Development of a novel risk prediction and risk stratification score for polycystic ovary syndrome (PCOS)

ObjectiveThe aim of this study was to develop a simple phenotypic algorithm that can capture the underlying clinical and hormonal abnormalities to help in the diagnosis and risk stratification of polycystic ovary syndrome (PCOS).MethodsThe study consisted of 111 women with PCOS fulfilling the Rotterdam diagnostic criteria and 67 women without PCOS. A Firth's penalized logistic regression model was used for independent variable section. Model optimism, discrimination and calibration were assessed using bootstrapping, area under the curve (AUC) and Hosmer‐Lemeshow statistics, respectively. The prognostic index (PI) and risk score for developing PCOS were calculated using independent variables from the regression model.ResultsFirth penalized logistic regression model with backward selection identified four independent predictors of PCOS namely free androgen index [β 0.30 (0.12), P = 0.008], 17‐OHP [β = 0.20 (0.01), P = 0.026], anti‐mullerian hormone [AMH; β = 0.04 (0.01) P < 0.0001] and waist circumference [β = 0.08 (0.02), P < 0.0001]. The model estimates indicated high internal validity (minimal optimism on 1000‐fold bootstrapping), good discrimination ability (bias corrected c‐statistic = 0.90) and good calibration (Hosmer‐Lemeshow χ2 = 3.7865). PCOS women with a high‐risk score (q1 + q2 + q3 vs q4) presented with a worse metabolic profile characterized by a higher 2‐hour glucose (P = 0.01), insulin (P = 0.0003), triglycerides (P = 0.0005), C‐reactive protein (P < 0.0001) and low HDL‐cholesterol (P = 0.02) as compared to those with lower risk score for PCOS.ConclusionsWe propose a simple four‐variable model, which captures the underlying clinical and hormonal abnormalities in PCOS and can be used for diagnosis and metabolic risk stratification in women with PCOS

Exercise and Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is a complex endocrinopathy affecting both the metabolism and reproductive system of women of reproductive age. Prevalence ranges from 6.1-19.9% depending on the criteria used to give a diagnosis. PCOS accounts for approximately 80% of women with anovulatory infer-tility, and causes disruption at various stages of the reproductive axis. Evidence suggests lifestyle modification should be the first line of therapy for women with PCOS. Several studies have examined the impact of exercise interventions on reproductive function, with results indicating improvements in menstrual and/or ovulation frequency following exercise. Enhanced insulin sensitivity underpins the mechanisms of how exercise restores reproductive function. Women with PCOS typically have a cluster of metabolic abnormalities that are risk factors for CVD. There is irrefutable evidence that exercise mitigates CVD risk factors in women with PCOS. The mechanism by which exercise improves many CVD risk factors is again associated with improved insulin sensitivity and decreased hyperinsulinemia. In addition to cardiometabolic and reproductive complications, PCOS has been associated with an increased prevalence of mental health disorders. Exercise improves psychological well-being in women with PCOS, dependent on certain physiological factors. An optimal dose-response relationship to exercise in PCOS may not be feasible because of the highly individualised characteristics of the disorder. Guidelines for PCOS suggest at least 150 min of physical activity per week. Evidence confirms that this should form the basis of any clinician or healthcare professional prescription