• Donald A Redelmeier and Jonathan S Zipursky.
• Department of Medicine, University of Toronto, Toronto, Canada. dar@ices.on.ca.
• J Gen Intern Med. 2023 Dec 1; 38 (16): 360436093604-3609.

AbstractObservational research can be strengthened by examining potential dose-response relationships that correlate a clinical intervention with a patient outcome. Despite being a classic criterion for establishing causality, dose-response testing can be difficult to interpret in clinical medicine due to multiple diverse pitfalls. This review introduces a cautionary framework for investigators considering dose-response relationships in observational research to support evidence-based medicine. Each pitfall is illustrated with a specific example relevant when analyzing a dose-response relationship. Several pitfalls stem from faulty interpretation including confounding by indication and fallible range selection. Additional pitfalls relate to improper analysis including fitting a nonlinear model and misclassification error. Further pitfalls arise in special situations including subjective self-report and artifacts from survival bias. These caveats are common sources of misunderstanding in analyses that examine the link between varying exposures and the intensity of clinical outcomes. Awareness of specific pitfalls, we suggest, might help advance the conduct, application, and translation of dose-response relationships in observational research to inform evidence-based medical care.© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.

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