Validity of administrative health data case definitions for identifying polycystic ovary syndrome: a systematic review and meta-analysis.

study questionWhat is the validity of published administrative health data case definitions of polycystic ovary syndrome (PCOS) compared with reference standards? SUMMARY ANSWER: Due to the limited number of eligible studies, drawing definitive conclusions is challenging; however, this review highlights significant gaps and variability in current PCOS case definitions, underscoring the need for standardized case definitions in future research. WHAT IS KNOWN ALREADY: Administrative health data offer the opportunity to evaluate health outcomes and disease epidemiology at a population-level. Currently, the validity of existing administrative health data case definitions for PCOS is unknown. STUDY DESIGN, SIZE, DURATION: A systematic review of the literature was conducted on full-text English-language articles up to July 2023, using the MEDLINE and EMBASE databases. PARTICIPANTS/MATERIALS, SETTING,

methodsTwo reviewers independently screened titles, abstracts and full texts, extracted data, assessed study quality and graded validity. A random effects meta-analysis was conducted to pool reported validity measures and heterogeneity was examined. MAIN RESULTS AND THE ROLE OF CHANCE: The review included four eligible articles consisting of three cross-sectional studies and one retrospective cohort study. Two studies defined PCOS using the Rotterdam Criteria, one study used self-report, and one used a clinical gold standard. All case definitions included the International Classification of Diseases (ICD)-9 code 256.4 for 'polycystic ovaries' and three studies used E28.2 for 'polycystic ovarian syndrome'. Three studies reported positive predictive value (PPV), which ranged from 30 to 96%. One study reported both PPV (96%) and sensitivity (50%) for one case definition. The pooled PPV estimate for the ICD code-based case definitions was 88% (95% confidence interval 82-95%; I2 = 100%). One study reported fair agreement (percent agreement= 90.3, κ = 0.27, percent agreement bias adjusted κ = 0.81). Overall, the risk of bias of the included studies was low. LIMITATIONS, REASONS FOR CAUTION: There were limited number of validations and precision indices of validations. WIDER IMPLICATIONS OF THE

findingsFurther validation of these case definitions in other administrative health datasets, and development of novel coding algorithms is required to inform future population-based studies in PCOS. STUDY FUNDING/COMPETING INTEREST(S): No external funding was used and there are no disclosures. REGISTRATION NUMBER: PROSPERO CRD42023385617.