Recurrence-free survival prediction for anal squamous cell carcinoma after chemoradiotherapy using planning CT-based radiomics model.

ABSTRACT:

Objectives

Approximately 30% of non-metastatic anal squamous cell carcinoma (ASCC) patients will experience recurrence after chemoradiotherapy (CRT), and currently available clinical variables are poor predictors of treatment response. We aimed to develop a model leveraging information extracted from radiation pretreatment planning CT to predict recurrence-free survival (RFS) in ASCC patients after CRT.

Methods

Radiomics features were extracted from planning CT images of 96 ASCC patients. Following pre-feature selection, the optimal feature set was selected via step-forward feature selection with a multivariate Cox proportional hazard model. The RFS prediction was generated from a radiomics-clinical combined model based on an optimal feature set with 5 repeats of nested 5-fo

SUBMITTER: Tang S 

PROVIDER: S-EPMC11751359 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature