Biomarkers for Clinical Classification and Outcomes of Immune Checkpoint Inhibitor-Related-Related Myocarditis in Lung Cancer

Condition(s) studied

Investigational drug(s) / intervention(s)

Biomarker Analysis for Severity Assessment: Blood samples will be collected at baseline and at follow-up time points (3 days, 7 days, and before discharge). Traditional myocardial injury biomarkers, iron metabolism-related biomarkers, and immunological biomarkers will be tested.

Study summary

This study aims to investigate the clinical classification and outcome-related biomarkers of immune checkpoint inhibitor (ICI)-related myocarditis in patients with lung cancer.A total of 50 patients with ICI-related myocarditis will be enrolled, including 25 with severe/critical myocarditis and 25 with subclinical/mild myocarditis. Blood samples will be collected at baseline and at follow-up time points (3 days, 7 days, and before discharge). Traditional myocardial injury markers, iron metabolism-related markers, and immunological markers will be measured and compared between groups. Changes in biomarkers after treatment will also be assessed. Clinical information such as in-hospital mortality and 3-month survival rates will be integrated to develop a severity assessment model. This model aims to evaluate disease severity and prognostic risk accurately by combining biomarkers, enhancing their application in clinical management.

Eligibility

Primary outcome measure(s)

• The correlation between the dynamic changes in biomarker combinations and disease severity. — Up to 3 months
  By monitoring the dynamic changes in biomarker combinations at different time points (baseline, day 3, day 7, and before discharge), this study aims to evaluate the differences between the severe/critical group and the mild/subclinical myocardial injury group, and investigate their correlation with disease severity. Independent sample t-tests will be used to assess the differences between the two groups, assuming a moderate effect size (Cohen's d = 0.7) for biomarkers between the severe/critical and subclinical/mild immune checkpoint inhibitor-related myocarditis patients. If significant differences (p \< 0.10) in biomarkers are observed between the groups, these differences will serve as key indicators for stratified management of disease severity.
• Predictive performance of the severity assessment model — Up to 3 months
  The severity assessment model, constructed based on biomarker combinations, was evaluated for its predictive performance using indicators such as the ROC curve and AUC value. The model demonstrated a predictive performance with an AUC \> 0.75 at different time points, indicating a high predictive ability and validating its practical application in clinical risk stratification.

Trial sites (1)