Researchers at MUSC Hollings Cancer Center in Charleston, S.C., have developed an AI-based tool to support clinicians in predicting which patients may be at high risk of serious complications after a stem cell or bone marrow transplant.
Four details to know:
- Researchers created a model to identify patients at higher risk of chronic graft-versus-host disease, one of the most serious complications after a stem cell or bone marrow transplant in which donor immune cells attack a patient’s healthy tissue.
- The model combines blood-based immune biomarkers with clinical data to generate individualized risk estimates. It was developed and validated using data from 1,310 stem cell and bone marrow transplant recipients across multiple studies, according to findings published Feb. 16 in The Journal of Clinical Investigation.
- In testing, the tool reliably predicted patients’ risk and separated them into low- and high-risk groups with distinct outcomes. Earlier identification of higher-risk patients could allow for closer monitoring or preventive strategies, with the potential to improve long-term outcomes, researchers said.
“By the time chronic GVHD is diagnosed, the disease process has often been unfolding for months, quietly hurting the body,” Sophie Paczesny, MD, PhD, lead study author and co-leader of Hollings’ Cancer Biology and Immunology Research Program, said in a news release. “We wanted to know whether we could detect warning signs earlier, before patients feel sick.”
4. The tool is intended to support risk assessment and clinical research rather than guide treatment decisions. It is available as a free, web-based application for clinicians and researchers. As a next step, researchers plan to study whether earlier intervention for high-risk patients improves long-term outcomes.
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