Screening for Androgen Excess in Women: Accuracy of Self-Reported Excess Body Hair Growth and Menstrual Dysfunction
Jessica L. Chan, Marita Pall, Uche Ezeh, Ruchi Mathur, Margareta D. Pisarska, Ricardo Azziz
Abstract
CONTEXT: Epidemiologic studies of polycystic ovary syndrome (PCOS) are limited, especially in populations where diagnostic resources are less available. In these settings, an accurate, low-cost screening tool would be invaluable. OBJECTIVE: To test the use of a simple questionnaire to identify women at increased risk for PCOS and androgen excess (AE) disorders. STUDY DESIGN: Prospective cohort study from 2006-2010. SETTING: Community-based. PARTICIPANTS: Women aged 14 to 45 years. INTERVENTION: A screening telephone questionnaire consisting of 3 questions was tested, where participants were asked to self-assess the presence/absence of male-like hair and menstrual irregularity. Participants were then invited to undergo a direct examination, including completing a medical history and undergoing a modified Ferriman-Gallwey (mFG) hirsutism score, ovarian ultrasound, and measurement of circulating total and free testosterone, DHEAS, TSH, prolactin and 17-hydroxyprogesterone levels. MAIN OUTCOME MEASURE: Accuracy of questionnaire in predicting PCOS, AE, and irregular menses. RESULTS: Participants with self-assessed irregular menses and/or excess hair were labeled "Possible Androgen Excess (Poss-AE)" and those self-assessed with regular menses and no excess hair were labeled "Probable Non-Androgen Excess (Non-AE)." The study was completed in 206/298 (69%) of the Poss-AE and in 139/192 (73%) of the Non-AE. Of Poss-AE and Non-AE subjects, 82.5% and 15.8%, respextively, presented with PCOS. The calculated sensitivity, specificity, positive predictive value, and negative predictive value of the 3-question telephone survey to predict PCOS was 89%, 78%, 85%, and 83%, respectively. CONCLUSIONS: A simple telephone questionnaire, based on self-assessment of body hair and menstrual status, can be used with a high predictive value to identify women at risk for AE disorders, including PCOS, and to detect healthy controls. This approach could be an important tool for needed epidemiologic studies.