A nomogram based on the red cell distribution width to lymphocyte ratio as a prognostic tool for non-muscle-invasive bladder cancer: a retrospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: This study investigated the prognostic value of the preoperative red cell distribution width to lymphocyte ratio (RLR) for recurrence-free survival (RFS) and overall survival (OS) in patients with non-muscle-invasive bladder cancer (NMIBC) undergoing transurethral resection of bladder tumor (TURBT). Methods: A retrospective analysis was performed on data from 239 patients who received TURBT. The optimal RLR cutoff was determined using time-dependent receiver operating characteristic (ROC) curve analysis. Survival outcomes were assessed using Kaplan-Meier curves and univariate/multivariate Cox regression. An RFS prognostic nomogram incorporating independent factors was developed and evaluated via the concordance index (C-index), calibration plots, time-dependent ROC, and decision curve analysis (DCA). Subgroup analyses assessed the consistency of the RLR-RFS association.Results: Elevated preoperative RLR was an independent prognostic factor for worse RFS and OS. Moreover, compared to the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR), RLR demonstrated relatively higher predictive performance for 1-year and 3-year RFS. The novel nomogram incorporating the RLR parameter demonstrated improved predictive accuracy and a trend toward greater net clinical benefit compared to the conventional model based solely on the EORTC recurrence risk classification. Subgroup analysis indicated a stronger relationship between high RLR and poor RFS in patients with pTaN0M0 compared to those with pT1N0M0. Conclusion: Preoperative RLR represents a potential independent prognostic indicator for tumor recurrence in NMIBC patients following TURBT. The RLR-based nomogram may improve recurrence risk prediction in this population.
Source: Frontiers in Oncology
Authors: Feifan Song, Shiqiang Su, Xueqiao Zhang, Yunpeng Cao, Xiongjie Cui, Lili Zhang, Chao Li, Shen Li, Shuo Tian, Lizhe Liu
Institution: Hebei Medical University
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7125896965
