An observational study in Lung Cancer and Myocarditis Due to Drug, sponsored by Shanghai Chest Hospital. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-02-10.
Sponsored by Shanghai Chest Hospital · Observational
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.
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This study's planned enrollment of 50 is below the median of 190 across 1,547 observational studies indexed under Lung Neoplasms.
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The study population consists of patients with pathologically confirmed lung cancer who have received at least one dose of immune checkpoint inhibitor (ICI) therapy and have been clinically diagnosed with ICI-related myocarditis. Eligible participants must be 18 years or older and capable of providing informed consent. Patients will be stratified into two groups based on disease severity: severe/critical myocarditis and mild/subclinical myocardial injury. Exclusion criteria include pregnancy or breastfeeding, severe underlying cardiovascular diseases or recent acute cardiac events, concurrent other malignancies or immune-related diseases, and inability to complete required examinations and follow-ups. This population is intended to represent a clinically relevant cohort for exploring the association between biomarker dynamics and disease severity in ICI-related myocarditis.
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Exclusion Criteria:
Severe Type: Significant symptoms (e.g., fatigue, palpitations, chest pain) triggered by daily activities without hemodynamic changes; elevated myocardial biomarkers (Cardiac troponin, creatine kinase, Creatine kinase myocardial band, Aspartate aminotransferase，natriuretic peptides); new ECG changes; structural and functional myocardial abnormalities on echocardiography or MRI. Critical Type: Intolerable symptoms (e.g., respiratory dysfunction, heart failure, cardiogenic shock) at rest or minimal activity, with hemodynamic instability; significantly elevated myocardial biomarkers (Cardiac troponin, creatine kinase, Creatine kinase myocardial band, Aspartate aminotransferase, natriuretic peptides); severe myocardial structural and functional abnormalities on echocardiography or MRI; new severe arrhythmias on ECG .
Diagnostic Test: Biomarker Analysis for Severity Assessment
Subclinical Myocardial Injury: All three of the following criteria must be met: 1. No clinical symptoms triggered by daily activities; 2. Only mild elevation of Cardiac troponin levels without elevation of other myocardial injury biomarkers; 3. No abnormalities detected in other auxiliary examinations. Mild Type: The following conditions must be met for diagnosis: 1. Daily activities may cause mild, nonspecific symptoms such as fatigue or shortness of breath; 2. Mild elevation of myocardial injury biomarkers (Cardiac troponin, creatine kinase, Creatine kinase myocardial band, Aspartate aminotransferase，natriuretic peptides); 3. Mild abnormalities on ECG, including new-onset sinus tachycardia, atrial arrhythmias, or nonspecific ST-T changes; 4. No structural or functional abnormalities of the myocardium detected by echocardiography or cardiac MRI.
Diagnostic Test: 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.
The correlation between the dynamic changes in biomarker combinations and disease severity.
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.
Time frame: Up to 3 months
Predictive performance of the severity assessment model
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.
Time frame: Up to 3 months
In-hospital mortality
The rate of death occurring within the hospital during a patient's stay.
Time frame: Up to 3 months
3-month survival rate
The 3-month survival rate will be defined as the proportion of patients alive 3 months after enrollment in the study.
Time frame: Up to 3 months
Improvement in patients' symptoms.
Patients' symptom improvement (e.g., fatigue, dyspnea) will be recorded using the New York Heart Association (NYHA) Functional Classification and analyzed in relation to changes in biomarker combinations. This will provide insights into the potential application of biomarkers in predicting symptom improvement and disease severity.
Time frame: Up to 3 months
Length of hospital stay.
The length of hospital stay will be recorded and analyzed in relation to biomarker combinations and model prediction results, providing additional data to support practical applications in clinical management.
Time frame: Up to 3 months
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