000128627 001__ 128627
000128627 005__ 20240228145541.0
000128627 0247_ $$2doi$$a10.18632/oncotarget.19536
000128627 0247_ $$2pmid$$apmid:28978130
000128627 0247_ $$2pmc$$apmc:PMC5620270
000128627 0247_ $$2altmetric$$aaltmetric:27094277
000128627 037__ $$aDKFZ-2017-04643
000128627 041__ $$aeng
000128627 082__ $$a610
000128627 1001_ $$0P:(DE-HGF)0$$aGross, Jonathan P$$b0
000128627 245__ $$aBody fat composition as predictive factor for treatment response in patients with newly diagnosed multiple myeloma - subgroup analysis of the prospective GMMG MM5 trial.
000128627 260__ $$a[S.l.]$$bImpact Journals LLC$$c2017
000128627 3367_ $$2DRIVER$$aarticle
000128627 3367_ $$2DataCite$$aOutput Types/Journal article
000128627 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1660726766_10248
000128627 3367_ $$2BibTeX$$aARTICLE
000128627 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000128627 3367_ $$00$$2EndNote$$aJournal Article
000128627 520__ $$aObesity is a well-known risk factor for malignant tumors and increased body mass index (BMI) is correlated to the risk of developing multiple myeloma (MM). The correlation of body fat composition with disease activity, adverse events and treatment response of MM patients has not been investigated yet.A subgroup of 108 patients from a single institution enrolled in the prospective GMMG-MM5 trial, who received a whole-body low-dose computed tomography (WBLDCT) before induction therapy, were included in this study. Body fat composition was measured in WBLDCT for each patient, divided in the compartments abdomen, pelvis, thigh and further categorized in subcutaneous (SAT) and visceral adipose tissue (VAT). The correlation of these parameters with disease activity (M protein, plasma cell count, LDH, CRAB-criteria), adverse cytogenetics, adverse events and treatment response were evaluated.Significant reciprocal correlation was found between adverse cytogenetics and VAT of the abdomen and pelvis, respectively (gain 1q21: p=0.009 and p=0.021; t(4;14): p=0.038 and p=0.042). No correlation of VAT or SAT with adverse events was observed. Significant reciprocal correlation was observed between abdominal (p=0.03) and pelvic (p=0.035) VAT and treatment response. Abdominal VAT remains significant (p=0.034) independently of revised ISS stage and treatment. The BMI did not show a significant correlation with treatment response or investigated cytogenetics.Based on the clinically relevant difference in treatment outcome depending on VAT and SAT, excessive body fat of abdomen and pelvis might be a predictive factor for poor treatment response. Further influences in this context should be considered as well, e.g. chemotherapy dosing and body fat metabolism. Further studies are necessary to investigate this hypothesis.
000128627 536__ $$0G:(DE-HGF)POF3-315$$a315 - Imaging and radiooncology (POF3-315)$$cPOF3-315$$fPOF III$$x0
000128627 588__ $$aDataset connected to CrossRef, PubMed,
000128627 7001_ $$aNattenmüller, Johanna$$b1
000128627 7001_ $$aHemmer, Stefan$$b2
000128627 7001_ $$0P:(DE-He78)2ef631585610340ff425c9c31fcabd03$$aTichy, Diana$$b3
000128627 7001_ $$0P:(DE-He78)5a7a75d1b29b770f98f1bb2062fc3df9$$aKrzykalla, Julia$$b4
000128627 7001_ $$0P:(DE-He78)a1aa959d47e3e026abe157a8adf24b96$$aGoldschmidt, Hartmut$$b5
000128627 7001_ $$aBertsch, Uta$$b6
000128627 7001_ $$0P:(DE-He78)3e76653311420a51a5faeb80363bd73e$$aDelorme, Stefan$$b7
000128627 7001_ $$aKauczor, Hans-Ulrich$$b8
000128627 7001_ $$0P:(DE-He78)7ccc574e713526d2a22d7acb9b2248c5$$aHillengass, Jens$$b9
000128627 7001_ $$0P:(DE-HGF)0$$aMerz, Maximilian$$b10$$eLast author
000128627 773__ $$0PERI:(DE-600)2560162-3$$a10.18632/oncotarget.19536$$gVol. 8, no. 40$$n40$$p68460-68471$$tOncoTarget$$v8$$x1949-2553$$y2017
000128627 909CO $$ooai:inrepo02.dkfz.de:128627$$pVDB
000128627 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)2ef631585610340ff425c9c31fcabd03$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000128627 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)5a7a75d1b29b770f98f1bb2062fc3df9$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000128627 9101_ $$0I:(DE-HGF)0$$6P:(DE-He78)a1aa959d47e3e026abe157a8adf24b96$$aExternal Institute$$b5$$kExtern
000128627 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)3e76653311420a51a5faeb80363bd73e$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000128627 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)7ccc574e713526d2a22d7acb9b2248c5$$aDeutsches Krebsforschungszentrum$$b9$$kDKFZ
000128627 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-HGF)0$$aDeutsches Krebsforschungszentrum$$b10$$kDKFZ
000128627 9131_ $$0G:(DE-HGF)POF3-315$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vImaging and radiooncology$$x0
000128627 9141_ $$y2017
000128627 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bONCOTARGET : 2015
000128627 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000128627 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000128627 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000128627 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000128627 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000128627 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000128627 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000128627 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bONCOTARGET : 2015
000128627 9201_ $$0I:(DE-He78)C060-20160331$$kC060$$lC060 Biostatistik$$x0
000128627 9201_ $$0I:(DE-He78)E010-20160331$$kE010$$lE010 Radiologie$$x1
000128627 980__ $$ajournal
000128627 980__ $$aVDB
000128627 980__ $$aI:(DE-He78)C060-20160331
000128627 980__ $$aI:(DE-He78)E010-20160331
000128627 980__ $$aUNRESTRICTED