The advent of immune checkpoint inhibitors (ICIs) has fundamentally reshaped oncology, yet their success is overshadowed by a spectrum of immune-related adverse events (irAEs), among which immune checkpoint inhibitors-associated myocarditis (ICIs-M) stands out as a rare but potentially fatal complication. Characterized by a high case fatality rate, ICIs-M presents a formidable clinical challenge that urgently demands early diagnosis, accurate risk stratification, and timely intervention. Peripheral biomarkers, particularly cardiac troponins (cTn), have become central to its management, but their application is fraught with complexities and controversies. This review adopts a problem-solution-future framework, moving beyond a traditional chronological summary to critically appraise the role of clinical characteristics and peripheral biomarkers at key clinical decision points. We deconstruct the "troponin paradox"—the observed discrepancy in diagnostic sensitivity and prognostic accuracy between cardiac troponin T (cTnT) and I (cTnI) assays—and delve into its potential mechanistic underpinnings, including the confounding role of concomitant myositis. We scrutinize the evidence for emerging inflammatory and systemic biomarkers, highlighting limitations regarding their specificity and clinical readiness. Furthermore, we offer a critical perspective on the prevailing consensus on therapeutic strategies, such as the timing of corticosteroid initiation, by exposing potential confounding biases in the existing literature. By structuring the analysis around the diagnostic-prognostic-therapeutic continuum, this review aims to address potential misconceptions, identify critical knowledge gaps, and propose a new paradigm for future research. We advocate for a shift from a reactive, troponin-centric approach to a proactive, multi-parameter, and dynamic risk assessment model. Ultimately, this work contributes to the advancement toward where ICIs-M is a predictable, preventable, and precisely treatable condition, moving the field from describing the problem to solving it.
Qian et al. (Thu,) studied this question.