Integrated machine learning risk model for predicting radiation pneumonitis in lung cancer patients with interstitial lung disease
The integrated nomogram combining clinical, dosimetric, and inflammatory predictors enables accurate, individualized RP risk assessment in lung cancer patients with ILD. It can guide adjustments to individualized radiotherapy plans or preventive interventions, supporting better patient selection, treatment decisions, and proactive follow-up.
Authors
- Haozheng Lu
- Aimin Jiang
- Zhaoqi Yuan
- Dawei Chen
Institutions
- Academy of Medical Sciences (GB)
- Shandong Tumor Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1080/07853890.2026.2634444
- Primary Topic
- Effects of Radiation Exposure
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Natural Science Foundation of Shandong Province
- National Science and Technology Major Project