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Background <p>Immune checkpoint inhibitors (ICIs) have revolutionized treatment for advanced lung cancer, yet their cardiotoxicity, particularly immune checkpoint inhibitor-related myocarditis, poses significant clinical challenges. This study aims to create a predictive model using cardiac biomarkers to identify patients prone to myocarditis during treatment, thereby enhancing clinical decision-making and patient outcomes.</p> Methods <p>In this retrospective cohort study, 1,838 patients with locally advanced and metastatic lung cancer and abnormal baseline cardiac parameters receiving immunotherapy from June 2018 to August 2024 were analyzed, with a follow-up date cutoff of September 20, 2024. Patients were randomly divided into training (70%) and validation (30%) cohorts. Logistic regression analysis was conducted on demographic information, clinical characteristics, treatments, and cardiac parameters of these patients prior to immunotherapy. A nomogram was constructed via multivariable logistic regression, and AUC and Hosmer-Lemeshow tests were performed to verify the accuracy of the model.</p> Results <p>Among 1,838 patients, 89 (4.84%) developed myocarditis. Independent predictors included α-HBDH &gt; 910 U/L (OR = 10.57, 95%CI: 2.47–45.22, <i>P</i> = 0.001), CK-MB &gt; 15 ng/mL (OR = 3.87, 95%CI: 1.06–14.11, <i>P</i> = 0.040), hs-cTnT elevation (14–28 pg/mL: OR = 4.19; 28–42 pg/mL: OR = 13.10; &gt;42 pg/mL: OR = 25.43, <i>P</i> &lt; 0.001), NT-proBNP &gt; 3× age-adjusted upper limit (OR = 9.72, 95%CI: 1.09–86.73, <i>P</i> = 0.042), and Caprini score ≥ 4 (OR = 4.49, 95%CI: 2.26–8.90, <i>P</i> &lt; 0.001). The nomogram demonstrated strong discrimination ability, with an AUC of 0.831 in the training cohort (sensitivity: 0.842, specificity: 0.717) and an AUC of 0.844 in the validation cohort.</p> Conclusions <p>This study establishes a validated risk assessment model integrating cardiac biomarkers (α-HBDH, CK-MB, hs-cTnT, NT-proBNP) and Caprini risk score to predict ICI-related myocarditis in lung cancer patients with cardiac abnormalities. The tool facilitates early identification of high-risk patients, enabling tailored monitoring and preemptive management. These findings underscore the critical role of baseline cardiac profiling in optimizing immunotherapy safety.</p>

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Myocarditis prediction in locally advanced or metastatic lung cancer patients with cardiac parameters abnormalities undergoing immunotherapy: development and validation of a risk assessment model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月25日

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  • Shanshan Li,
  • Feng Du,
  • Yan Zhang,
  • Qiang Wang,
  • Jianjian Dou,
  • Xiangjiao Meng

摘要

Background

Immune checkpoint inhibitors (ICIs) have revolutionized treatment for advanced lung cancer, yet their cardiotoxicity, particularly immune checkpoint inhibitor-related myocarditis, poses significant clinical challenges. This study aims to create a predictive model using cardiac biomarkers to identify patients prone to myocarditis during treatment, thereby enhancing clinical decision-making and patient outcomes.

Methods

In this retrospective cohort study, 1,838 patients with locally advanced and metastatic lung cancer and abnormal baseline cardiac parameters receiving immunotherapy from June 2018 to August 2024 were analyzed, with a follow-up date cutoff of September 20, 2024. Patients were randomly divided into training (70%) and validation (30%) cohorts. Logistic regression analysis was conducted on demographic information, clinical characteristics, treatments, and cardiac parameters of these patients prior to immunotherapy. A nomogram was constructed via multivariable logistic regression, and AUC and Hosmer-Lemeshow tests were performed to verify the accuracy of the model.

Results

Among 1,838 patients, 89 (4.84%) developed myocarditis. Independent predictors included α-HBDH > 910 U/L (OR = 10.57, 95%CI: 2.47–45.22, P = 0.001), CK-MB > 15 ng/mL (OR = 3.87, 95%CI: 1.06–14.11, P = 0.040), hs-cTnT elevation (14–28 pg/mL: OR = 4.19; 28–42 pg/mL: OR = 13.10; >42 pg/mL: OR = 25.43, P < 0.001), NT-proBNP > 3× age-adjusted upper limit (OR = 9.72, 95%CI: 1.09–86.73, P = 0.042), and Caprini score ≥ 4 (OR = 4.49, 95%CI: 2.26–8.90, P < 0.001). The nomogram demonstrated strong discrimination ability, with an AUC of 0.831 in the training cohort (sensitivity: 0.842, specificity: 0.717) and an AUC of 0.844 in the validation cohort.

Conclusions

This study establishes a validated risk assessment model integrating cardiac biomarkers (α-HBDH, CK-MB, hs-cTnT, NT-proBNP) and Caprini risk score to predict ICI-related myocarditis in lung cancer patients with cardiac abnormalities. The tool facilitates early identification of high-risk patients, enabling tailored monitoring and preemptive management. These findings underscore the critical role of baseline cardiac profiling in optimizing immunotherapy safety.