Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors

Author:

Boscaro Eleonora1,Urbino Irene1,Catania Federica Maria1,Arrigo Giulia1,Secreto Carolina1,Olivi Matteo1,D’Ardia Stefano1,Frairia Chiara1,Giai Valentina1,Freilone Roberto1,Ferrero Dario2,Audisio Ernesta1,Cerrano Marco1ORCID

Affiliation:

1. Division of Hematology, Department of Oncology, Presidio Molinette, AOU Città della Salute e della Scienza di Torino, 10126 Turin, Italy

2. Division of Hematology, Department of Molecular Biotechnology and Health Sciences, University of Torino, 10126 Turin, Italy

Abstract

An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on “knowledge banks”. Indeed, more robust prognostic estimations can be obtained by matching each patient’s genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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