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

Abstract

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.

Keywords: Bladder cancer; Fluorescence in situ hybridization; Nomogram; Overall survival; Radical cystectomy.

Fig. 1

The flowchart of the study

Fig. 2

Distribution of FISH results across the whole cohort.(A) Pie plots illustrating the status of the four FISH sites. (B) UpSet plot showing the distribution of different combinations of FISH-positive sites. The horizontal axis represents different combinations of FISH-positive sites. The vertical axis shows the patient number for each combination. FISH: fluorescence in situ hybridization analysis; CSP: chromosome-specific centromeric probe; GLP: gene locus-specific probe

Fig. 3

Correlations of the FISH assay results with the pT stage in the whole cohort. (A-D) Bar plots showing the correlations between the four FISH sites status and pT stage. (E) Bar plots showing the correlation between the FISH test result and pT stage. (F) Bar plots showing the distribution of the number of positive FISH sites in bladder cancer patients with different pT stages. FISH: fluorescence in situ hybridization analysis; CSP: chromosome-specific centromeric probe; GLP: gene locus-specific probe

Fig. 4

Correlations of the FISH assay results with pN stage and LVI status. (A) Bar plots showing the correlations between the FISH assay results and pN stage. (B) Bar plots showing the correlations between the FISH assay results and LVI status. FISH: fluorescence in situ hybridization analysis; CSP: chromosome-specific centromeric probe; GLP: gene locus-specific probe; LNM: lymph node metastasis; LVI: lymphovascular invasion

Fig. 5

The FISH–clinical nomogram for OS prediction. The FISH–clinical nomogram was developed to predict the 1-year, 2-year, and 3-year OS of bladder cancer patients who underwent RC. CSP: chromosome-specific centromeric probe; GLP: gene locus‐specific probe; LVI: lymphovascular invasion; OS: overall survival; RC: radical cystectomy

Fig. 6

Calibration curve analysis and DCA of the FISH–clinical model. (A-C) Calibration curves of the FISH–clinical model in the training, internal validation, and external validation sets. The 45-degree gray line represents perfect prediction. The broken line represents the model prediction, which has a closer fit to the gray line, indicating a better prediction. (D-F) DCA results of the FISH–clinical model in the training, internal validation, and external validation sets. The x-axis shows the threshold probability. The y-axis represents the net benefit, which is calculated across a range of threshold probabilities. The black and gray lines represent the hypothesis that no patients or all patients died, respectively. The solid red line represents the FISH–clinical model

Fig. 7

Kaplan‒Meier survival curves for patients in the high-, moderate-, and low-risk groups. Kaplan‒Meier survival curves indicating significant differences in OS among patients in the high-, moderate-, and low-risk groups in the training set (A), the internal validation set (B), the external validation set (C), and the whole cohort (D)