A nomogram to predict development of brain metastasis in non-small cell lung cancer patients: a retrospective analysis using routinely available medical records.

ABSTRACT:

Background

Brain metastases (BrM) are a frequent complication among patients with non-small cell lung cancer (NSCLC). While guidelines exist for baseline CNS screening in advanced NSCLC, surveillance strategies for early-stage disease remain limited. This study aimed to develop a time-dependent BrM risk prediction nomogram using readily available clinical information.

Methods

We analyzed a retrospective cohort of NSCLC patients at Penn State Health. Our objectives were to (1) systematically evaluate the performance of existing BrM risk prediction algorithms and (2) construct novel nomograms for BrM risk prediction in NSCLC. Using Cox-proportional hazard models with L1-regularization, we predicted BrM risk at 6-month, 1-year, and 2-year follow-up intervals.

Findings

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SUBMITTER: Wilding H 

PROVIDER: S-EPMC12418891 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature