medRxiv [Preprint]. 2024 Mar 19:2024.03.12.24304047. doi: 10.1101/2024.03.12.24304047.

ABSTRACT

BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability.

OBJECTIVES: To examine an artificial intelligence (AI)-enhanced electrocardiographic (AI-ECG) surrogate for imaging risk biomarkers, and its association with CTRCD.

METHODS: Across a five-hospital U.S.-based health system (2013-2023), we identified patients with breast cancer or non-Hodgkin lymphoma (NHL) who received anthracyclines (AC) and/or trastuzumab (TZM), and a control cohort receiving immune checkpoint inhibitors (ICI). We deployed a validated AI model of left ventricular systolic dysfunction (LVSD) to ECG images (≥0.1, positive screen) and explored its association with i) global longitudinal strain (GLS) measured within 15 days ( n =7,271 pairs); ii) future CTRCD (new cardiomyopathy, heart failure, or left ventricular ejection fraction [LVEF]<50%), and LVEF<40%. In the ICI cohort we correlated baseline AI-ECG-LVSD predictions with downstream myocarditis.

RESULTS: Higher AI-ECG LVSD predictions were associated with worse GLS (-18% [IQR:-20 to -17%] for predictions<0.1, to -12% [IQR:-15 to -9%] for ≥0.5 ( p <0.001)). In 1,308 patients receiving AC/TZM (age 59 [IQR:49-67] years, 999 [76.4%] women, 80 [IQR:42-115] follow-up months) a positive baseline AI-ECG LVSD screen was associated with ∼2-fold and ∼4.8-fold increase in the incidence of the composite CTRCD endpoint (adj.HR 2.22 [95%CI:1.63-3.02]), and LVEF<40% (adj.HR 4.76 [95%CI:2.62-8.66]), respectively. Among 2,056 patients receiving ICI (age 65 [IQR:57-73] years, 913 [44.4%] women, follow-up 63 [IQR:28-99] months) AI-ECG predictions were not associated with ICI myocarditis (adj.HR 1.36 [95%CI:0.47-3.93]).

CONCLUSION: AI applied to baseline ECG images can stratify the risk of CTRCD associated with anthracycline or trastuzumab exposure.

CONDENSED ABSTRACT: There is an unmet need for scalable and affordable biomarkers to stratify the risk of cancer therapeutics-related cardiac dysfunction (CTRCD). In this hospital system-based, decade-long cohort of patients without cardiomyopathy receiving anthracyclines or trastuzumab, a validated artificial intelligence algorithm applied to baseline electrocardiographic (AI-ECG) images identified individuals with a 2-fold and 4.8-fold risk of developing any cardiomyopathy or left ventricular ejection fraction <40%, respectively. This supports a role for AI-ECG interpretation of images as a scalable approach for the baseline risk stratification of patients initiating cardiotoxic chemotherapy.

PMID:38562897 | PMC:PMC10984033 | DOI:10.1101/2024.03.12.24304047