Data-driven prognostic factors analysis and personalized follow-up strategies for post-progression survival in locally advanced esophageal squamous cell carcinoma after definitive chemoradiotherapy.

ABSTRACT:

Background

This study investigates clinical characteristics influencing post-progression survival (PPS) in locally advanced esophageal squamous cell carcinoma (ESCC) after definitive chemoradiotherapy (dCRT), aiming to develop individualized follow-up strategies using conditional PPS.

Methods

The correlation between PPS and overall survival (OS) using Spearman correlation analysis. LASSO regression, Cox regression, and machine-learning methods were employed to identify prognostic factors, and a prediction model was constructed. The Shapley additive explanations (SHAP) method was used to interpret the model. Conditional PPS survival rates and recurrence risks were analyzed.

Results

This study enrolled 741 patients, with a median follow-up of 27.2 months. PPS was positi

SUBMITTER: Qiu J 

PROVIDER: S-EPMC12777853 | biostudies-literature | 2026 Dec

REPOSITORIES: biostudies-literature