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Published on: February 8, 2018
The predictive value of serial troponin measurements in patients treated with immune checkpoint inhibitors
Moran Gvili Perelman1,2, Rafael Y Brzezinski1,2, Barliz Waissengrin2,3
1Division of Cardiology, Tel-Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel.
Background:
Immune checkpoint inhibitors (ICIs) may lead to immune-related adverse events, including potentially life-threatening cardiovascular (CV) complications. Despite guideline-recommended troponin monitoring, limited data exist on evaluating its predictive significance.
Objective:
We aimed to assess the predictive value of serial high-sensitivity troponin I (hs-TnI) monitoring in patients treated with ICIs.
Methods:
A retrospective, single-center, observational study including patients treated with ICIs and performing serial hs-TnI measurements. The primary endpoint was all-cause mortality, and the secondary endpoint was CV events, defined as the composite of myocarditis, pericarditis, acute coronary syndrome, heart failure, or arrhythmias. A tree classifier model identified the most predictive hs-TnI concentration for the main study endpoints.
Results:
Overall, 455 patients performed baseline (T1) and follow-up hs-TnI (T2) assessments and were included in the cohort. During a mean follow-up of 25 months (IQR [12-36]), 253 (56%) patients died, and 70 (15%) developed CV events. T2 > 8 ng/L was significantly associated with increased all-cause mortality (64% vs 48%, P < .001) and CV events (22% vs 9%, P < .001), notably HF (12% vs 4%, P = .003) and myocarditis (3% vs 0%, P = .038). A multivariable analysis confirmed that T2 > 8 ng/L was an independent predictor for all-cause mortality (HR 1.67, 95% CI: 1.29-2.17, P < .001) and CV events (HR 2.59, 95% CI: 1.50-4.46, P = .001).
Conclusions:
Our study emphasizes the significant role of serial troponin monitoring during ICIs therapy as an independent predictor of all-cause mortality and CV events, and suggests an optimal lower hs-TnI cutoff of >8 ng/L for risk stratification. Large prospective trials are needed to confirm these findings.
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