carla M Prado
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-05-15       Impact factor: 4.254

3.  Pre-diagnostic C-reactive protein concentrations, CRP genetic variation and mortality among individuals with colorectal cancer in Western European populations.

Authors:  Katharina Nimptsch; Krasimira Aleksandrova; Veronika Fedirko; Mazda Jenab; Marc J Gunter; Peter D Siersema; Kana Wu; Verena Katzke; Rudolf Kaaks; Salvatore Panico; Domenico Palli; Anne M May; Sabina Sieri; Bas Bueno-de-Mesquita; Karina Standahl; Maria-Jose Sánchez; Aurora Perez-Cornago; Anja Olsen; Anne Tjønneland; Catalina Bonet Bonet; Christina C Dahm; María-Dolores Chirlaque; Valentina Fiano; Rosario Tumino; Aurelio Barricarte Gurrea; Marie-Christine Boutron-Ruault; Florence Menegaux; Gianluca Severi; Bethany van Guelpen; Young-Ae Lee; Tobias Pischon
Journal:  BMC Cancer       Date:  2022-06-24       Impact factor: 4.638

4.  Body Mass Index Is Associated With All-cause Mortality After THA and TKA.

Authors:  Michelle M Dowsey; Peter F M Choong; Elizabeth W Paxton; Tim Spelman; Robert S Namba; Maria C S Inacio
Journal:  Clin Orthop Relat Res       Date:  2018-06       Impact factor: 4.176

5.  The relationship between body-mass index and overall survival in non-small cell lung cancer by sex, smoking status, and race: A pooled analysis of 20,937 International lung Cancer consortium (ILCCO) patients.

Authors:  Mei Jiang; Aline F Fares; Daniel Shepshelovich; Ping Yang; David Christiani; Jie Zhang; Kouya Shiraishi; Brid M Ryan; Chu Chen; Ann G Schwartz; Adonina Tardon; Sanjay Shete; Matthew B Schabath; M Dawn Teare; Loic Le Marchand; Zuo-Feng Zhang; John K Field; Hermann Brenner; Nancy Diao; Juntao Xie; Takashi Kohno; Curtis C Harris; Angela S Wenzlaff; Guillermo Fernandez-Tardon; Yuanqing Ye; Fiona Taylor; Lynne R Wilkens; Michael Davies; Yi Liu; Matt J Barnett; Gary E Goodman; Hal Morgenstern; Bernd Holleczek; Sera Thomas; M Catherine Brown; Rayjean J Hung; Wei Xu; Geoffrey Liu
Journal:  Lung Cancer       Date:  2020-12-04       Impact factor: 5.705

6.  Collider scope: when selection bias can substantially influence observed associations.

Authors:  Marcus R Munafò; Kate Tilling; Amy E Taylor; David M Evans; George Davey Smith
Journal:  Int J Epidemiol       Date:  2018-02-01       Impact factor: 7.196

7.  Complex inter-relationship of body mass index, gender and serum creatinine on survival: exploring the obesity paradox in melanoma patients treated with checkpoint inhibition.

Authors:  Girish S Naik; Sushrut S Waikar; Alistair E W Johnson; Elizabeth I Buchbinder; Rizwan Haq; F Stephen Hodi; Jonathan D Schoenfeld; Patrick A Ott
Journal:  J Immunother Cancer       Date:  2019-03-29       Impact factor: 13.751

Review 8.  Statins as Potential Chemoprevention or Therapeutic Agents in Cancer: a Model for Evaluating Repurposed Drugs.

Authors:  Nalinie Joharatnam-Hogan; Leo Alexandre; James Yarmolinsky; Blossom Lake; Nigel Capps; Richard M Martin; Alistair Ring; Fay Cafferty; Ruth E Langley
Journal:  Curr Oncol Rep       Date:  2021-02-13       Impact factor: 5.075

  8 in total

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