BACKGROUND: Polycystic ovary syndrome is the most common endocrine disorder affecting reproductive-aged women. It is diagnosed using a combination of menstrual irregularity, clinical and/or biochemical hyperandrogenism and polycystic ovary morphology upon ultrasound. Hyperandrogenism in females may clinically manifest as hirsutism, acne, alopecia, or other masculinization of features. Assessing total/free testosterone, dehydroepiandrosterone sulfate, and 17-hydroxyprogesterone provides biochemical evidence of hyperandrogenism. OBJECTIVE: To determine self-reported clinical signs of androgen excess using data from the Ovulation and Menstruation Health (OM) Study, a diverse, multi-ethnic cohort study being conducted at Boston University School of Medicine. METHODS: Data was collected from participants enrolled in the Ovulation and Menstruation Health Study pilot cohort. This epidemiologic survey captured demographics, menstrual cycle patterns, PCOS histories, reproductive histories and manifestations of androgen excess in a diverse patient population. Participants were women ages 18-45 who had the capacity to ovulate/menstruate at the time of the study, had no history of chemotherapy, radiation, or surgical menopause, and were not pregnant at the time of the study. To assess androgen excess, participants were asked to self-report hair growth in nine body areas, acne on the face and back and hair loss on the scalp. The nine body areas were scored using the modified Ferriman-Gallwey (mFG) scoring system. Reference images created by a medical illustrator were used for hirsutism and alopecia grading while clear descriptions were provided for grading acne severity. Clinical hirsutism was defined as total mFG score of ≥ 8, or ethnic specific cutoff for East Asian (≥ 2) and Southeast Asian (≥ 3) women. Alopecia was defined as scalp hair loss ≥ 2. For participants that consented to medical record validation total, free and bioavailable testosterone lab levels were assessed for biochemical hyperandrogenism evaluation. RESULTS: Beginning August 9, the day the study opened to the public, 249 participants completed the pilot survey questionnaire. These participants were 66.8% white (n=165), 6.5% Hispanic or Spanish origin (n=16), 10.5% Black or African-American (n=26), 1.6% East Asian (n=4), 2.0% Southeast Asian (n=5), 2.4% South Asian (n=6), and 10.9% were of mixed ethnic backgrounds (n=27). 22.5% (55/245) of these women had clinical hirsutism by total mFG score. Mean total mFG scores were highest in women who were South Asian at 13.8±9.1 (n=6) and Hispanic at 8.6±8.7 (n=16). Moderate-severe acne was reported in 23.6% (58/246) of respondents, 24.8% (41/165) of white women, 26.7% (4/15) of Hispanic women, 15.4% (4/26) of Black women, 0.0% (0/4) of East Asian women, 20.0% (1/5) of Southeast Asian women, 50% of South Asian women (3/6) and 20% (5/25) of women of mixed ethnicities. 9.4% (23/246) of all pilot women reported alopecia, highest in Black (26.9%, 7/26) and East Asian women (25%, 1/4). Among women that had a PCOS diagnosis there was a higher presence of clinical hirsutism, higher acne severity, and higher prevalence of alopecia when compared to non-PCOS women. In addition, 33%(4/12) of the 44 women that consented to medical record validation had total testosterone levels above the normal range. CONCLUSIONS: This pilot population demonstrated an ethnic dependent pattern of development for hirsutism, acne and alopecia. Additionally, women who had a PCOS diagnosis were more likely to report having the clinical signs of androgen excess than those without a diagnosis. / 2020-06-14T00:00:00Z

INTRODUCTION: Polycystic Ovary Syndrome (PCOS) is the most common endocrinopathy causing infertility in women of reproductive age. According to the Rotterdam criteria, a PCOS diagnosis should be given if at least two of the following are met: 1) hyperandrogenism; 2) oligo-anovulation; and 3) polycystic ovarian morphology. Previous studies analyzing the prevalence of PCOS have done so in unselected and clinical populations but few studies have attempted to characterize the syndrome and its long-term outcomes within Electronic Health Records using International Classification of Disease (ICD) codes. OBJECTIVES: With a hospital-based electronic health record dataset, this thesis seeks to: (1) characterize PCOS in reproductively aged women (18-34) using the diagnostic codes (ICD-9 and ICD-10) versus the Rotterdam criteria, (2) determine the prevalence of metabolic syndrome (MetS), Type 2 Diabetes, and cardiac events in women above age 35, (3) determine age of diagnosis for MetS and time to diagnosis of MetS. METHODS: The following 3 cohorts were queried on the Research Patient Data Registry (RPDR): 1) patients aged 18-34 with classic PCOS (phenotype A and B) but without an ICD diagnosis for PCOS, 2) patients aged 18-34 with a PCOS ICD-9/10 diagnosis and 3) patients above age 35 with a history or current diagnosis of PCOS. Their electronic health records (between January 1 , 2003 and December 31 , 2020) were ascertained from 9 Mass General Brigham institutions after IRB approval and analyzed on Software for Statistics and Data Science (STATA). RESULTS: Overall, RPDR identified 12,669 patients aged 18-34 who fit the Rotterdam criteria (under multiple phenotypes), 4646 of which had classic PCOS but lacked an ICD- 9/10 code for PCOS. RPDR also identified 9341 women aged 35 and above with a past or current diagnosis of PCOS. Hispanics/Latinas (18-34) were two times more likely to be undiagnosed when compared to Non-Hispanic Whites (OR: 2.25, 95% CI: 1.98-2.56). The prevalence of MetS, specified by a diagnostic code (277.7 or E88.81), and other cardiac conditions in women above age 35 were considerably lower than those found in the current literature. CONCLUSION: Databases such as RPDR allow for a detailed analysis of patient demographics, labs, procedures and diagnoses. Additionally, it allows for larger cohorts of patients matching more specific criteria to be ascertained. Future studies should compare the prevalence of individual features of MetS by ICD codes and analyze the cardiology reports to determine if the events are being reported but not codified. / 2023-11-30