A Novel Nomogram for Predicting Endometrial Malignancy in Postmenopausal Women

Area of Science:

• Gynecologic Oncology
• Reproductive Medicine
• Biomarker Research

Background:

• Postmenopausal women are at risk for endometrial malignancy.
• Early detection of endometrial cancer is crucial for improved patient outcomes.
• Accurate risk stratification is needed for timely and personalized interventions.

Purpose of the Study:

• To identify clinical risk factors for endometrial malignancy in postmenopausal women.
• To develop and validate a predictive model for early detection of endometrial cancer.
• To enable personalized intervention strategies based on individual risk.

Main Methods:

• Analysis of 1146 postmenopausal women undergoing diagnostic hysteroscopy.
• Multivariate logistic regression to identify independent risk factors for endometrial carcinoma.
• Development and validation of a predictive nomogram using ROC analysis, calibration plots, and decision curve analysis.

Main Results:

• Endometrial carcinoma was diagnosed in 6.0% of cases.
• Seven independent risk factors identified: elevated fibrinogen and D-dimer, hypertriglyceridemia, decreased HDL, postmenopausal bleeding, ultrasonography blood-flow signals, and increased endometrial thickness.
• The predictive nomogram demonstrated high diagnostic performance (AUC 0.955-0.960).

Conclusions:

• A novel 7-indicator prediction model for endometrial malignancy risk was developed and validated.
• The model shows excellent discriminative ability for risk stratification in postmenopausal women.
• This tool supports early detection and personalized management of endometrial cancer.