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Recurrence in Non-Muscle Invasive Bladder Cancer Patients: External Validation of the EORTC, CUETO and EAU Risk Tables and Towards a Non-Linear Survival Model

Recurrence in Non-Muscle Invasive Bladder Cancer Patients: External Validation of the EORTC,... BACKGROUND:EORTC, CUETO and EAU are the most commonly used risk stratification models for recurrence and progression in non-muscle invasive bladder cancer (NMIBC).OBJECTIVE:We assessed the predictive value of the EORTC, CUETO and EAU risk group stratification methods for our population and explore options to improve the predictive value using Cox Proportional Hazards (CPH), Boosted Cox regression and a non-linear Random Survival Forest (RSF) model.MATERIALS:Our retrospective database included of 452 NMIBC patients who underwent a transurethral resection of bladder tumor (TURBT) between 2000 and 2018 in our hospital. The cumulative incidence of recurrence was calculated at one- and five-years for all risk stratification methods. A customized CPH, Boosted Cox and RSF models were trained in order to predict recurrence, and the performances were compared.RESULTS:Risk stratification using the EORTC, CUETO and EAU showed small differences in recurrence probabilities between the risk groups as determined by the risk stratification. The concordance indices (C-index) were low and ranged between 0.51 and 0.57. The predictive accuracies of CPH, Boosted Cox and RSF models were also moderate, with C-indices ranging from 0.61 to 0.64.CONCLUSIONS:Prediction of recurrence in patients with NMIBC based on patient characteristics is difficult. Alternative (non-linear) approaches have the potential to improve the predictive value. Nonetheless, the currently used characteristics are unable to properly stratify between the recurrence risks of patients. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bladder Cancer IOS Press

Recurrence in Non-Muscle Invasive Bladder Cancer Patients: External Validation of the EORTC, CUETO and EAU Risk Tables and Towards a Non-Linear Survival Model

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References (39)

Publisher
IOS Press
Copyright
Copyright © 2020 © 2020 – IOS Press and the authors. All rights reserved
ISSN
2352-3727
eISSN
2352-3735
DOI
10.3233/BLC-200305
Publisher site
See Article on Publisher Site

Abstract

BACKGROUND:EORTC, CUETO and EAU are the most commonly used risk stratification models for recurrence and progression in non-muscle invasive bladder cancer (NMIBC).OBJECTIVE:We assessed the predictive value of the EORTC, CUETO and EAU risk group stratification methods for our population and explore options to improve the predictive value using Cox Proportional Hazards (CPH), Boosted Cox regression and a non-linear Random Survival Forest (RSF) model.MATERIALS:Our retrospective database included of 452 NMIBC patients who underwent a transurethral resection of bladder tumor (TURBT) between 2000 and 2018 in our hospital. The cumulative incidence of recurrence was calculated at one- and five-years for all risk stratification methods. A customized CPH, Boosted Cox and RSF models were trained in order to predict recurrence, and the performances were compared.RESULTS:Risk stratification using the EORTC, CUETO and EAU showed small differences in recurrence probabilities between the risk groups as determined by the risk stratification. The concordance indices (C-index) were low and ranged between 0.51 and 0.57. The predictive accuracies of CPH, Boosted Cox and RSF models were also moderate, with C-indices ranging from 0.61 to 0.64.CONCLUSIONS:Prediction of recurrence in patients with NMIBC based on patient characteristics is difficult. Alternative (non-linear) approaches have the potential to improve the predictive value. Nonetheless, the currently used characteristics are unable to properly stratify between the recurrence risks of patients.

Journal

Bladder Cancer – IOS Press

Published: Sep 21, 2020

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