ArticleBMC urology2026
A dynamic nomogram and risk classification for predicting prognosis in renal cell carcinoma with venous tumor thrombus.
Article in BMC urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTo establish an effective dynamic nomogram and a novel risk classification system to predict overall survival (OS) for Renal Cell Carcinoma with venous tumor thrombus (RCC-VTT).
methods318 patients were enrolled and randomly divided into a training set and a validation set in a 7:3 ratio. LASSO regression analysis and multivariate Cox regression analysis were employed to identify significant prognostic factors. Based on these factors, a nomogram model was developed and evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). Survival differences were assessed using Kaplan-Meier curves and the log-rank test.
resultsEight survival predictors were identified: Mayo Clinic Stage, Histology, N Stage, M Stage, Renal Sinus Invasion, Sarcomatoid Feature, Hemoglobin, and Estimated Glomerular Filtration Rate. The C-indexes for the training and validation sets were 0.77 (95% CI: 0.72-0.82) and 0.75 (95% CI: 0.68-0.82), respectively. The AUCs for the training and validation sets were 0.869 (95% CI: 0.805-0.933) and 0.854 (95% CI: 0.770-0.937) for the 5-yr predictions, respectively. DCA further confirmed the clinical utility of the model. Additionally, the nomogram-based classification system stratified patients into distinct risk subgroups for OS (P < 0.0001).
conclusionsWe developed a dynamic nomogram and novel risk classification system for RCC-VTT. This tool has the potential to personalize treatment strategies.
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