001     288715
005     20240303010022.0
024 7 _ |a 10.1080/16078454.2024.2320006
|2 doi
024 7 _ |a pmid:38407192
|2 pmid
024 7 _ |a 1024-5332
|2 ISSN
024 7 _ |a 1024-5340
|2 ISSN
024 7 _ |a 1607-8454
|2 ISSN
024 7 _ |a altmetric:160127446
|2 altmetric
037 _ _ |a DKFZ-2024-00434
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Salwender, Hans
|0 0000-0001-7803-0814
|b 0
245 _ _ |a Cytomegalovirus immunoglobulin serology prevalence in patients with newly diagnosed multiple myeloma treated within the GMMG-MM5 phase III trial.
260 _ _ |a Abingdon, Oxon
|c 2024
|b Taylor & Francis
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 1709041733_14145
|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
520 _ _ |a The seroprevalence of antibodies against Cytomegalovirus (CMV) is an established poor prognostic factor for patients receiving an allogeneic stem cell transplantation. However, the impact of CMV serology on outcome after autologous stem cell transplantation remains unknown.Here, we analyzed the CMV immunoglobulin (Ig) serology of 446 newly-diagnosed multiple myeloma (MM) patients of the GMMG-MM5 phase III trial with a median follow-up of 58 months.CMV IgG and IgM positivity was seen in 51% and 6% of the patients, respectively. In multivariate analysis CMV IgG and CMV IgM serology show an age-depending effect for PFS. We identified positive CMV IgG/positive CMV IgM serology as an age-depending beneficial factor on PFS.Younger patients with a positive CMV IgG/positive CMV IgM serology experienced a favorable effect on PFS, whereas a positive CMV IgG/positive CMV IgM serology at older age has a disadvantageous effect on PFS.
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
650 _ 7 |a CMV
|2 Other
650 _ 7 |a CMV IgM
|2 Other
650 _ 7 |a CMV-Infection
|2 Other
650 _ 7 |a GMMG-MM5 Phase III Trial
|2 Other
650 _ 7 |a age-depending effect
|2 Other
650 _ 7 |a autologous stem cell transplantation
|2 Other
650 _ 7 |a maintenance therapy
|2 Other
650 _ 7 |a multiple myeloma
|2 Other
650 _ 7 |a cytomegalovirus-specific hyperimmune globulin
|0 129L90A25N
|2 NLM Chemicals
650 _ 7 |a Immunoglobulins, Intravenous
|2 NLM Chemicals
650 _ 7 |a Antibodies, Viral
|2 NLM Chemicals
650 _ 7 |a Immunoglobulin G
|2 NLM Chemicals
650 _ 7 |a Immunoglobulin M
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Cytomegalovirus
|2 MeSH
650 _ 2 |a Hematopoietic Stem Cell Transplantation
|2 MeSH
650 _ 2 |a Multiple Myeloma: diagnosis
|2 MeSH
650 _ 2 |a Multiple Myeloma: therapy
|2 MeSH
650 _ 2 |a Prevalence
|2 MeSH
650 _ 2 |a Seroepidemiologic Studies
|2 MeSH
650 _ 2 |a Transplantation, Autologous
|2 MeSH
650 _ 2 |a Immunoglobulins, Intravenous
|2 MeSH
650 _ 2 |a Antibodies, Viral
|2 MeSH
650 _ 2 |a Immunoglobulin G
|2 MeSH
650 _ 2 |a Cytomegalovirus Infections: epidemiology
|2 MeSH
650 _ 2 |a Immunoglobulin M
|2 MeSH
700 1 _ |a Weinhold, Niels
|b 1
700 1 _ |a Benner, Axel
|0 P:(DE-He78)e15dfa1260625c69d6690a197392a994
|b 2
|u dkfz
700 1 _ |a Miah, Kaya
|0 P:(DE-He78)b97fc5666ea8f9db9ef499de6b2397cf
|b 3
|u dkfz
700 1 _ |a Merz, Maximilian
|b 4
700 1 _ |a Haenel, Mathias
|b 5
700 1 _ |a Jehn, Christian
|b 6
700 1 _ |a Mai, Elias
|b 7
700 1 _ |a Menis, Ekaterina
|b 8
700 1 _ |a Blau, Igor
|b 9
700 1 _ |a Scheid, Christof
|b 10
700 1 _ |a Hose, Dirk
|b 11
700 1 _ |a Seckinger, Anja
|b 12
700 1 _ |a Luntz, Steffen
|b 13
700 1 _ |a Besemer, Britta
|b 14
700 1 _ |a Munder, Markus
|b 15
700 1 _ |a Brossart, Peter
|b 16
700 1 _ |a Glass, Bertram
|b 17
700 1 _ |a Lindemann, Hans-Walter
|b 18
700 1 _ |a Weisel, Katja
|b 19
700 1 _ |a Hanoun, Christine
|b 20
700 1 _ |a Schnitzler, Paul
|b 21
700 1 _ |a Klemm, Sarah
|b 22
700 1 _ |a Goldschmidt, Hartmut
|b 23
700 1 _ |a Raab, Marc
|b 24
700 1 _ |a Elmaagacli, Ahmet
|b 25
773 _ _ |a 10.1080/16078454.2024.2320006
|g Vol. 29, no. 1, p. 2320006
|0 PERI:(DE-600)2035573-7
|n 1
|p 2320006
|t Hematology
|v 29
|y 2024
|x 1024-5332
909 C O |o oai:inrepo02.dkfz.de:288715
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 2
|6 P:(DE-He78)e15dfa1260625c69d6690a197392a994
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 3
|6 P:(DE-He78)b97fc5666ea8f9db9ef499de6b2397cf
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 JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b HEMATOLOGY : 2014
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2023-07-21T08:11:22Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2023-07-21T08:11:22Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Double anonymous peer review
|d 2023-07-21T08:11:22Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-10-24
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2023-10-24
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b HEMATOLOGY : 2022
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2023-10-24
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2023-10-24
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2023-10-24
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-10-24
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-10-24
920 1 _ |0 I:(DE-He78)C060-20160331
|k C060
|l C060 Biostatistik
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)C060-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21