Selection bias in rheumatic disease research

Hyon K. Choi, Uyen Sa Nguyen, Jingbo Niu, Goodarz Danaei, Yuqing Zhang

Research output: Contribution to journalReview articlepeer-review

77 Scopus citations


The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias - a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic - in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the 'risk factor paradox' - a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research.

Original languageEnglish
Pages (from-to)403-412
Number of pages10
JournalNature Reviews Rheumatology
Issue number7
StatePublished - Jul 2014


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