The Predictive Power of Endocrine Tests for the Diagnosis of Polycystic Ovaries in Women with Oligoamenorrhea

Abstract

Various hormonal parameters and the best logistic regression model to predict disease probability were evaluated in women with polycystic ovary syndrome (PCOS). Concentrations of LH, FSH, LH/FSH ratio, testosterone, free testosterone, SHBG and insulin in serum were recorded in 32 women with PCOS and in 25 controls. A model including LH/FSH ratio, insulin and testosterone measurements yielded the best goodness of fit for classification of women with and without PCOS in the logistic regression analysis. Only LH/FSH ratio and insulin were retained as significant variables. The diagnostic characteristics of LH/FSH ratio and insulin for PCOS when compared by receiver-operator characteristic analysis were found to be equally effective. By combining these two variables a higher area under curve was obtained. LH/FSH ratio, insulin or the combination of these two can predict the disease probability in women with PCOS.