Predicting Severe Radiation Pneumonitis in Patients With Locally-Advanced Non–Small-Cell Lung Cancer After Thoracic Radiotherapy: Development and Validation of a Nomogram Based on the Clinical, Hematological, and Dose-Volume Histogram Parameters

Abstract

Purpose

This study aimed to investigate the risk factors for severe radiation pneumonitis (RP) after thoracic radiotherapy (RT) in patients with locally advanced non-small cell lung cancer (NSCLC), develop a prediction model to identify high-risk groups, and investigate the impact of severe RP on overall survival (OS).

Methods

We retrospectively collected clinical, dosimetric, and hematological factors of patients with stage III NSCLC receiving thoracic RT without immunotherapy. The primary and secondary end points were severe RP and OS, respectively. Fine-Gray competing risk regression analyses were used to identify the risk factors for severe RP. The patients were randomly divided into training and validation cohorts at a ratio of 6:4. The model was evaluated using receiver operating characteristic (ROC) and calibration curves, and decision curve analysis (DCA). The OS of patients in the RP vs. non-RP and mild RP vs. severe RP groups was analyzed using the Kaplan-Meier method.

Results

A total of 305 patients were enrolled in the analysis, and 32 (10.5%) developed severe RP. Interstitial lung disease (ILD) (P = .013), percentage of ipsilateral lung volume receiving ≥ 20 Gy (ipsilateral V₂₀) (P = .029), pre-RT derived neutrophil lymphocyte ratio (dNLR) (P = .026), and post-RT systemic inflammation response index (SIRI) (P = .010) were independent predictors of severe RP, and were used to establish the nomogram based on a training cohort. The ROC area under the curve (AUC) of the nomogram was 0.804. Calibration curves and DCA showed favorable consistency and positive net benefits in both training and validation cohorts. Cases who developed severe RP had a shorter OS than those who developed mild RP (P = .027).

Conclusion

ILD, ipsilateral V₂₀, pre-RT dNLR, and post-RT SIRI could predict severe RP in patients with locally advanced NSCLC receiving thoracic RT. By combining these indicators, a nomogram was constructed and validated, demonstrating its potential value in clinical practice.