New AI Tool Improves Treatment of Cancer Patients after Heart Attack
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New AI Tool Improves Treatment of Cancer Patients after Heart Attack


Researchers at the University of Zurich have developed an AI-based tool that combines cancer-related and traditional cardiovascular factors. The new risk prediction model enables more precise, individualized treatment for cancer patients who suffer a heart attack.

Cancer patients who suffer a heart attack face a dangerous mix of risks, which makes their clinical treatment particularly challenging. As a result, patients with cancer have been systematically excluded from many clinical trials and available risk scores. Until now, doctors had no standard tool to guide treatment in this vulnerable group.

International study leverages population data
An international team led by researchers from the University of Zurich (UZH) has now developed the first risk prediction model designed specifically for cancer patients who have had a heart attack. The study, published in The Lancet, analyzed more than one million heart attack patients in England, Sweden and Switzerland, including over 47,000 with cancer.

Overall, the results show that cancer patients have strikingly poor prognosis: nearly one in three died within six months, while around one in 14 suffered a major bleed and one in six experienced another heart attack, stroke or cardiovascular death. “To provide targeted treatment for these patients, clinicians need more accurate tools to assess individual risk profiles,” says first author Florian A. Wenzl from the Center for Molecular Cardiology at UZH and the National Health Service England.

AI helps disentangle cancer and heart disease
To achieve this goal, the researchers developed ONCO-ACS. The new tool uses artificial intelligence to combine cancer-related factors with standard clinical data to predict the chances of death, major bleeding or another cardiac event within six months. Although traditionally considered as separate disease entities, the findings highlight the close interplay of cancer and cardiovascular disease. “Depending on the tumor characteristics, cancer patients can be at elevated risk of bleeding, of arterial blood clotting, or both – each requiring different anti-platelet medication for secondary prevention after the acute event,” notes Wenzl.

Impact on clinical practice
The new tool gives doctors reliable information to tailor treatment individually and balance the benefits and harms. “By accounting for both cancer and heart disease, ONCO-ACS marks a step towards truly personalized medicine. It can help doctors decide who benefits from invasive procedures and intensive drug therapy, and who may be at greater risk of harm,” explains senior author Professor Thomas F. Lüscher from the National Heart and Lung Institute, Imperial College London and the Royal Brompton and Harefield Hospitals.

The researchers hope the ONCO-ACS score will soon be integrated into clinical practice to support decisions on catheter-based treatment and antiplatelet therapy. ONCO-ACS provides a validated approach to implement clinical practice guidelines. The new tool can also help to design future trials aiming to improve outcomes in cancer patients who suffer a heart attack.
Literature
Wenzl FA, Ow KW, Velders MA, et al. Prediction of mortality, bleeding, and ischaemic events in patients with cancer and acute coronary syndrome: a model development and validation study. Lancet, 29 January 2026. DOI https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(25)02020-3/fulltext
Regions: Europe, Switzerland, Sweden, United Kingdom
Keywords: Health, Medical, Well being, Applied science, Artificial Intelligence

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