Diagnostic and prognostic parameters in immune checkpoint inhibitor-associated myocarditis: a meta-analysis

Background and aims: Myocarditis from immune checkpoint inhibitor (ICI) therapy is a challenge in clinical practice, and the assessment of ICI-related myocarditis (ICI-M) is often complicated by a variable phenotype. Various biochemical and imaging parameters including cardiac magnetic resonance (CMR) are frequently used, but evidence for reliant diagnosis or prognostic assessment of patients with ICI-M is conflicting. This meta-analysis aims to determine whether biochemical and imaging parameters including late gadolinium enhancement (LGE), left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) are suitable as independent parameters to predict ICI-M diagnosis or prognosis.

Methods and results:
After screening of scientific databases, data from 32 trials with 3568 patients were included. LGE [odds ratio (OR) 5.32, 95% confidence interval (CI) 1.61-17.50; n=719; p=0.006] and myo- or pericardial oedema [OR 5.52, 95% CI 1.16-26.40; n=415; p=0.03] in CMR, LVEF [OR 5.53, 95% CI 2.47-8.59; n=2694; p=0.0004] and GLS [OR 4.20, 95% CI 2.05-6.35; n=642; p=0.0001] in echocardiography, and troponin I [standardized mean difference (SMD) 0.70, 95% CI 0.04-1.36; n=279; p=0.04] and BNP/NT-proBNP [SMD 0.92, 95% CI 0.30-1.54; n=905; p=0.003] elevation in biochemical parameters were associated with myocarditis following immune checkpoint inhibitor therapy. Reduced LVEF [OR 5.11, 95% CI 2.53-7.68; n=222; p=0.0001] and troponin I elevation [SMD 2.27, 95% CI 0.33-4.22; n=76; p=0.02] independently predicted major adverse cardiovascular events (MACE).

Conclusion:
LGE, myo- or pericardial oedema in CMR, LVEF and GLS in echocardiography and troponin I, BNP/NT-proBNP and CRP are independent marker for reliant diagnosis of ICI-M. LVEF and troponin I may qualify as screening modality to identify patients at risk for MACE, which require a close anti-inflammatory treatment regime. Further evidence is required to identify the most suitable combination of multi-modalities for diagnosis and prognostic assessment of patients with ICI-M.