Can We Go beyond Pathology? The Prognostic Role of Risk Scoring Tools for Cancer-Specific Survival of Patients with Bladder Cancer Undergoing Radical Cystectomy
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View abstract on PubMed
Summary
This summary is machine-generated.The AJCC staging system has low accuracy for predicting cancer-specific mortality after radical cystectomy (RC). Improved prediction models incorporate pathological data, comorbidity index, smoking history, and inflammatory markers.
Area Of Science
- Urology
- Surgical Oncology
- Oncology
Background
- Radical cystectomy (RC) is a primary treatment for muscle-invasive and BCG-unresponsive bladder cancer.
- Perioperative scoring tools are used to assess patient risk and outcomes.
- Prognostic value of existing scores for cancer-specific mortality (CSM) after RC requires further investigation.
Purpose Of The Study
- To evaluate the prognostic accuracy of established scoring systems for CSM in RC patients.
- To identify additional predictors of CSM to improve risk stratification.
Main Methods
- Retrospective analysis of 215 patients undergoing RC (2015-2021).
- Survival analysis using Cox proportional hazards models.
- Accuracy assessed via concordance index (C-index) and area under the curve (AUC).
Main Results
- Existing scores (AJCC, COBRA, CCI) showed low accuracy in predicting CSM (C-indices: 0.66, 0.65, 0.59).
- AJCC staging and Charlson Comorbidity Index (CCI) > 5 were significant CSM predictors.
- A multivariable model including pathological data, CCI, smoking, and neutrophil-to-lymphocyte ratio achieved high accuracy (C-index: 0.80).
Conclusions
- The AJCC staging system alone has limited accuracy for predicting CSM post-RC.
- Integrating pathological details, comorbidity index, smoking status, and inflammatory markers significantly enhances CSM prediction accuracy.
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