000140844 001__ 140844
000140844 005__ 20240229105117.0
000140844 0247_ $$2doi$$a10.1016/j.bbi.2018.05.009
000140844 0247_ $$2pmid$$apmid:29763737
000140844 0247_ $$2ISSN$$a0889-1591
000140844 0247_ $$2ISSN$$a1090-2139
000140844 0247_ $$2altmetric$$aaltmetric:42106668
000140844 037__ $$aDKFZ-2018-01599
000140844 041__ $$aeng
000140844 082__ $$a150
000140844 1001_ $$aKühl, T.$$b0
000140844 245__ $$aValidation of inflammatory genetic variants associated with long-term cancer related fatigue in a large breast cancer cohort.
000140844 260__ $$aOrlando, Fla.$$bAcademic Press$$c2018
000140844 3367_ $$2DRIVER$$aarticle
000140844 3367_ $$2DataCite$$aOutput Types/Journal article
000140844 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1539607137_22523
000140844 3367_ $$2BibTeX$$aARTICLE
000140844 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000140844 3367_ $$00$$2EndNote$$aJournal Article
000140844 520__ $$aStudies to date have reported several associations between single nucleotide polymorphisms (SNPs) and cancer related fatigue (CRF), but have been limited by small sample sizes, missing adjustment for relevant covariates or multiple testing, as well as varying CRF definitions, i.e. time and method of assessment. This study aimed to validate previously reported associations using the largest independent breast cancer sample to date and to evaluate further functional cytokine variants in relation to total CRF and all relevant CRF subdomains (physical, cognitive, and affective CRF).45 candidate SNPs in inflammatory pathway genes were selected based on previous reports (16 SNPs) or regulatory function (29 SNPs). Breast cancer patients recruited between 2002 and 2005 provided information on CRF at first follow-up (FU1) (N = 1389) and second follow-up (FU2) (N = 950), a median of 6.2 years and 11.7 years respectively after diagnosis. SNP associations were assessed using linear regression models on CRF scores separately for FU1 and FU2. Additionally, patients with persistent fatigue (fatigued at both time-points) were compared to those never fatigued using logistic regression models (N = 684). All analyses were adjusted for relevant covariates. Secondary analyses were conducted for CRF subdomains.For total CRF none of the previously reported associations were confirmed after correction for multiple testing. The p-value distribution of all SNPs was not different than the one expected by chance. Analyses of CRF subdomains yielded a significant association between TNF-α rs3093662 and persistent physical CRF (Odds Ratio (OR) = 3.23, 95% Confidence Interval (CI) = 1.71-6.10, p = 0.0003).We were unable to confirm previously reported findings, suggesting that individual SNPs are unlikely to be of clinical utility. Further investigations in well powered studies are warranted, which consider genetic heterogeneity according to subdomains of CRF.
000140844 536__ $$0G:(DE-HGF)POF3-313$$a313 - Cancer risk factors and prevention (POF3-313)$$cPOF3-313$$fPOF III$$x0
000140844 588__ $$aDataset connected to CrossRef, PubMed,
000140844 7001_ $$0P:(DE-He78)6b04712f3afe72044d496a25505cb1ea$$aBehrens, S.$$b1$$udkfz
000140844 7001_ $$0P:(DE-He78)bce1fdec5ce564e2666156d96aeabec9$$aJung, A. Y.$$b2$$udkfz
000140844 7001_ $$aObi, N.$$b3
000140844 7001_ $$aThöne, K.$$b4
000140844 7001_ $$0P:(DE-He78)2def8f8594c8f797f5ed4398258c6cac$$aSchmidt, Martina$$b5$$udkfz
000140844 7001_ $$aBecher, H.$$b6
000140844 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b7$$eLast author$$udkfz
000140844 773__ $$0PERI:(DE-600)1462491-6$$a10.1016/j.bbi.2018.05.009$$gVol. 73, p. 252 - 260$$p252 - 260$$tBrain, behavior and immunity$$v73$$x0889-1591$$y2018
000140844 909CO $$ooai:inrepo02.dkfz.de:140844$$pVDB
000140844 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)6b04712f3afe72044d496a25505cb1ea$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000140844 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)bce1fdec5ce564e2666156d96aeabec9$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000140844 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)2def8f8594c8f797f5ed4398258c6cac$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000140844 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000140844 9131_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0
000140844 9141_ $$y2018
000140844 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000140844 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000140844 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000140844 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000140844 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBRAIN BEHAV IMMUN : 2017
000140844 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000140844 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000140844 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000140844 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000140844 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000140844 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000140844 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences
000140844 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000140844 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bBRAIN BEHAV IMMUN : 2017
000140844 9201_ $$0I:(DE-He78)C020-20160331$$kC020$$lEpidemiologie von Krebserkrankungen$$x0
000140844 9201_ $$0I:(DE-He78)G210-20160331$$kG210$$lBewegung, Präventionsforschung und Krebs$$x1
000140844 980__ $$ajournal
000140844 980__ $$aVDB
000140844 980__ $$aI:(DE-He78)C020-20160331
000140844 980__ $$aI:(DE-He78)G210-20160331
000140844 980__ $$aUNRESTRICTED