Dataset Information

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

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.

SUBMITTER: Mayeda ER

PROVIDER: S-EPMC5858690 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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

Mayeda Elizabeth Rose ER Glymour M Maria MM

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20170101 1

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 surv ...[more]

PMID: 28069728

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Project description:BackgroundDietary exposure assessments are a critical issue in evaluating human nutrition studies; however, nutrition-specific criteria are not consistently included in existing bias assessment tools.ObjectivesOur objective was to develop a set of risk of bias (RoB) tools that integrated nutrition-specific criteria into validated generic assessment tools to address RoB issues, including those specific to dietary exposure assessment.MethodsThe Nutrition QUality Evaluation Strengthening Tools (NUQUEST) development and validation process included 8 steps. The first steps identified 1) a development strategy; 2) generic assessment tools with demonstrated validity; and 3) nutrition-specific appraisal issues. This was followed by 4) generation of nutrition-specific items and 5) development of guidance to aid users of NUQUEST. The final steps used established ratings of selected studies and feedback from independent raters to 6) assess reliability and validity; 7) assess formatting and usability; and 8) finalize NUQUEST.ResultsNUQUEST is based on the Scottish Intercollegiate Guidelines Network checklists for randomized controlled trials, cohort studies, and case-control studies. Using a purposive sample of 45 studies representing the 3 study designs, interrater reliability was high (Cohen's κ: 0.73; 95% CI: 0.52, 0.93) across all tools and at least moderate for individual tools (range: 0.57-1.00). The use of a worksheet improved usability and consistency of overall interrater agreement across all study designs (40% without worksheet, 80%-100% with worksheet). When compared to published ratings, NUQUEST ratings for evaluated studies demonstrated high concurrent validity (93% perfect or near-perfect agreement). Where there was disagreement, the nutrition-specific component was a contributing factor in discerning exposure methodological issues.ConclusionsNUQUEST integrates nutrition-specific criteria with generic criteria from assessment tools with demonstrated reliability and validity. NUQUEST represents a consistent and transparent approach for evaluating RoB issues related to dietary exposure assessment commonly encountered in human nutrition studies.

Dataset Information

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

Publications

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

Similar Datasets

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