Developing and validating a nomogram of suicide risk in lung cancer patients based on the SEER database.

ABSTRACT:

Purpose

This study sought to determine independent predictors of suicide among patients with lung cancer and to establish a dynamic nomogram to predict suicide risk, with the ultimate goal of enabling early recognition and prevention in high-risk populations.

Methods

We analyzed 188,147 lung cancer cases from the most recent Surveillance, Epidemiology, and End Results (SEER) database (2004-2015) to identify predictors of suicide risk and develop a predictive model. The cohort was randomized into a training and validation group. Validation consisted of assessing the consistency index (C-index), subject-operating characteristic curves (ROC), and calibration curves.

Results

A total of 188,147 eligible lung cancer patients were enrolled and randomized into the training an

SUBMITTER: Li W 

PROVIDER: S-EPMC12824074 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature