Predictive significance of the hemoglobin, albumin, lymphocyte, and platelet score for radiation pneumonitis in lung cancer patients: a respective comparative study with dosimetric parameters.

INTRODUCTION

Inflammatory response and nutritional status have been linked to adverse reactions of radiotherapy. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score, associated with both inflammation and nutrition, can effectively predict prognosis in various cancers. However, its role in predicting radiation pneumonitis (RP) among radiotherapy patients remains unclear, and further investigation is needed to elucidate it.

METHODS

The general clinical data of lung cancer patients who underwent radiotherapy between January 2021 and October 2024 were retrospectively collected. RP was graded in accordance with the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Predictive factors for RP were identified using LASSO and multivariate logistic regression analyses, and a nomogram was subsequently developed based on these factors. The predictive performance of the nomogram was comprehensively evaluated using the area under the receiver operating characteristic (AUROC) analyses, calibration curve, and decision curve analysis.

RESULTS

A total of 396 patients' data were analyzed (development cohort: 301; temporal validation cohort: 95). Multivariate logistic analysis revealed that the HALP score and lung volume receiving ≥5 Gy (V5) were independent predictors of symptomatic RP, and regarding severe RP were HALP, V5, albumin, and hemoglobin. The AUROC values of the HALP score were 0.77 (95% CI: 0.72-0.83) and 0.83 (95% CI: 0.76-0.90) for predicting symptomatic and severe RP. The integrated HALP-V5 model exhibited excellent predictive ability both in symptomatic RP (AUROC: 0.84; 95% CI: 0.79-0.89) and severe RP (AUROC: 0.89; 95% CI: 0.83-0.94), with high predictive accuracy and clinical utility.

CONCLUSION

HALP can be employed as a promising independent predictor of RP in lung cancer patients undergoing radiotherapy, and the combination of V5 can further improve prediction accuracy.