Acute myeloid leukaemia (AML) is the most-common acute leukaemia in adults, and is primarily a disease of older adults (defined in this Review as those aged ≥60 years, unless otherwise stated), with a median age at diagnosis of 67 years1, 2. The survival rates for younger adults with AML (aged <60 years) have improved, to some extent, over time, owing mostly to the development of intensive consolidation chemotherapy regimens, and improvements in supportive care and allogeneic haematopoietic-stem-cell transplantation (allo-HSCT) — the standard induction chemotherapy regimens have not changed substantially over the past 40 years3. In older patients, however, limited or no improvement in survival rates has been achieved, especially in patients aged >75 years, for whom no improvement in outcome has been demonstrated over the past three decades4.
01-12-2015 | Hematologic cancers | Article
Molecular therapy for acute myeloid leukaemia
Abstract
Acute myeloid leukaemia (AML) is a heterogeneous disease that is, in general, associated with a very poor prognosis. Multiple cytogenetic and molecular abnormalities that characterize different forms of AML have been used to better prognosticate patients and inform treatment decisions. Indeed, risk status in patients with this disease has classically been based on cytogenetic findings; however, additional molecular characteristics have been shown to inform risk assessment, including FLT3, NPM1, KIT, and CEBPA mutation status. Advances in sequencing technology have led to the discovery of novel somatic mutations in tissue samples from patients with AML, providing deeper insight into the mutational landscape of the disease. The majority of patients with AML (>97%) are found to have a clonal somatic abnormality on mutational profiling. Nevertheless, our understanding of the utility of mutation profiling in clinical practice remains incomplete and is continually evolving, and evidence-based approaches to application of these data are needed. In this Review, we discuss the evidence-base for integrating mutational data into treatment decisions for patients with AML, and propose novel therapeutic algorithms in the era of molecular medicine.
Nat Rev Clin Oncol 2016; 13: 305–318. doi:10.1038/nrclinonc.2015.210
Subject terms: Acute myeloid leukaemia • Cancer genetics • Cancer therapy • Outcomes research • Predictive markers