AI Model Predicts Heart Risks for Cancer Patients Following Heart Attacks
Recent advancements in artificial intelligence offer new hope for cancer patients who experience heart attacks. A newly developed tool aims to aid healthcare professionals in evaluating the risks of repeat heart-related complications in this vulnerable group.
Researchers from the United Kingdom and throughout Europe have engineered an innovative computer-based tool targeted at doctors assessing the risk of recurrent heart issues in patients battling cancer. Individuals with cancer frequently encounter more severe outcomes after a heart attack. This is primarily due to the effects of cancer and its treatments, which can debilitate the body, compromise blood vessels, and alter the process of blood clotting. Until now, healthcare teams lacked comprehensive guidance that considered the unique struggles cancer imposes on heart health, meaning doctors had to depend on generic heart risk tools that were not tailored for these patients.
When a cancer patient suffers a heart attack, the likelihood of experiencing serious complications afterward tends to be elevated compared to individuals without cancer. Certain cancers heighten the risk of severe bleeding, while others can lead to hazardous blood clots. In some instances, both risks coexist. Physicians are faced with the challenge of deciding whether to administer blood-thinning medications or to employ measures guarding against clots, all while understanding that miscalculations can result in harm. Making these critical decisions has long been challenging, as conventional tools often fail to incorporate cancer-specific factors.
An international research team spearheaded by the University of Leicester has addressed this need by introducing a model called ONCO-ACS. This innovative tool leverages artificial intelligence to merge standard heart data with cancer-related information, including tumor type and the patient’s medical history. By synthesizing these elements, the system can assess heart attack risks and predict the likelihood that a patient will experience death or significant bleeding within six months following a heart attack.
The researchers evaluated the tool using health records from over one million heart attack patients across England, Sweden, and Switzerland. Among these patients, more than 47,000 had received a current or past cancer diagnosis. The extensive size of this dataset enabled the team to analyze patterns that smaller studies could easily overlook. Findings indicated that cancer patients generally faced dismal outcomes after a heart attack. Nearly one in three such patients succumbed within six months, with about one in fourteen suffering a major bleeding event, and roughly one in six experiencing another heart attack, stroke, or heart-related mortality during the same timeframe.
Dr. Florian A. Wenzl from the University of Leicester and the study’s lead author stated that cancer patients who suffer heart attacks have frequently been overlooked in major research initiatives, despite being among the most complicating cases in cardiology. He emphasized that this new tool provides clinicians with clearer data to evaluate the benefits and risks of treatment options, moving away from reliance on speculation and broad guidelines.
Improvements in cancer care have allowed many individuals to live longer with their conditions, increasing the likelihood they will later experience heart issues. Concurrently, advancements in cardiac treatment have improved survival rates for heart attack patients. This interrelation has led to a rising population of patients requiring care strategies that simultaneously address both cancer and heart disease. Senior author Professor David Adlam indicated that this combination of conditions presents new challenges that necessitate enhanced decision-making support grounded in reliable patient data.
The research team hopes that ONCO-ACS will soon be implemented in routine hospital settings. It may assist in guiding decisions about catheter-based cardiac procedures and anticoagulant therapies following a heart attack. The researchers also believe this model could facilitate future studies by improving patient selection and outcome measurements.
Another senior author, Professor Thomas F. Lüscher from Imperial College London, noted that this tool marks a step forward in aligning treatment with a patient’s comprehensive health profile. By incorporating both cancer and heart disease factors, the model delivers a more holistic assessment of risk. The study received funding from Cancer Research UK and the British Heart Foundation, with additional support from Health Data Research UK, and was published in The Lancet.
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New AI tool helps determine the risk of secondary heart attacks in cancer patients
