Endometrial thickness and its diagnostic utility in postmenopausal women: A retrospective analysis of ultrasound and histopathological findings

This study aims to assess the diagnostic performance of transvaginal ultrasound (TVUS) and create a multivariable risk stratification model to detect endometrial malignancy and precursor lesions in postmenopausal women with asymptomatic endometrial thickening. In this retrospective observational study, 587 postmenopausal women with asymptomatic endometrial thickening identified during routine TVUS were included. The participants were divided into two groups: a positive group (221 women with malignant or precursor lesions) and a negative group (366 women with benign lesions), based on histopathological results. Data collected included endometrial thickness, ultrasound features, and clinical risk factors such as age, BMI, and diabetes status. Multivariable logistic regression was used to assess the predictive value of individual and combined factors. The performance of the risk stratification model was validated using sensitivity, specificity, and the area under the receiver operating characteristic curve. Comparative analyses were done to evaluate the diagnostic value of individual parameters and the combined forecasting model. Endometrial thickness was significantly higher in the positive group (14.2 ± 4.8 mm) compared to the negative group (10.1 ± 3.2 mm, p < 0.001). Ultrasound features like irregular endometrial borders and heterogeneous echotexture were more commonly seen in the positive group (34.5 % vs. 7.5 %, p < 0.001). Multivariable analysis revealed that endometrial thickness (OR 2.94, p < 0.001), ultrasound abnormalities (OR 4.12, p < 0.001), diabetes (OR 1.98, p < 0.001), and BMI ≥30 kg/m 2 (OR 1.82, p = 0.009) were independent predictors of malignancy. The combined forecasting model achieved an AUC of 0.81, surpassing the performance of individual parameters. The use of clinical and ultrasound features in a multivariable risk stratification model significantly enhances diagnostic accuracy for detecting endometrial malignancy. This approach provides a practical and personalized method for identifying high-risk postmenopausal women, helping to target interventions and reduce unnecessary procedures.