Combination of Naples prognostic score and pathological factors for evaluating the long-term prognosis of patients with late-onset colorectal cancer: a multicenter machine learning study.

ABSTRACT:

Background

Given the increasingly aging population, precise prognostic models are essential for optimizing postoperative care in patients with late-onset colorectal cancer (LOCRC). Inflammatory, immune, and nutritional factors, along with the Naples prognostic score (NPS), platelet-to-lymphocyte ratio (PLR), and clinicopathological variables, are emerging as predictors of postoperative outcomes in patients with LOCRC. In order to overcome traditional statistical limitations in prognosis, this study aimed to evaluate NPS, PLR, and clinicopathological variables as prognostic factors for LOCRC and incorporate them into a machine learning (ML) model for LOCRC prognosis.

Methods

The data from 1,588 patients with postoperative LOCRC and aged ≥50 years were retrospectively collecte

SUBMITTER: Alburiahi TAH 

PROVIDER: S-EPMC12776133 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature