| Literature DB >> 32249005 |
Roland B Walter1, Elihu H Estey2.
Abstract
Acute myeloid leukemia (AML) remains difficult to treat: despite multiagent chemotherapy, allogeneic hematopoietic cell transplantation, and several newly approved agents, many patients will not be alive and in remission 3 years after diagnosis. However, with more agents available there are more options and a corresponding need to choose among them. Doing so is complicated by the molecular diversity of AML and the older age of many patients, predisposing them to both treatment-related mortality and, more commonly, resistance to treatment. There is no shortage of scoring systems to identify patients at high risk of early death or treatment resistance after conventional AML induction chemotherapy. As we point out here, their accuracy is limited. Furthermore, without periodic recalibration to account for new therapies and changes in supportive care, the accuracy of any prediction model will decrease over time. The limitations we describe here are important for clinicians to be aware of.Entities:
Keywords: Acute myeloid leukemia (AML); Mathematical modeling; Medical fitness; Outcome prediction; Therapeutic resistance; Treatment-related mortality
Mesh:
Substances:
Year: 2020 PMID: 32249005 DOI: 10.1016/j.blre.2020.100679
Source DB: PubMed Journal: Blood Rev ISSN: 0268-960X Impact factor: 8.250