Recent advances in precision medicine for acute myeloid leukemia

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Item Type:	Review
Title:	Recent advances in precision medicine for acute myeloid leukemia
Creators Name:	Hernández-Sánchez, A. and Bullinger, L.
Abstract:	PURPOSE OF REVIEW: Acute myeloid leukemia (AML) is a heterogeneous disease, in which treatment response and patient survival are highly conditioned by the leukemia biology. The aim of this review is to summarize recent advances in AML classification, risk stratification models, measurable residual disease (MRD) and the increasing number of treatment options that are paving the way towards precision medicine in AML. RECENT FINDINGS: AML classification and risk stratification were recently updated by incorporating novel molecular markers that are important for diagnosis and outcome prediction. In addition, the impact of co-mutational patterns is under investigation and novel approaches using machine learning algorithms are starting to be used for individualized risk estimation. Molecular markers are also becoming useful in predicting response to non-intensive treatments. MRD informs of treatment response with high sensitivity, allowing dynamic patient risk assessment and early intervention. Finally, important advances were made in AML therapy, with an increasing number of targeted therapies becoming available and many novel treatment approaches being under development with promising early results. SUMMARY: A better understanding of AML biology is leading to improved risk stratification and important advances in treatments, which are allowing the development of precision medicine in AML at an unprecedented pace.
Keywords:	Acute Myeloid Leukemia, Machine Learning, Outcome Prediction, Precision Medicine, Targeted Therapy
Source:	Current Opinion in Oncology
ISSN:	1040-8746
Publisher:	Lippincott Williams & Wilkins
Volume:	35
Number:	6
Page Range:	581-588
Date:	November 2023
Official Publication:	https://doi.org/10.1097/cco.0000000000000965
PubMed:	View item in PubMed

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