Characterizing the Clinical and Genetic Spectrum of Polycystic Ovary Syndrome in Electronic Health Records
Year: 2020
Type: article
Study design: Observational Study
Abstract: CONTEXT: Polycystic ovary syndrome (PCOS) is one of the leading causes of infertility, yet current diagnostic criteria are ineffective at identifying patients whose symptoms reside outside strict diagnostic criteria. As a result, PCOS is underdiagnosed and its etiology is poorly understood. OBJECTIVE: We aim to characterize the phenotypic spectrum of PCOS clinical features within and across racial and ethnic groups. METHODS: We developed a strictly defined PCOS algorithm (PCOSkeyword-strict) using the International Classification of Diseases, ninth and tenth revisions and keywords mined from clinical notes in electronic health records (EHRs) data. We then systematically relaxed the inclusion criteria to evaluate the change in epidemiological and genetic associations resulting in 3 subsequent algorithms (PCOScoded-broad, PCOScoded-strict, and PCOSkeyword-broad). We evaluated the performance of each phenotyping approach and characterized prominent clinical features observed in racially and ethnically diverse PCOS patients. RESULTS: The best performance came from the PCOScoded-strict algorithm, with a positive predictive value of 98%. Individuals classified as cases by this algorithm had significantly higher body mass index (BMI), insulin levels, free testosterone values, and genetic risk scores for PCOS, compared to controls. Median BMI was higher in African American females with PCOS compared to White and Hispanic females with PCOS. CONCLUSIONS: PCOS symptoms are observed across a severity spectrum that parallels the continuous genetic liability to PCOS in the general population. Racial and ethnic group differences exist in PCOS symptomology and metabolic health across different phenotyping strategies.
Institutions: Meharry Medical College, Vanderbilt University Medical Center
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,750
Funders: Doris Duke Charitable Foundation, Vanderbilt University, Vanderbilt University Medical Center, Georgia Clinical and Translational Science Alliance, National Institutes of Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, National Center for Research Resources, National Center for Advancing Translational Sciences, National Institute on Minority Health and Health Disparities, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1435936284, G1531600799, G1706615277, G1766209448, G1846282300, G1967470738, G2103760183, Understanding the genetic risk underlying racial disparities in uterine fibroids, G2310098089, G2328519459, G25420283, G2615776415, G2683268942, G3395468139, G3420921512, G3619590958, G364208108, G3791753988, G3938985443, G4049315607, G4198746417, Automated Storage and Retrieval of Biological Systems, G4395870004, G4410787187, The Meharry RISE initiative, G450819360, G560889077, G5679716143, G5717004637, Genetic Epidemiology of Multiple Sclerosis, G6173849340, G6589054092, G669548034, G7163342664, Training in Pharmacological Sciences, The Vanderbilt Institute for Clinical and Translational Research (VICTR), G8098630230, Epidemiologic Architecture for Genes Linked to Environment (EAGLE), G8332127685, G9000008449, G9000011408, G9000022789, G9000043901, G9000054231, G9000090229, G9000167145, Research Training in Diabetes and Endocrinology, G949362299, G95160140
OpenAlex ID: W3087830223