New tool improves prediction of post-BMT outcomes in patients with MDS

Researchers have developed a new personalized blood and marrow transplant (BMT) outcomes prediction tool for patients with myelodysplastic syndromes (MDS) that incorporates both genomic and clinical data. The tool, although not yet publically available, may help clinicians better identify potential risks and benefits for patients to determine appropriate treatment options prior to BMT.

Predict survival and relapse with more accuracy than current tools

The new tool correctly predicted a patient’s likelihood of surviving for a given length of time at 74% compared to 67% using the current internal prognostic scoring system (IPSS-R). The tool accurately predicted a patient's risk of transformation to acute myeloid leukemia 80 percent of the time, compared to IPSS-R accuracy of 73 percent.

Tool developed based on large cohort

The tool is based on a web application that was created and tested with genomic information not currently used with the IPSS-R and clinical data from 2,302 patients with MDS who were enrolled in the CIBMTR Registry.

Dr. Aziz Nazha from the Cleveland Clinic, Cleveland, OH presented the model on behalf of the CIBMTR® (Center for International Blood and Marrow Transplant Research®) Chronic Leukemia Committee at the 2018 American Society of Hematology (ASH) Annual Meeting.

Dr Nazha concluded that adding genomic data can increase the understanding a patient's prognosis and allows for improvements in developing a personalized treatment plan to counsel patients. Additional work on this tool is being done to predict survival probability after BMT at 6,12 and 24 months.

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