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A Risk-Scoring Model for Severe Checkpoint Inhibitor-Related Pneumonitis: A Case-Control Study
Haiyi Deng1, Jiating Deng2, Xinqing Lin1
1Pulmonary and Critical Care Medicine, Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, The First Affiliated Hospital of Guangzhou Medical University, 151# Yanjiang Road, Guangzhou, 510120, China.
Background And Objective:
Checkpoint inhibitor-related pneumonitis (CIP) is one of the most common serious and fatal adverse events associated with immune checkpoint inhibitors (ICIs). The study sought to identify risk factors of all-grade and severe CIP and to construct a risk-scoring model specifically for severe CIP.
Methods:
This observational, retrospective case-control study involved 666 lung cancer patients who received ICIs between April 2018 and March 2021. The study analyzed patient demographic, preexisting lung diseases, and the characteristics and treatment of lung cancer to determine the risk factors for all-grade and severe CIP. A risk score for severe CIP was developed and validated in a separate patient cohort of 187 patients.
Results:
Among 666 patients, 95 patients were afflicted with CIP, of which 37 were severe cases. Multivariate analysis revealed age ≥ 65 years, current smoking, chronic obstructive pulmonary disease, squamous cell carcinoma, prior thoracic radiotherapy, and extra-thoracic radiotherapy during ICI were independently associated with CIP events. Five factors, emphysema (odds ratio [OR] 2.87), interstitial lung disease (OR 4.76), pleural effusion (OR 3.00), history of radiotherapy during ICI (OR 4.30), and single-agent immunotherapy (OR 2.44) were independently associated with severe CIP and were incorporated into a risk-score model (score ranging 0-17). The area under the model receiver operating characteristic curve for the model was 0.769 in the development cohort and 0.749 in the validation cohort.
Conclusions:
The simple risk-scoring model may predict severe CIP in lung cancer patients receiving ICIs. For patients with high scores, clinicians should use ICIs with caution or strengthen the monitoring of these patients.
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