Troponin for surveillance of immune checkpoint inhibitor–associated myocarditis and post-therapy cardiovascular risk stratification: a systematic review and meta-analysis

Figures

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  Figure 1. PRISMA flow Diagram of Study Selection This figure summarizes the identification, screening, eligibility assessment, and final inclusion of studies according to PRISMA 2020. Records were retrieved from Medline (PubMed), Embase, Cochrane CENTRAL, and Scopus, with additional studies identified through reference-list screening. After duplicate removal, titles/abstracts and full texts were screened against prespecified criteria. The figure reports reasons for exclusion at fulltext review and the final number of studies included in quantitative meta-analyses and narrative synthesis. PRISMA, Preferred Reporting Items for Systematic Reviews and MetaAnalyses; CENTRAL, Cochrane Central Register of Controlled Trials.

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  Figure 2. diagnostic meta-analysis forest plot. Forest plot showing study-level and pooled associations between troponin elevation and confirmed immune checkpoint inhibitor (ICI)-associated myocarditis. Effect estimates are presented as odds ratios with 95% confidence intervals, and the pooled estimate was calculated using a random-effects model. Between-study heterogeneity is reported using I2. ICI, immune checkpoint inhibitor; OR, odds ratio; CI, confidence interval.

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  Figure 3. Troponin and MACE forest plot. Forest plot of the prognostic meta-analysis evaluating the association between troponin elevation and major adverse cardiovascular events (MACE) or cardiovascular events in patients receiving immune checkpoint inhibitors. Study-level hazard ratios with 95% confidence intervals are shown, with a pooled random-effects estimate. Statistical heterogeneity is summarized using I2. MACE, major adverse cardiovascular events; ICI, immune checkpoint inhibitor; HR, hazard ratio; CI, confidence interval.

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  Figure 4. Leave-One-Out sensitivity analysis for troponin and MACE. Leave-one-out sensitivity analysis for the meta-analysis of troponin elevation and MACE/cardiovascular events. Each row shows the pooled hazard ratio recalculated after omitting one study at a time. Consistency of the pooled estimates across iterations indicates that the overall association is not driven by a single study. MACE, major adverse cardiovascular events; HR, hazard ratio; CI, confidence interval.

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  Figure 5. Troponin and mortality forest plot. Forest plot of the prognostic meta-analysis evaluating the association between troponin elevation and mortality in immune checkpoint inhibitor–treated patients. Studylevel hazard ratios with 95% confidence intervals are displayed, and the pooled estimate was generated using a random-effects model. Between-study heterogeneity is reported using I2. ICI, immune checkpoint inhibitor; HR, hazard ratio; CI, confidence interval.

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  Figure 6. Leave-One-Out sensitivity analysis for troponin and mortality. Leave-one-out sensitivity analysis for the meta-analysis of troponin elevation and mortality. Each row presents the pooled hazard ratio after sequential exclusion of one study. The stability of pooled estimates across exclusions supports robustness of the overall association despite between-study heterogeneity. ICI, immune checkpoint inhibitor; HR, hazard ratio; CI, confidence interval.

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  Figure 7. QUADAS-2 risk-of-bias summary for diagnostic/screening studies. Traffic-light plot summarizing risk of bias and applicability concerns for included diagnostic and screening studies assessed with QUADAS-2. Domains include patient selection, index test, reference standard, and flow/timing, rated as low, unclear, or high risk. The reference standard domain was frequently rated high risk where myocarditis definitions incorporated troponin, introducing incorporation bias. QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies-2.

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  Figure 8. QUIPS risk-of-bias summary for prognostic studies. Traffic-light plot summarizing risk of bias across included prognostic studies using the QUIPS tool. Domains include study participation, study attrition, prognostic factor measurement, outcome measurement, study confounding, and statistical analysis/reporting, rated as low, moderate, or high risk. Confounding was the most common concern due to limited adjustment for baseline cardiovascular and cancer-related factors in several cohorts. QUIPS, Quality In Prognostic Studies.