The results where presented by HARMONY Experts at the 63rd annual meeting of the American Society for Hematology in December, 2022.
Click here to learn more about the HARMONY presentations at ASH2022 >
Click here to open the HARMONY AML scientific paper >
Click here to read the IHI article about the AML results >
See below the text of the article.
Machine learning tool can help identify candidates for stem cell transplant therapy for some cancers
HARMONY’s prototype may offer a more precise way for doctors to predict who should undergo the invasive and risky treatment.
The decision to perform stem cell transplant therapy is not taken lightly. In simple terms, it involves an incredibly invasive series of procedures that essentially destroy a person’s natural immune system, before replacing it with a new one. It can take months to recover, and can even be fatal. That’s why when doctors decide to go ahead with stem cell therapy, they have to be really thorough in weighing the potential benefits against the risks.
The first line treatment for the blood cancer acute myeloid leukaemia (AML) is intensive chemotherapy. Once patients go into remission (meaning the cancer can no longer be detected), they are categorised into three risk categories (low, intermediate, advanced), according to how likely the cancer is to come back. This judgement is based on parameters like age, gender, molecular genetic mutations, and chromosomal abnormalities. People in the low- and intermediate-risk group are not good candidates for stem cell transplantation because of the risks. But those whose cancer is more likely to return are often advised to undergo the procedure.
The current methods used to predict who should be put forward for this therapy, called allogeneic hematopoietic stem cell transplantation (alloHSCT), can be improved. The IMI project HARMONY have developed a prototype machine learning tool using data on numerous different parameters from 842 patients with AML. The tool produces a graphic that describes the probability of relapse-free survival over time. It’s still a prototype, but ultimately, it should help clinicians to carefully weigh the risks and benefits to patients.
#bigdataforbloodcancer: Accelerating Better and Faster Treatment for Patients with Hematologic Malignancies.
The HARMONY Alliance (HARMONY and HARMONY PLUS) is a public-private European Network of Excellence for Big Data in Hematology. Our mission is to unlock and spread valuable knowledge on hematologic malignancies (blood cancers) among a large number of stakeholders, with the goal to harness and mine Big Data to speed up the development of improved treatments for patients and more effective treatment strategies.
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