Can We Go beyond Pathology? The Prognostic Role of Risk Scoring Tools for Cancer-Specific Survival of Patients with Bladder Cancer Undergoing Radical Cystectomy

Author:

Ślusarczyk Aleksander1ORCID,Wolański Rafał1ORCID,Miłow Jerzy2ORCID,Piekarczyk Hanna1,Lipiński Piotr2,Zapała Piotr1,Niemczyk Grzegorz1,Kurzyna Paweł1ORCID,Wróbel Andrzej3ORCID,Różański Waldemar2,Radziszewski Piotr1,Zapała Łukasz1ORCID

Affiliation:

1. Department of General, Oncological and Functional Urology, Medical University of Warsaw, 02-091 Warsaw, Poland

2. 2nd Clinic of Urology, Medical University of Lodz, 93-513 Łódź, Poland

3. Second Department of Gynecology, Medical University of Lublin, Jaczewskiego 8, 20-090 Lublin, Poland

Abstract

Radical cystectomy (RC) remains a mainstay surgical treatment for non-metastatic muscle-invasive and BCG-unresponsive bladder cancer. Various perioperative scoring tools assess comorbidity burden, complication risks, and cancer-specific mortality (CSM) risk. We investigated the prognostic value of these scores in patients who underwent RC between 2015 and 2021. Cox proportional hazards were used in survival analyses. Risk models’ accuracy was assessed with the concordance index (C-index) and area under the curve. Among 215 included RC patients, 63 (29.3%) died, including 53 (24.7%) cancer-specific deaths, with a median follow-up of 39 months. The AJCC system, COBRA score, and Charlson comorbidity index (CCI) predicted CSM with low accuracy (C-index: 0.66, 0.65; 0.59, respectively). Multivariable Cox regression identified the AJCC system and CCI > 5 as significant CSM predictors. Additional factors included the extent of lymph node dissection, histology, smoking, presence of concomitant CIS, and neutrophil-to-lymphocyte ratio, and model accuracy was high (C-index: 0.80). The internal validation of the model with bootstrap samples revealed its slight optimism of 0.06. In conclusion, the accuracy of the AJCC staging system in the prediction of CSM is low and can be improved with the inclusion of other pathological data, CCI, smoking history and inflammatory indices.

Publisher

MDPI AG

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