Development and validation of prognostic models for bone metastasis in Non-Small cell lung cancer based on Machine learning algorithms.

ABSTRACT:

Background

Bone is a common site of metastasis in non-small cell lung cancer (NSCLC), yet no validated prognostic model is currently available for patients presenting with bone metastases at diagnosis.

Methods

We retrospectively reviewed 1,299 NSCLC patients who underwent high-throughput sequencing between 2016 and 2023. Of these, 195 were diagnosed with bone metastases at presentation. Three machine learning algorithms were applied to identify prognostic variables. A nomogram constructed with Cox regression was used to predict overall survival (OS) and was internally validated with 1,000 bootstrap resamples.

Results

Four independent prognostic factors were identified, including age, serum calcium, monocyte-to-albumin ratio, and prognostic nutritional index. The nomog

SUBMITTER: Fang J 

PROVIDER: S-EPMC12538467 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature