Development and external validation of a FISH-clinical nomogram for predicting overall survival in bladder cancer patients after radical cystectomy.

BACKGROUND: Bladder cancer has notable heterogeneity. The urine-based fluorescence in situ hybridization (FISH) test can detect bladder cancer noninvasively. In this study, we aimed to construct a nomogram based on FISH results and clinical features (referred to as the FISH-clinical model) to predict the overall survival (OS) of bladder cancer patients following radical cystectomy (RC). METHODS: A total of 261 eligible patients were enrolled for this study. The SYSMH cohort was divided into training (n = 138) and internal validation (n = 70) sets; the SYSUTH cohort was used for external validation (n = 53). Multivariate Cox proportional hazards regression was applied for FISH-clinical model construction, and model performance was evaluated according to analyses of calibration, discrimination ability, and clinical usefulness. RESULTS: FISH-identified chromosome 7 and 17 aneuploidies correlated significantly with increased pT stage; the former was associated with lymph node metastasis. Six variables, age, tumor size, pT stage, lymphovascular invasion, chromosome 7 aneuploidy, and p16 locus loss, were found to be independent predictors of OS and were incorporated into our FISH-clinical model. The model demonstrated good calibration and discrimination, with C-indexes (95% CIs) of 0.772 (0.693-0.851), 0.712 (0.605-0.819) and 0.705 (0.587-0.822), in the training, internal validation and external validation sets respectively. Decision curve analysis demonstrated the model's clinical utility. Furthermore, all enrolled patients were successfully categorized into high-, medium- or low-risk groups, and stratified analyses were performed. CONCLUSIONS: Preoperative FISH has predictive value for OS, and we developed a FISH-clinical model for OS prediction in bladder cancer patients who have not received neoadjuvant chemotherapy or immunotherapy. This model showed favorable predictive efficacy with internal and external validation.