Literature DB >> 35687257

How Genetics Can Drive Initial Therapy Choices for Older Patients with Acute Myeloid Leukemia.

Jozal W Moore1, Nancy Torres1, Michael Superdock2, Jason H Mendler1, Kah Poh Loh3.   

Abstract

OPINION STATEMENT: Treatment of older adults with acute myeloid leukemia (AML) is challenging. Therapy decisions must be guided by multiple factors including aging-related conditions (e.g., comorbidities, functional impairment), therapy benefits and risks, patient preferences, and disease characteristics. Balancing these factors requires understanding the unique, and frequently higher-risk cytogenetic and molecular characteristics of AML in older adult populations, which should caution providers not to reduce therapy intensity on the basis of age alone. Instead, geriatric assessments should be employed to determine fitness for therapy. Treatment options in AML are increasingly targeted to specific mutations or recognized to have differential benefits on the basis of genomics, and representation of older adults and geriatric outcome reporting in clinical trials is improving. Additionally, newer studies have begun to explore personalized therapy strategies on the basis of initial genetic testing. Review and refinement of practice guidelines for older patients on the basis of these advances is needed and is anticipated to remain an important topic in ongoing hematology/oncology clinical education.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Acute myeloid leukemia; Genetics; Geriatric hematology-oncology; Older adults; Precision medicine

Mesh:

Year:  2022        PMID: 35687257     DOI: 10.1007/s11864-022-00991-z

Source DB:  PubMed          Journal:  Curr Treat Options Oncol        ISSN: 1534-6277


  58 in total

1.  Survival for older patients with acute myeloid leukemia: a population-based study.

Authors:  Betul Oran; Daniel J Weisdorf
Journal:  Haematologica       Date:  2012-07-06       Impact factor: 9.941

Review 2.  Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel.

Authors:  Hartmut Döhner; Elihu Estey; David Grimwade; Sergio Amadori; Frederick R Appelbaum; Thomas Büchner; Hervé Dombret; Benjamin L Ebert; Pierre Fenaux; Richard A Larson; Ross L Levine; Francesco Lo-Coco; Tomoki Naoe; Dietger Niederwieser; Gert J Ossenkoppele; Miguel Sanz; Jorge Sierra; Martin S Tallman; Hwei-Fang Tien; Andrew H Wei; Bob Löwenberg; Clara D Bloomfield
Journal:  Blood       Date:  2016-11-28       Impact factor: 22.113

3.  The predictive value of hierarchical cytogenetic classification in older adults with acute myeloid leukemia (AML): analysis of 1065 patients entered into the United Kingdom Medical Research Council AML11 trial.

Authors:  D Grimwade; H Walker; G Harrison; F Oliver; S Chatters; C J Harrison; K Wheatley; A K Burnett; A H Goldstone
Journal:  Blood       Date:  2001-09-01       Impact factor: 22.113

4.  Geriatric assessment in older patients with acute myeloid leukemia: a retrospective study of associated treatment and outcomes.

Authors:  Alexander E Sherman; Gabriela Motyckova; K Rebecca Fega; Daniel J Deangelo; Gregory A Abel; David Steensma; Martha Wadleigh; Richard M Stone; Jane A Driver
Journal:  Leuk Res       Date:  2013-06-06       Impact factor: 3.156

5.  Age and acute myeloid leukemia.

Authors:  Frederick R Appelbaum; Holly Gundacker; David R Head; Marilyn L Slovak; Cheryl L Willman; John E Godwin; Jeanne E Anderson; Stephen H Petersdorf
Journal:  Blood       Date:  2006-02-02       Impact factor: 22.113

6.  Geriatric assessment predicts survival for older adults receiving induction chemotherapy for acute myelogenous leukemia.

Authors:  Heidi D Klepin; Ann M Geiger; Janet A Tooze; Stephen B Kritchevsky; Jeff D Williamson; Timothy S Pardee; Leslie R Ellis; Bayard L Powell
Journal:  Blood       Date:  2013-04-02       Impact factor: 22.113

7.  Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461).

Authors:  John C Byrd; Krzysztof Mrózek; Richard K Dodge; Andrew J Carroll; Colin G Edwards; Diane C Arthur; Mark J Pettenati; Shivanand R Patil; Kathleen W Rao; Michael S Watson; Prasad R K Koduru; Joseph O Moore; Richard M Stone; Robert J Mayer; Eric J Feldman; Frederick R Davey; Charles A Schiffer; Richard A Larson; Clara D Bloomfield
Journal:  Blood       Date:  2002-08-01       Impact factor: 22.113

8.  Age and acute myeloid leukemia: real world data on decision to treat and outcomes from the Swedish Acute Leukemia Registry.

Authors:  Gunnar Juliusson; Petar Antunovic; Asa Derolf; Sören Lehmann; Lars Möllgård; Dick Stockelberg; Ulf Tidefelt; Anders Wahlin; Martin Höglund
Journal:  Blood       Date:  2008-11-13       Impact factor: 22.113

9.  Big data analysis of treatment patterns and outcomes among elderly acute myeloid leukemia patients in the United States.

Authors:  Bruno C Medeiros; Sacha Satram-Hoang; Deborah Hurst; Khang Q Hoang; Faiyaz Momin; Carolina Reyes
Journal:  Ann Hematol       Date:  2015-03-20       Impact factor: 3.673

10.  Value of Different Comorbidity Indices for Predicting Outcome in Patients with Acute Myeloid Leukemia.

Authors:  Maxi Wass; Friederike Hitz; Judith Schaffrath; Carsten Müller-Tidow; Lutz P Müller
Journal:  PLoS One       Date:  2016-10-12       Impact factor: 3.240

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