Home > Publications database > Outcomes with intensive treatment for acute myeloid leukemia: an analysis of two decades of data from the HARMONY Alliance. > print

001     294426
005     20250507095842.0
024 7 _ |a 10.3324/haematol.2024.285805
|2 doi
024 7 _ |a pmid:39506894
|2 pmid
024 7 _ |a 0390-6078
|2 ISSN
024 7 _ |a 1592-8721
|2 ISSN
024 7 _ |a altmetric:170330602
|2 altmetric
037 _ _ |a DKFZ-2024-02255
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Sobas, Marta Anna
|b 0
245 _ _ |a Outcomes with intensive treatment for acute myeloid leukemia: an analysis of two decades of data from the HARMONY Alliance.
260 _ _ |a Pavia
|c 2025
|b Ferrata Storti Foundation
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1746604672_3750
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a 2025 May 1;110(5):1126-1140
520 _ _ |a Since 2017, targeted therapies combined with conventional intensive chemotherapy have started to improve outcome of patients with acute myeloid leukemia (AML). However, even before these innovations outcomes with intensive chemotherapy have improved, which has not yet been extensively studied. Thus, we used a large pan-European multicenter dataset of the HARMONY Alliance to evaluate treatment-time dependent outcomes over two decades. In 5359 AML patients, we compared the impact of intensive induction therapy on outcome over four consecutive 5-year calendar periods from 1997 to 2016. During that time, the 5- year survival of AML patients improved significantly, also across different genetic risk groups. In particular, the 60-day mortality rate has dropped from 13.0% to 4.7% over time. The independent effect of calendar periods on outcome was confirmed in multivariate models. Improvements were documented both for patients.
536 _ _ |a 313 - Krebsrisikofaktoren und Prävention (POF4-313)
|0 G:(DE-HGF)POF4-313
|c POF4-313
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
700 1 _ |a Turki, Amin T
|b 1
700 1 _ |a Ramiro, Angela Villaverde
|b 2
700 1 _ |a Sánchez, Alberto Hernández
|b 3
700 1 _ |a Elicegui, Javier Martinez
|b 4
700 1 _ |a González, Teresa
|b 5
700 1 _ |a Melchor, Raúl Azibeiro
|b 6
700 1 _ |a Abáigar, María
|b 7
700 1 _ |a Tur, Laura
|b 8
700 1 _ |a Dall'Olio, Daniele
|b 9
700 1 _ |a Sträng, Eric
|b 10
700 1 _ |a Tettero, Jesse M
|b 11
700 1 _ |a Castellani, Gastone
|b 12
700 1 _ |a Benner, Axel
|0 P:(DE-He78)e15dfa1260625c69d6690a197392a994
|b 13
|u dkfz
700 1 _ |a Döhner, Konstanze
|b 14
700 1 _ |a Thiede, Christian
|b 15
700 1 _ |a Metzeler, Klaus H
|b 16
700 1 _ |a Haferlach, Torsten
|b 17
700 1 _ |a Damm, Frederik
|0 P:(DE-HGF)0
|b 18
700 1 _ |a Ayala, Rosa
|b 19
700 1 _ |a Martínez-López, Joaquín
|b 20
700 1 _ |a Mills, Ken I
|b 21
700 1 _ |a Sierra, Jorge
|b 22
700 1 _ |a Lehmann, Sören
|b 23
700 1 _ |a Porta, Matteo G Della
|b 24
700 1 _ |a Mayer, Jiri
|b 25
700 1 _ |a Reinhardt, Dirk
|b 26
700 1 _ |a Medina, Rubén Villoria
|b 27
700 1 _ |a Schulze-Rath, Renate
|b 28
700 1 _ |a Barbus, Martje
|b 29
700 1 _ |a Hernández-Rivas, Jesús María
|b 30
700 1 _ |a Huntly, Brian J P
|b 31
700 1 _ |a Ossenkoppele, Gert
|b 32
700 1 _ |a Döhner, Hartmut
|b 33
700 1 _ |a Bullinger, Lars
|0 P:(DE-HGF)0
|b 34
773 _ _ |a 10.3324/haematol.2024.285805
|0 PERI:(DE-600)2805244-4
|n 5
|p 1126-1140
|t Haematologica
|v 110
|y 2025
|x 0390-6078
909 C O |p VDB
|o oai:inrepo02.dkfz.de:294426
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 13
|6 P:(DE-He78)e15dfa1260625c69d6690a197392a994
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 18
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 34
|6 P:(DE-HGF)0
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-313
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Krebsrisikofaktoren und Prävention
|x 0
914 1 _ |y 2024
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2023-06-05T07:07:08Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2023-06-05T07:07:08Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Peer review
|d 2023-06-05T07:07:08Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-08-23
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-08-23
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2023-08-23
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-08-23
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-08-23
920 1 _ |0 I:(DE-He78)C060-20160331
|k C060
|l C060 Biostatistik
|x 0
920 1 _ |0 I:(DE-He78)BE01-20160331
|k BE01
|l DKTK Koordinierungsstelle Berlin
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C060-20160331
980 _ _ |a I:(DE-He78)BE01-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21