Mortality prediction models after radical cystectomy for bladder tumour: A systematic review and critical appraisal

• Published in: European journal of clinical investigation Vol. 52; no. 10; pp. e13822 - n/a
• Main Authors: Sarrió‐Sanz, Pau, Martinez‐Cayuelas, Laura, Lumbreras, Blanca, Sánchez‐Caballero, Laura, Palazón‐Bru, Antonio, Gil‐Guillén, Vicente F., Gómez‐Pérez, Luis
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01-10-2022
• Subjects: Bias; Bladder; Cancer; Chemotherapy; Content analysis; Feasibility studies; Literature reviews; Mortality; nomograms; Patients; Prediction models; radical cystectomy; Risk analysis; Risk assessment; Systematic review; Tumors; urinary bladder neoplasms; mortality; models; radical cystectomy; urinary bladder neoplasms; nomograms
• ISSN: 0014-2972; 1365-2362
• DOI: 10.1111/eci.13822

Introduction
To identify risk‐predictive models for bladder‐specific cancer mortality in patients undergoing radical cystectomy and assess their clinical utility and risk of bias.
Methods
Systematic review (CRD42021224626:PROSPERO) in Medline and EMBASE (from their creation until 31/10/2021) was screened to include articles focused on the development and internal validation of a predictive model of specific cancer mortality in patients undergoing radical cystectomy. CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) were applied.
Results
Nineteen observational studies were included. The main predictors were sociodemographic variables, such as age (18 studies, 94.7%) and sex (17, 89.5% studies), tumour characteristics (TNM stage (18 studies, 94.7%), histological subtype/grade (15 studies, 78.9%), lymphovascular invasion (10 studies, 52.6%) and treatment with chemotherapy (13 studies, 68.4%). C‐index values were presented in 14 studies. The overall risk of bias assessed using PROBAST led to 100% of studies being classified as high risk (the analysis domain was rated to be at high risk of bias in all the studies), and 52.6% showed low applicability. Only 5 studies (26.3%) included an external validation and 2 (10.5%) included a prospective study design.
Conclusions
Using clinical predictors to assess the risk of bladder‐specific cancer mortality is a feasibility alternative. However, the studies showed a high risk of bias and their applicability is uncertain. Studies should improve the conducting and reporting, and subsequent external validation studies should be developed.