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October 12, 2025Scientific Reports2 citationsOpen Access

Prognostic risk factors and a survival prediction model for immune checkpoint inhibitor related myocarditis in patients with lung cancer: a multicenter study

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XCXiaoyun ChengLLLingzhi LongYLYuzhang Li

Key Points

  • The study developed a survival prediction model for lung cancer patients with immune checkpoint inhibitor-related myocarditis, highlighting significant contributing factors.
  • Cox regression identified protective factors like combined radiotherapy and longer ICI treatment duration as associated with lower all-cause death risk.
  • Risk factors for severe myocarditis included low-dose glucocorticoid use and angiogenesis inhibitors, underscoring the need for cautious management strategies.
  • The nomogram model demonstrated excellent predictive ability for survival, offering practical applications to guide clinical decisions for affected patients.

Abstract

Immune checkpoint inhibitor (ICI)-related myocarditis is a rare but fatal immune-related adverse event in lung cancer patients, with limited multivariate prognostic analysis. This study aimed to identify risk factors for severity, major adverse cardiac events (MACE) and survival time, and develop a survival prediction model. Data from 70 lung cancer patients with ICI-related myocarditis (training set) and 40 patients (validation set) were analyzed, with ≥ 1.5 years of follow-up. Cox regression was employed to determine factors associated with survival time, and Logistic regression models identified risk factors for severe myocarditis and MACE. Several factors were independently associated with all-cause death: protective factors included combined radiotherapy (HR 0.12, 95%CI: 0.01–0.98, p = 0.047) and longer ICI treatment duration (≥ 132 days, HR 0.93, 95%CI: 0.91–0.98, p = 0.013); risk factors included low-dose glucocorticoid use in patients with severe myocarditis (HR 3.92, 95%CI: 1.16–13.2, p = 0.028). A nomogram model constructed based on these three variables yielded area under the time-ROC curves of 0.832, 0.835, and 0.924 for 0.5-, 1-, and 1.5-year survival in the training set, and 0.821, 0.806, and 0.789 in the validation set, respectively. It also demonstrated good discriminative ability and clinical utility for predicting survival in lung cancer patients with ICI-related myocarditis, as this study established a validated nomogram model that may aid survival prediction in this population. Additionally, we analyzed the risk factors for severe ICI related myocarditis and 90-day MACE. We found that the use of angiogenesis inhibitors was an independent risk factor for severe myocarditis (OR 18.72, 95% CI: 2.52–428.27, p = 0.02); a history of coronary artery disease (OR 10.54, 95% CI: 1.62–210.10, p = 0.037) was an independent risk factor for 90-day MACE; and left ventricular ejection fraction (OR 0.94, 95% CI: 0.88–0.99, p = 0.026) was an independent protective factor against 90-day MACE.

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Cite This Study

Cheng et al. (2025) studied this question.

synapsesocial.com/papers/68ebc91af2c3e4d8d926e1d8https://doi.org/10.1038/s41598-025-19460-2
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