Researchers have developed a novel prognostic framework using genomic sequencing data to assess risk in patients with acute myeloid leukemia (AML). Their work was presented at the American Society of Hematology (ASH) 57th Annual Meeting & Exposition in Orlando, Florida (December 5-8).
Physicians have long known that genomic mutations are a primary cause of AML development and progression, but less is understood about how particular combinations of genomic risk factors can impact patient outcomes.
Researchers looked at the profiles of 111 cancer genes matched with detailed diagnostic, treatment, and survival data from 1540 patients with AML. About two-thirds of patient’s risk variation could be attributed to genomic factors such as balanced rearrangements, copy number changes, and point mutations. The remaining patients’ risk was mostly associated with clinical data, including diagnostic blood counts, demographic data, and treatment regimens.
Using these genomic assessments coupled with clinical data, the team developed their own framework for evaluating prognostic indicators at different stages of therapy to predict the probability of different outcomes and to compute how these probabilities change as a patient’s risk factors evolve over time. With this framework, the team was able to correctly predicted the risk status of 72% of patients.
The team concluded that their technique could be used to accurately predict the outcomes of different treatment strategies for each individual patient with AML. The prognostic framework has since been implemented into a web portal, although the researchers estimate that a cohort of about 10,000 patients will be needed to establish precise clinical support.
