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Risk stratification and conditional recurrence after radical cystectomy: toward adaptive follow-up.

Roberto Contieri¹, Alberto Martini², Marc Furrer^3,4

¹Department of Urology, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale, Naples, Italy.

BJU International

|March 13, 2026

Summary

A new model identifies high-risk bladder cancer patients after radical cystectomy (RC) using pathological T stage, node status, and lymphovascular invasion (LVI). This allows for tailored follow-up schedules to improve patient outcomes.

Keywords:

Muscle invasive bladder cancer follow‐up radical cystectomy recurrence risk stratification

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Establishing a Competing Risk Regression Nomogram Model for Survival Data

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Published on: October 23, 2020

Area of Science:

Urology
Oncology
Data Science in Medicine

Background:

Radical cystectomy (RC) is a primary treatment for muscle-invasive bladder cancer.
Accurate risk stratification is crucial for optimizing post-operative follow-up (FU) and patient management.
Current FU strategies may not adequately differentiate risk levels, potentially leading to overtreatment or undertreatment.

Purpose of the Study:

To develop and validate a data-driven model for risk-stratifying patients post-RC.
To identify patients at high risk of recurrence following bladder cancer treatment.
To propose a risk-adapted follow-up schedule based on the developed model.

Main Methods:

Retrospective analysis of 3196 patients with cT2-T4 N0M0 bladder cancer undergoing RC across 16 European centers.
Classification and Regression Tree (CART) analysis incorporating pathological T stage, N stage, and lymphovascular invasion (LVI).
Landmark analysis to evaluate conditional risk of recurrence at 1, 2, 3, 4, and 5 years post-RC.

Main Results:

A high-risk group (pT3-4, node-positive, or pT2 with LVI) demonstrated significantly worse 5-year recurrence-free survival (RFS) (37.8% vs. 76.2%).
The model strongly predicted recurrence (HR 4.29), cancer-specific survival (sHR 5.80), and overall survival (HR 3.04).
Elevated recurrence risk persisted up to 4 years, with risk convergence observed after 5 years in event-free patients.

Conclusions:

A simple, pathology-based model (pT3-4/pN+/pT2+LVI) effectively stratifies patients after RC.
This model facilitates the implementation of a risk-adapted follow-up strategy.
Prospective validation is needed to confirm clinical utility, safety, and cost-effectiveness.