The following is a summary of “Development and validation of a prognostic nomogram for overall and disease-specific survival in patients with sarcomatoid urothelial carcinoma,” published in the June 2023 issue of the Urologic Oncology by Diamantopoulos et al.

Sarcomatoid urothelial carcinoma (SUC) is an uncommon, aggressive variant of bladder cancer for which prognostic information is limited. In this study, researchers present the first prognostic nomograms for 3- and 5-year overall survival (OS) and disease-specific survival (DSS) derived from the surveillance, epidemiology, and results database (SEER) for patients with SUC. Patients with SUC were identified using the ICD-10 topography codes C67.0-C67.9 (bladder cancer) and the morphologic code 8,122 (SUC). Patients were randomized into a training cohort (TC) and a validation cohort (VC) in a ratio of 7:3. Using multivariate Cox regression, variables substantially associated with OS and DSS were identified and used to construct the nomograms. 

Internal and external validation utilized Harrel’s C-statistic with bootstrap resampling and calibration curves. With decision curve analysis (DCA), the clinical utility of the nomograms was evaluated. The likelihood ratio test evaluated the fit between the nomograms and the AJCC 8th edition staging system. A total of 741 SUC patients were included (507 TC and 234 VC). There were no statistically significant differences between the two cohorts’ baseline characteristics. Sex, SEER stage, radical cystectomy, and chemotherapy were variables shared by the OS and DSS nomograms, with age added to the former. The optimism-corrected C-statistic for the nomograms was 0.68 for OS and 0.67 for DSS. Comparatively, the AJCC’s C-statistics for OS and DSS were 0.59 and 0.60, respectively (P<0.001). 

The nomogram’s constructed calibration curves demonstrated appropriate congruence between predicted and actual survival. The nomograms exhibited optimal clinical utility in the DCA, outperforming the AJCC staging system by maintaining higher clinical net benefits than the treat all, treat none, and AJCC curves across threshold probabilities. They present the initial prognostic nomograms developed for SUC patients. Their models demonstrated superior predictive performance compared to the AJCC system, utilizing a set of variables readily available in clinical practice, and may be valuable tools for the individual risk assessment of these patients.

Source: sciencedirect.com/science/article/abs/pii/S1078143923000467