ArticleScientific reports2025
Establishment and validation of a nomogram to predict overall survival for patients with primary renal neuroendocrine tumor.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Whole-exome sequencing unveils novel potential gene mutations involved in primary renal small cell carcinoma.Oncology letters · 2026Article
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Authors and funding
7 authors.
Funding
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Abstract
Our study aimed to develop a nomogram to predict overall survival (OS) at 1, 3, and 5 years for patients with primary renal neuroendocrine tumor (PRNET). The Surveillance, Epidemiology, and End Results database (2000-2021) was utilized to gather cases and extract data. We performed a multivariate analysis using a Cox proportional-hazards model to identify prognostic factors independently affecting OS. Based on these predictors, a nomogram was constructed and validated internally via a bootstrap resampling method. Finally, we included 266 PRNET patients. The multivariate analysis demonstrated that age, Fuhrman grade, surgery, summary stage, N stage, and histology were prognostic factors independently affecting OS (all P < 0.05). A nomogram was then constructed using the abovementioned predictors, except for the N stage. The bootstrap-corrected concordance index (C-index) of the nomogram was 0.820 (95% CI 0.805-0.835), surpassing the C-index of the TNM stage (0.571, 95% CI 0.550-0.592, P < 0.001). Based on time-dependent C-index results, the nomogram demonstrated a better discriminative ability compared to the TNM staging system. There was a good consistency between the observed values and predicted probabilities indicated by the calibration curves. The nomogram's clinical utility was supported by the decision curve analysis. Additionally, the nomogram can classify PRNET patients into low-risk and high-risk subgroups, with high-risk patients having poorer OS (P < 0.0001). The prognostic nomogram, based on individualized clinicopathological information, may be helpful in predicting survival outcomes for PRNET patients more accurately. Further external validation is required in future studies to confirm our developed nomogram's prognostic accuracy and clinical applicability.
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