Background The majority of available studies on the AMH thresholds were not age-specific and performed the receiver operating characteristic curve (ROC) analysis, based on variations in sensitivity and specificity rather than positive and negative predictive values (PPV and NPV, respectively), which are more clinically applicable. Moreover, all of these studies used a pre-specified age categorization to report the age-specific cut-off values of AMH. Methods A total of 803 women, including 303 PCOS patients and 500 eumenorrheic non-hirsute control women, were enrolled in the present study. The PCOS group included PCOS women, aged 20–40 years, who were referred to the Reproductive Endocrinology Research Center, Tehran, Iran. The Rotterdam consensus criteria were used for diagnosis of PCOS. The control group was selected among women, aged 20–40 years, who participated in Tehran Lipid and Glucose cohort Study (TLGS). Generalized additive models (GAMs) were used to identify the optimal cut-off points for various age categories. The cut-off levels of AMH in different age categories were estimated, using the Bayesian method. Main results and the role of chance Two optimal cut-off levels of AMH (ng/ml) were identified at the age of 27 and 35 years, based on GAMs. The cut-off levels for the prediction of PCOS in the age categories of 20–27, 27–35, and 35–40 years were 5.7 (95 % CI: 5.48–6.19), 4.55 (95 % CI: 4.52–4.64), and 3.72 (95 % CI: 3.55–3.80), respectively. Based on the Bayesian method, the PPV and NPV of these cut-off levels were as follows: PPV = 0.98 (95 % CI: 0.96–0.99) and NPV = 0.40 (95 % CI: 0.30–0.51) for the age group of 20–27 years; PPV = 0.96 (95 % CI: 0.91–0.99) and NPV = 0.82 (95 % CI: 0.78–0.86) for the age group of 27–35 years; and PPV = 0.86 (95 % CI: 0.80–0.94) and NPV = 0.96 (95 % CI: 0.93–0.98) for the age group of 35–40 years. Conclusions Application of age-specific cut-off levels of AMH, according to the GAMs and Bayesian method, could elegantly assess the value of AMH in discriminating PCOS patients in all age categories.
BackgroundInsulin resistance (IR) is a major cardiometabolic risk factor in females with polycystic ovary syndrome (PCOS). The euglycemic clamp is the gold standard method to measure IR. However, considering the time and cost that it takes, surrogate markers of IR are now widely used. The current study aimed at evaluating the cutoff points of even less invasive anthropometric and body composition variables to predict IR in females with PCOS.MethodsThe current cross sectional study selected 224 females with PCOS, using Rotterdam criteria, referred to reproductive endocrinology research center; 88 of which were diagnosed with insulin resistance. Receiver operating characteristics curve was used to explore the best cutoff values of each anthropometric and body composition measures. IR was defined as homeostasis model assessment formula greater or equal to 2.6: HOMA-IR = fasting insulin (mU/L) × fasting plasma glucose (mM/L)/22.5.ResultsThe highest area under the curve (0.751) was for the multiplication of waist circumference (WC) by body mass index (BMI), as a single index. The highest sensitivity and specificity were for body water (BW) percentage (82% for values greater than 32.85%) and WC (79% for values greater than 88 cm), respectively.ConclusionsIt was concluded that there were simple anthropometric variables; e.g., WC × BMI, percentage of BW, and WC that could help to estimate IR in clinical settings especially when the gold standard or surrogate markers of IR were unavailable.
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