Work

Development and multicenter validation of a predictive model for malignant pleural effusion recurrence

Year: 2026

Type: article

Abstract: Early prediction of malignant pleural effusion (MPE) recurrence within 3 months is essential for optimizing management in lung cancer patients. This study developed and validated a machine learning model to estimate the 3-month recurrence risk of MPE in patients with newly diagnosed lung cancer. Using data from 221 patients for model training and 237 from two external validation cohorts, the Elastic Net model-based solely on four routine clinical features (treatment regimen, alanine aminotransferase, total pleural effusion volume, and tumor diameter)-achieved excellent performance, with areas under the curve of 0.848 and 0.940 in external validation. The model significantly outperformed other machine learning approaches. An interactive risk stratification tool was further developed to classify patients into four risk groups, enabling early identification and individualized management of high-risk patients. This tool offers a practical and generalizable solution for guiding clinical decision-making.

Source: iScience

DOI: 10.1016/j.isci.2026.115040

Authors: Xin Hu, Yongjie Jiang, Yiluo Heibi, Li Jiang, Yuying Li

Institutions: Southwest Medical University, Affiliated Hospital of Southwest Medical University, Third People's Hospital of Chengdu, Affiliated Hospital of North Sichuan Medical College

Language: English

Topic: Pleural and Pulmonary Diseases

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,240