Clinical Reviews:
Efficacy of azacitidine is independent of molecular and clinical characteristics - an analysis of 128 patients with myelodysplastic syndromes or acute myeloid leukemia and a review of the literature
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Abstract
Andrea Kuendgen1, Catharina Müller-Thomas2, Michael Lauseker4, Torsten Haferlach3, Petra Urbaniak1, Thomas Schroeder1, Carolin Brings1, Michael Wulfert1, Manja Meggendorfer3, Barbara Hildebrandt5, Beate Betz5, Brigitte Royer-Pokora5, Norbert Gattermann1, Rainer Haas1, Ulrich Germing1 and Katharina S. Götze2
1Department of Hematology, Oncology and Clinical Immunology, Heinrich-Heine University, Duesseldorf, Germany
2Department of Medicine III, Hematology and Oncology, Technische Universität München, Munich, Germany
3MLL Munich Leukemia Laboratory, Munich, Germany
4Institute for Medical Informatics and Biometry, Ludwig-Maximilians-Universität, Munich, Germany
5Institute for Human Genetics, Heinrich-Heine University, Duesseldorf, Germany
Correspondence to:
Andrea Kuendgen, email: kuendgen@med.uni-duesseldorf.de
Keywords: myelodysplastic syndromes; azacitidine; hypomethylating agents; response prediction; targeted therapy
Received: January 10, 2018 Accepted: March 24, 2018 Published: June 12, 2018
ABSTRACT
Azacitidine is the first drug to demonstrate a survival benefit for patients with MDS. However, only half of patients respond and almost all patients eventually relapse. Limited and conflicting data are available on predictive factors influencing response. We analyzed 128 patients from two institutions with MDS or AML treated with azacitidine to identify prognostic indicators. Genetic mutations in ASXL1, RUNX1, DNMT3A, IDH1, IDH2, TET2, TP53, NRAS, KRAS, FLT3, KMT2A-PTD, EZH2, SF3B1, and SRSF2 were assessed by next-generation sequencing.
With a median follow up of 5.6 years median survival was 1.3 years with a response rate of 49%. The only variable with significant influence on response was del(20q). All 6 patients responded (p = 0.012) but survival was not improved. No other clinical, cytogenetic or molecular marker for response or survival was identified. Interestingly, patients from poor-risk groups as high-risk cytogenetics (55%), t-MDS/AML (54%), TP53 mutated (48%) or relapsed after chemotherapy (60%) showed a high response rate. Factors associated with shorter survival were low platelets, AML vs. MDS, therapy-related disease, TP53 and KMT2A-PTD. In multivariate analysis anemia, platelets, FLT3-ITD, and therapy-related disease remained in the model. Poor-risk factors such as del(7q)/-7, complex karyotype, ASXL1, RUNX1, EZH2, and TP53 did not show an independent impact. Thus, no clear biomarker for response and survival can be identified. Although a number of publications on predictive markers for response to AZA exist, results are inconsistent and improved response rates did not translate to improved survival. Here, we provide a comprehensive overview comparing the studies published to date.
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