ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2017
The Obesity Paradox in Survival after Cancer Diagnosis: Tools for Evaluation of Potential Bias.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Adiposity and cancer survival: a systematic review and meta-analysis.Cancer causes & control : CCC · 2022Pooled it
- Chronic High-Fat Diet Does Not Alter Overall Cancer Incidence in Trp53R270H/+ Mice.Cancer research communications · 2026Article
- Variation in image-assessed abdominal adiposity and skeletal muscle and their associations with pathological characteristics in renal cell carcinoma.Cancer causes & control : CCC · 2026Article
- Polygenic risk score and 20-year prostate cancer-specific mortality and survival.Communications medicine · 2026Article
- Collider Bias Is an Insufficient Explanation for the Inverse Obesity Paradox in Prostate Cancer.Cancer medicine · 2025Article
- Identifying characteristics and clinical conditions associated with hand grip strength in adults: the Project Baseline Health Study.Scientific reports · 2024Article
- Associations of combined physical activity and body mass index groups with colorectal cancer survival outcomes.BMC cancer · 2023Article
- A hint for the obesity paradox and the link between obesity, perirenal adipose tissue and Renal Cell Carcinoma progression.Scientific reports · 2022Article
- Body mass index and survival after cancer diagnosis: A pan-cancer cohort study of 114 430 patients with cancer.Innovation (Cambridge (Mass.)) · 2022Article
- Article
- Selection bias in multidrug-resistant tuberculosis cohort studies assessing sputum culture conversion.PloS one · 2022Article
- Statins as Potential Chemoprevention or Therapeutic Agents in Cancer: a Model for Evaluating Repurposed Drugs.Current oncology reports · 2021Review
- 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.Lung cancer (Amsterdam, Netherlands) · 2021Article
- The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2020Article
- Obesity paradox in cancer: Is bigger really better?Evolutionary applications · 2019Article
- Complex inter-relationship of body mass index, gender and serum creatinine on survival: exploring the obesity paradox in melanoma patients treated with checkpoint inhibition.Journal for immunotherapy of cancer · 2019Article
- Can Survival Bias Explain the Age Attenuation of Racial Inequalities in Stroke Incidence?: A Simulation Study.Epidemiology (Cambridge, Mass.) · 2018Article
- Body Mass Index Is Associated With All-cause Mortality After THA and TKA.Clinical orthopaedics and related research · 2018Article
- Collider scope: when selection bias can substantially influence observed associations.International journal of epidemiology · 2018Article
- Explaining the Obesity Paradox: The Association between Body Composition and Colorectal Cancer Survival (C-SCANS Study).Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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.
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