Abstract
STUDY QUESTION: What 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, METHODS: Two 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 FINDINGS: Further 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.