A Risk-scoring Model for Predicting Post-recurrence Survival in Patients With Endometrial Carcinoma

Area of Science:

• Gynecology
• Oncology
• Medical Statistics

Background:

• Recurrent endometrial carcinoma typically has a poor prognosis.
• Significant variability exists in patient survival times.
• Predictive tools for post-recurrence survival are needed.

Purpose of the Study:

• To develop and validate a risk-scoring model for predicting survival in patients with recurrent endometrial carcinoma.
• To identify key factors influencing post-recurrence survival.

Main Methods:

• Retrospective analysis of 236 patients with recurrent endometrial carcinoma (2007-2013).
• Logistic regression models used to identify independent predictors of short survival.
• Risk scores derived from odds ratios of identified factors.

Main Results:

• Platelet count, serum CA125, and progression-free survival were significant predictors.
• A risk-scoring model achieved an AUC of 0.782 (95% CI 0.713-0.851).
• Excluding primary refractory disease identified age and hemoglobin as predictors, yielding a model with AUC 0.821 (95% CI 0.750-0.892).

Conclusions:

• A validated risk-scoring model accurately predicts post-recurrence survival in endometrial carcinoma.
• The model demonstrates utility with or without primary refractory disease.
• This tool has potential for precision medicine applications in endometrial cancer care.