A research team from China has developed and validated a novel nomogram to predict extraurothelial recurrence (EUR) after radical nephroureterectomy (RNU) in patients with upper urinary tract urothelial carcinoma (UTUC).
Nomogram models were developed to predict EUR-free survival (EURFS) using independent risk factors. The least absolute shrinkage and selection operator (LASSO) was used to determine variables for multivariable Cox regression. Nomogram validation was performed using the concordance index (C-index), calibration plots, time-dependent receiver-operator characteristics curve, and decision curve analysis (DCA).
A group of 521 patients with UTUC who underwent RNU were retrospectively studied, and their data were used in a training cohort (n=301) and an external validation cohort (n=220). Patients were placed into 3 risk groups based on their total points as calculated by the nomograms researchers had developed. Kaplan-Meier analysis was used to determine the difference in EURFS of each group.
Four variables were screened through LASSO regression: bladder cancer history, Ki-67, lymphovascular invasion, and pathological T stage. Each variable was shown to be an independent predictive factor for EUR. In both the training and validation cohorts, the C-index of the model was 0.793. When compared with prediction based on categorized pathological T stage, the DCA curves for 5-year EUR showed better performance. The 5-year EURFS rates were 92.2%, 63.8%, and 36.2% in patients stratified to the low-, medium-, and high-risk groups, respectively.
The novel nomogram demonstrated accurate prediction for the probability of EUR in patients with UTUC, as well as perfect performance in discrimination ability and clinical net benefit. This model may be utilized by urologists to help determine proper treatment and monitoring for patients.