Table 2. ROC Analysis of Variables in Predicting Elevated Liver Enzymes in Women With PCOS.

Variable	Cutoff	AUC	95% CI	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	PLH	NLH	DA (%)
BMI	25.2	0.681	0.563 - 0.798	52.9	82.4	60.0	77.8	3.00	0.57	72.5
Blood glucose	103	0.639	0.483 - 0.794	40.0	94.9	72.7	82.4	7.87	0.63	81.0
Testosterone	0.550	0.627	0.422 - 0.832	38.5	87.0	62.5	71.4	2.95	0.71	69.4
Model 1	7.46	0.783	0.664 - 0.901	40.0	94.9	72.7	82.4	7.87	0.63	81.0
Model 2	17.7	0.861	0.688 - 0.999	66.7	100	100	87.0	Inf	0.33	89.7

Optimal cutoffs for anthropometric, clinical and biochemical measures in 102 patients with PCOS. Sensitivity and specificity were calculated. Two models were set up for predicting elevated liver enzymes using ROC curves to determine clinical references for early diagnosis and prevention. Model 1 included BMI ≥ 25.2 kg/m² and blood glucose ≥ 103 mg/dL, and Model 2 included BMI ≥ 25.2 kg/m², blood glucose ≥ 103 mg/dL, and testosterone ≥ 0.550 nmol/L. ROC: receiver-operating characteristics; AUC: area under the receiver-operating characteristics curve; CI: confidence interval; PPV: positive predictive value; NPV: negative predictive value; PLH: positive likelihood ratio; NLH: negative likelihood ratio; DA: diagnostic accuracy; Inf: infinity.