Selecting controls is not selecting "normals": design and analysis issues for studying the etiology of polycystic ovary syndrome.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a highly prevalent disorder among postmenarcheal premenopausal women, accounting for much of anovulatory infertility, and it is associated with several comorbidities. The natural history of PCOS, as well as hypotheses regarding its etiology, facilitates employment of the case-control study design. However, a review of the literature suggested that inconsistency of research findings in relation to the etiology of PCOS might be, in part, due to the different choice of controls for case-control design and application.
DESIGN: Investigators have often employed "healthy" control groups and neglected to consider the tenability of the "rare disease" assumption in the analysis when instituting the case-control strategy. This might result in the introduction of a positive bias or overestimation of odds ratios, producing an effect estimate that is more extreme than that in the underlying population. Using several quantitative, though hypothetical, literature-driven examples, this bias is described and demonstrated. In addition, recommendations are provided with regard to case-sampling strategy when the rare disease assumption is untenable, as it may frequently be in studies of PCOS. CONCLUSION(S): It is hoped that more consistent case-control methodology, in concert with recent consensus on case definition, will more effectively facilitate the elucidation of the causes and consequences of PCOS.