Precision oncology for acute myeloid leukemia using a knowledge bank approach.

ABSTRACT: Underpinning the vision of precision medicine is the concept that causative mutations in a patient's cancer drive its biology and, by extension, its clinical features and treatment response. However, considerable between-patient heterogeneity in driver mutations complicates evidence-based personalization of cancer care. Here, by reanalyzing data from 1,540 patients with acute myeloid leukemia (AML), we explore how large knowledge banks of matched genomic-clinical data can support clinical decision-making. Inclusive, multistage statistical models accurately predicted likelihoods of remission, relapse and mortality, which were validated using data from independent patients in The Cancer Genome Atlas. Comparison of long-term survival probabilities under different treatments enables therapeuti

SUBMITTER: Gerstung M 

PROVIDER: S-EPMC5764082 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature