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Updated: Jan 6, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and external validation of a FISH-clinical nomogram for predicting overall survival in bladder cancer
Junjiong Zheng1, Sihong Lu2, Qihang Zhang1
1Department of Urology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong Provincial Clinical Research Center for Urological Diseases, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China.
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.
