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May 29, 2026Journal of Clinical Oncology0 citations

Artificial intelligence surrogate models to predict long-term cardiovascular effects of immune checkpoint inhibitor therapies using electrocardiograms.

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FDFrances DeanJBJoshua BarriosGTGeoffrey Tison

Key Result

AI-based ECG surrogate models estimated that immune checkpoint inhibitors increased the 10-year relative risk of heart failure by 32% (RR 1.32; 95% CI 1.27-1.36) and ischemic heart disease by 17%.

Key Points

  • This study aims to predict the long-term cardiovascular effects of immune checkpoint inhibitors using AI models based on ECG data.
  • Developed two ECG AI models using data from over 80,000 cancer patients treated between 1986 and 2021.
  • Evaluated 15,277 patients, including those treated with anthracyclines and trastuzumab, for risk assessment.
  • Used time-to-event framework for observed outcomes and causal analysis with pre and post treatment ECGs.
  • Models achieved average AUC of 0.78 and 0.77 across various cardiovascular diseases.
  • ICI treated patients showed a 10-year risk increase of 10% for ischemic heart disease, venous thromboembolism, and critical ventricular arrhythmias compared to other treatments.
  • Anthracyclines and trastuzumab were associated with a 45% and 46% increase in heart failure risk, respectively.

Study Design

Type

Observational (n=80,000)

Multicenter

No

Structured PICO

Do immune checkpoint inhibitors and other cancer therapies increase the long-term risk of cardiovascular disease in cancer patients as predicted by AI ECG surrogate models?

P
Population
Over 80,000 cancer patients treated from 1986 to 2021 at the University of California, San Francisco, with a hold-out evaluation cohort of 15,277 patients (including 3,681 treated with anthracyclines, 751 with trastuzumab, and 3,572 with immune checkpoint inhibitors).
I
Intervention
Cancer therapies including immune checkpoint inhibitors (ICI), anthracyclines, and trastuzumab.
C
Comparator
Patients with any other cancer treatment (for the observed model) or paired pre-treatment baseline (for the causal model).
O
Outcome
10-year risk of cardiovascular diseases (including atrial fibrillation, ischemic heart disease, heart failure, ischemic stroke, critical ventricular arrhythmia, venous thromboembolism, and conduction disorders) predicted by AI ECG surrogate models.surrogate

AI-based ECG surrogate models suggest that immune checkpoint inhibitors, alongside anthracyclines and trastuzumab, may significantly increase the long-term risk of multiple cardiovascular diseases including heart failure and ischemic heart disease.

Main Result

Effect estimate: RR 1.32 (95% CI 1.27-1.36)

Abstract

12020 Background: Immune checkpoint inhibitors (ICI) revolutionized the treatment landscape for many cancers, with close to 50% of cancer patients now ICI eligible. Acutely, ICI are associated with myocarditis. Long term cardiovascular effects of ICI are less clear. We built artificial intelligence (AI) models as surrogates for predicting long-term cardiovascular disease (CVD) after ICI using electrocardiograms (ECG). Methods: Using data from over 80,000 cancer patients treated from 1986 to 2021 at the University of California, San Francisco, we develop two ECG AI models as surrogates for risk over time of CVD. First, we built a model of observed CVD using true outcomes in a time to event framework. This model is a surrogate for prevalence under the current standard of care. Second, we build a model for causal outcomes using before-and-after data and estimate risk from ECGs for causal analyses. We hold out patients (N=15,277), including all those treated with anthracyclines (N= 3,681), trastuzumab (N=751), or ICI (N= 3,572), for evaluation. Causal effects are estimated with paired pre and post treatment ECGs within three years. Results: Models have average AUC across CVDs and years of 0.78 and 0.77. The observed model estimates ICI treated patients compared to those with any other cancer treatment have higher average 10-year risk of ischemic heart disease (IHD) by 10% (95% CI: 2-18%), venous thromboembolism (VTE) by 10% (1-20%), and critical ventricular arrhythmias (CVA) by 10% (3-19%), largely due to high baseline risk. Anthracycline and trastuzumab treated patients did not have higher 10-year heart failure (HF) risk relative to other treatments in aggregate. The causal framework estimates anthracyclines increased average 10-year risk of HF by 45% and trastuzumab by 46%. Anthracyclines and trastuzumab significantly increased risk of atrial fibrillation, IHD, ischemic stroke, CVA, VTE, and conduction disorders as well. ICI increased risk of each of these significantly by smaller amounts. Notably, after ICI, average 10-year risk of HF increased by 32% and IHD by 17%. Conclusions: Our study demonstrates potential long-term CVD effects of ICI as estimated from ECGs. This framework can be used to evaluate effects of new therapies in the future. 10-year pre/post treatment relative risks. CVD Anthracycline Trastuzumab ICI Atrial fibrillation 1.34 1.29, 1.39 1.30 1.24, 1.36 1.25 1.21, 1.28 Ischemic heart disease 1.25 1.21, 1.28 1.28 1.23, 1.32 1.17 1.14, 1.19 Heart failure 1.45 1.39, 1.52 1.46 1.38, 1.55 1.32 1.27, 1.36 Ischemic stroke 1.41 1.32, 1.50 1.31 1.22, 1.41 1.28 1.21, 1.35 Critical ventricular arrhythmia 1.18 1.15, 1.22 1.14 1.09, 1.19 1.10 1.07, 1.13 Venous thromboembolism 1.29 1.24, 1.33 1.26 1.21, 1.31 1.26 1.21, 1.30 Conduction disorder 1.19 1.17, 1.21 1.19 1.16, 1.21 1.15 1.13, 1.17

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Cite This Study

Dean et al. (2026) conducted an observational in Cancer (n=80,000). Immune checkpoint inhibitors (ICI) vs. Pre-treatment baseline / other cancer treatments was evaluated on 10-year risk of heart failure (RR 1.32, 95% CI 1.27-1.36). AI-based ECG surrogate models estimated that immune checkpoint inhibitors increased the 10-year relative risk of heart failure by 32% (RR 1.32; 95% CI 1.27-1.36) and ischemic heart disease by 17%.

synapsesocial.com/papers/6a192da0fab5b468c44167f1https://doi.org/10.1200/jco.2026.44.16_suppl.12020
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