Establishment and validation of a nomogram to predict overall survival for patients with primary renal neuroendocrine tumor

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-04-22
DOI
https://doi.org/10.1038/s41598-025-98228-0
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Establishment and validation of a nomogram to predict overall survival for patients with primary renal neuroendocrine tumor

Hua Yang, Qicheng Long, Yajun Fu, Xiaoke Chen et al.
2 links
Scientific Reports
Renal cell carcinoma treatment
article

Establishment and validation of a nomogram to predict overall survival for patients with primary renal neuroendocrine tumor

Hua Yang, Qicheng Long, Yajun Fu, Xiaoke Chen, Yang Wang, Wen-Hui Luo, Yanlin Zhu
article en

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.

Scientific ReportsVol. 15(1)
Hubei University of Medicine (CN), Zhuhai People's Hospital (CN), Guangdong Provincial People's Hospital (CN)
Openalex Percentile: Top 87%
Renal cell carcinoma treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.