Development and validation of a prediction model for the prognosis of renal cell carcinoma with liver metastases: a population-based cohort study.

ABSTRACT:

Background

Current studies on the establishment of prognostic model for renal cell carcinoma (RCC) with liver metastases (LM) were scarce. This study aimed to develop nomograms to predict the prognosis of RCC with LM.

Methods

Patients diagnosed with RCC between 2010 and 2021 from the Surveillance, Epidemiology, and End Results (SEER) database were selected. The eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) machine learning algorithms were used to screen for the most influential factors affecting prognosis, and the Venn diagram method was employed for further refinement. Subsequently, a nomogram related to brain metastases was constructed. The performance of the nomograms was evaluated through receiver operating characteristics (ROC) curves, calibration plots, C-

SUBMITTER: Wang F 

PROVIDER: S-EPMC11649420 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature