Predicting Recurrence and Progression in Patients with Non-Muscle-Invasive Bladder Cancer: Systematic Review on the Performance of Risk Stratification Models
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View abstract on PubMed
Summary
This summary is machine-generated.Current risk stratification for non-muscle-invasive bladder cancer (NMIBC) shows poor accuracy for predicting recurrence. New models combining clinical and molecular data are needed for better patient management.
Area Of Science
- Urology
- Oncology
- Medical Informatics
Background
- Non-muscle-invasive bladder cancer (NMIBC) requires accurate risk stratification to predict recurrence and progression.
- Several classification systems exist, but their clinical utility is debated.
Purpose Of The Study
- To systematically review the evidence on risk stratification models for NMIBC.
- To assess the performance and limitations of current NMIBC risk stratification tools.
Main Methods
- Systematic review adhering to PRISMA guidelines.
- Inclusion of studies developing or validating NMIBC risk stratification models.
- Analysis of discrimination measures (AUC, C-Index) for recurrence and progression.
Main Results
- Twenty-five studies with 22,737 patients were analyzed, identifying six classifications (three predictive, three expert-based).
- High risk of bias and heterogeneity were noted across studies; oncological outcomes were inconsistently defined.
- EORTC and CUETO systems are most validated, but generally show poor discrimination for recurrence and only moderate for progression.
Conclusions
- Existing NMIBC risk classifications have limited accuracy, particularly for predicting recurrence.
- There is a significant unmet need for novel, more accurate risk models for NMIBC.
- Future models should integrate clinicopathological and molecular data for improved risk prediction.
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