Tumor size predicts metastatic disease at diagnosis and prognosis in unilateral Wilms tumor a population-based study with external validation
摘要
The impact of tumor size on prognosis, metastasis, and treatment response in Wilms tumor (WT) remains incompletely understood. This study aimed to elucidate the influence of tumor size on survival, metastatic risk, and the efficacy of radiotherapy and chemotherapy in WT patients.
MethodsWe analyzed WT patients in the Surveillance, Epidemiology, and End Results (SEER) program (2000–2022) and from our institution’s electronic medical records (2013–2024). Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Prognostic factors were identified via univariate and multivariate Cox proportional hazards models, and propensity score matching (PSM) was used to balance baseline characteristics.
ResultsA total of 1916 patients from the SEER cohort and 237 patients from our institutional cohort with WT were included in this study. In the SEER cohort, patients with tumor size > 10.4 cm had significantly worse survival compared to those with tumors ≤ 10.4 cm. Restricted cubic spline (RCS) analysis revealed linear associations between tumor size and patient outcomes for overall survival (OS) (p overall = 0.011, p nonlinear = 0.906) and cancer-specific survival (CSS) (p overall = 0.010, p nonlinear = 0.998). Multivariate analysis confirmed that larger tumor size was an independent risk factor for poorer OS (HR = 1.79, p = 0.011). The metastasis rate was significantly lower in the small tumor group than in the large tumor group (87/762 vs. 187/880, p < 0.001). Among all patients who received chemotherapy, those with larger tumors had worse prognosis, particularly in the distant metastasis stage, showing a 9.8% reduction in 5-year OS. These findings were consistently validated using our institutional dataset.
ConclusionLarger tumor size is associated with higher metastatic risk and unfavorable prognosis in WT. This highlights its potential value as a practical supplementary indicator for risk stratification and clinical decision-making, particularly in resource-limited settings.