Purpose of review: Acute myeloid leukemia (AML) is an immensely heterogeneous disease based on the presence of varying combinations of morphologic, immunophenotypic, genetic, and molecular characteristics identified among those diagnosed with this disease. Although current therapeutic strategies provide a reasonable likelihood of achieving a complete remission for the majority of patients, relapse rates and subsequent disease-related mortality remain unacceptably high. Improved methods of risk stratification are needed to better identify patients at considerable risk of relapse in hopes of allowing for early therapeutic intervention and/or intensification that may lead to a higher likelihood of cure. The current status of risk stratification of AML and emerging technologies with potential to improve prognostic classification and outcomes are summarized in this review.
Recent findings: Refinement of our understanding of the impact of current pretreatment AML cytogenetic, immunophenotypic, and molecular aberrations to predict outcomes and guide therapeutic decision-making is ongoing. Emerging data suggest that incorporation of the degree of posttreatment response and/or the detection of minimal residual disease can improve the accuracy of risk stratification for individual patients.
Summary: Although pretreatment disease characteristics remain the hallmark of prognostication for AML patients, posttreatment parameters such as minimal residual disease assessment and degree of response to therapy possess the ability to further refine our identification of patients with unfavorable disease and thereby influence decisions regarding therapeutic planning.