Analysis of prognostic factors and development of a predictive model following radical nephrectomy for Wilms tumor in children

Wilms tumor (WT) is a common pediatric renal malignancy that poses significant challenges in clinical management and prognosis. The aim of the present study was to identify prognostic factors affecting outcomes in pediatric patients with WT following radical nephrectomy, to stratify high-risk groups for recurrence, and to develop a predictive model to support clinical decision-making and research in Chinese pediatric WT populations. The present retrospective, single-center study included clinical data from 180 pediatric patients with WT who underwent radical nephrectomy at the Baoding Branch of Beijing Children's Hospital (Baoding, China) between January 2015 and January 2019. Univariate and multivariate analyses were performed to identify prognostic factors, and a prediction model was constructed and validated. Progression-free survival (PFS) and overall survival (OS) were analyzed for all patients. The final follow-up was in July 2024. The results demonstrated that the 5-year OS and PFS rates were 99.6 and 94.3%, respectively. The median OS was 76.9 months (range, 30-101 months) and the median PFS was 75.5 months (range, 29-101 months). During follow-up, 25 patients experienced recurrence and 16 died. Univariate analysis revealed that clinical stage, histological subtype and tumor thrombus were significantly associated with prognosis (P<0.05). Multivariate Cox regression analysis identified advanced clinical stage [stage III-IV; hazard ratio (HR), 4.151; 95% confidence interval (CI), 1.440-11.922; P=0.009] and unfavorable histology (HR, 3.842; 95% CI, 1.592-9.283; P=0.002) as independent prognostic factors. A predictive model incorporating these two variables was established, yielding an area under the receiver operating characteristic curve of 0.755 (95% CI, 0.685-0.816; P<0.001). In conclusion, clinical stage and histological subtype are independent predictors of prognosis in children with WT after radical surgery. A predictive model based on these factors may help estimate individual prognosis and guide clinical management strategies.