Integrating Radiosensitivity Index and Radiation Resistance Related Index Improves Prostate Cancer Outcome Prediction.

ABSTRACT:

Purpose

This study aimed to establish a nomogram combining 31-gene signature (31-GS), radiosensitivity index (RSI), and radiation-resistance-related gene index (RRRI) to predict recurrence in prostate cancer (PCa) patients.

Methods and materials

Transcriptome data of PCa were obtained from gene expression omnibus and the cancer genome atlas to validate the predictive potential of 3 sets of published biomarkers, namely, 31-GS, RSI, and RRRI. To adjust these markers for the characteristics of PCa, we analyzed 4 PCa-associated radiosensitivity predictive indices based on 31-GS, RSI, and RRRI by the Cox analysis and least absolute shrinkage and selection operator regression analysis. Time-dependent receiver operating characteristic curves, decision curve analyses, integrated dis

SUBMITTER: Wu QQ 

PROVIDER: S-EPMC11872654 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature