Unveiling prognostic factors and predictive modeling in lung adenocarcinoma with neuroendocrine differentiation.

ABSTRACT:

Background

Some lung cancer patients are pathologically confirmed to have lung adenocarcinoma with neuroendocrine differentiation (LUAD-ND). However, research on this subtype remains limited. This study aimed to systematically investigate the metastatic patterns and prognosis-related factors of LUAD-ND, and construct neural network-based prediction models for survival outcomes.

Methods

By analyzing the Surveillance, Epidemiology, and End Results (SEER) database, we employed the Cox proportional hazards model to investigate prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in patients with LUAD-ND. We calculated hazard ratios (HRs) and 95% confidence intervals (CIs) and detailed the median survival time and specific time survival probabilities fo

SUBMITTER: Li W 

PROVIDER: S-EPMC12432600 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature