When Should We Biopsy? A Risk Factor-Based Predictive Model for EIN and Endometrial Cancer

Area of Science:

• Gynecology
• Oncology
• Medical Diagnostics

Background:

• Rising global incidence of endometrial cancer (EC) across all age groups.
• Endometrial intraepithelial neoplasia (EIN) is a precursor lesion to EC.
• Need for a clinical model to identify women requiring prompt evaluation for EIN/EC.

Purpose of the Study:

• Develop a multivariable risk prediction model for EIN/EC.
• Guide endometrial biopsy decisions.
• Determine an appropriate BMI cutoff for predicting EIN/EC risk in Asian women.

Main Methods:

• Retrospective review of 1192 women undergoing hysteroscopy (2010-2023).
• Multivariable logistic regression with stepwise selection to identify independent predictors.
• Model stability and calibration assessed using bootstrap resamples.

Main Results:

• Six independent predictors identified: postmenopausal status, abnormal uterine bleeding (AUB), multiple polyps, PCOS, BMI, and endometrial thickness (EMT).
• Obesity (BMI ≥ 30 kg/m²), increased EMT (≥20 mm), and other factors significantly correlated with EIN/EC risk.
• The model demonstrated good discrimination (AUC 0.79) and excellent calibration.

Conclusions:

• A six-factor clinical model effectively stratifies individual EIN/EC risk.
• The model can guide timely, risk-based biopsy decisions, identifying high-risk patients and minimizing unnecessary procedures.
• BMI ≥ 30 kg/m² confirmed as a meaningful cutoff, but external validation is needed.