Prediction of STAS in lung adenocarcinoma with nodules ≤ 2 cm using machine learning: a multicenter retrospective study.

ABSTRACT:

Background and objective

Spread through air spaces (STAS) is an important factor in determining the aggressiveness and recurrence risk of lung cancer, especially in early-stage adenocarcinoma. Preoperative identification of STAS is crucial for optimizing surgical strategies. This study aimed to develop and validate machine learning models to predict the presence of STAS using preoperative clinical, radiological, and pathological data in lung cancer patients.

Patients and methods

A retrospective analysis was conducted on 1,290 lung cancer patients from two hospitals: Qilu Hospital of Shandong University and Qianfoshan Hospital. Data from 1,174 patients from Qilu Hospital were used for model training and internal validation, while 116 patients from Qianfoshan Hospital were use

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC11887330 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature