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A Risk-Scoring Model for Severe Checkpoint Inhibitor-Related Pneumonitis: A Case–Control Study

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Abstract

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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Author notes

  1. Haiyi Deng, Jiating Deng and Xinqing Lin contributed equally to this work.

Authors and Affiliations

  1. Pulmonary 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

    Haiyi Deng, Xinqing Lin, Wenhui Guan, Yilin Yang, Jianhui Wu, Guihuan Qiu, Ni Sun, Maolin Zhou, Jiaxi Deng, Xiaohong Xie, Zhanhong Xie, Ming Liu, Yinyin Qin & Chengzhi Zhou

  2. Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Jiating Deng, Ziying Lin, Yanli Qiu & Yanbin Zhou

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  1. Haiyi Deng
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Corresponding authors

Correspondence to Yanbin Zhou or Chengzhi Zhou.

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Funding

This work was supported by the National Key R&D Program of China (Grant number: 2021YFC2301101), State Key Laboratory of Respiratory Disease-The open project (Grant number: SKLRD-OP-202011, SKLRD-OP-202111), the Fundamental and Applied Fundamental Research Project of City-School (Institute) Joint Funding Project, Guangzhou Science and Technology Bureau (Grant number: 202102010186), and Beijing Xisike Clinical Oncology Research Foundation (Grant number: Y-HS202102-0118).

Conflict of interest

The authors report no conflict of interest.

Ethics approval

Approval was granted by the Ethics Committee of The First Affiliated Hospital of Guangzhou Medical University.

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Informed consent was obtained from all individual participants included in the study.

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Author contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by HD, JD, XL, WG, ZL, YQ, YY, JW, GQ, NS, and MZ. The first draft of the manuscript was written by HD and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Deng, H., Deng, J., Lin, X. et al. A Risk-Scoring Model for Severe Checkpoint Inhibitor-Related Pneumonitis: A Case–Control Study. Clin Drug Investig 43, 347–357 (2023). https://doi.org/10.1007/s40261-023-01267-6

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