000144333 001__ 144333
000144333 005__ 20240229112620.0
000144333 0247_ $$2doi$$a10.1186/s12885-019-5842-7
000144333 0247_ $$2pmid$$apmid:31296182
000144333 0247_ $$2pmc$$apmc:PMC6624952
000144333 0247_ $$2altmetric$$aaltmetric:63450101
000144333 037__ $$aDKFZ-2019-01786
000144333 041__ $$aeng
000144333 082__ $$a610
000144333 1001_ $$0P:(DE-He78)9b2a61b2abe4a64ca23b6783b7c4fe63$$aAlwers, Elizabeth$$b0$$eFirst author$$udkfz
000144333 245__ $$aExternal validation of molecular subtype classifications of colorectal cancer based on microsatellite instability, CIMP, BRAF and KRAS.
000144333 260__ $$aHeidelberg$$bSpringer$$c2019
000144333 3367_ $$2DRIVER$$aarticle
000144333 3367_ $$2DataCite$$aOutput Types/Journal article
000144333 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1634561975_21237
000144333 3367_ $$2BibTeX$$aARTICLE
000144333 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000144333 3367_ $$00$$2EndNote$$aJournal Article
000144333 520__ $$aCompeting molecular classification systems have been proposed to complement the TNM staging system for a better prediction of survival in colorectal cancer (CRC). However, validation studies are so far lacking. The aim of this study was to validate and extend previously published molecular classifications of CRC in a large independent cohort of CRC patients.CRC patients were recruited into a population-based cohort study (DACHS). Molecular subtypes were categorized based on three previously published classifications. Cox-proportional hazard models, based on the same set of patients and using the same confounders as reported by the original studies, were used to determine overall, cancer-specific, or relapse-free survival for each subtype. Hazard ratios and confidence intervals, as well as Kaplan-Meier plots were compared to those reported by the original studies.We observed similar patterns of worse survival for the microsatellite stable (MSS)/BRAF-mutated and MSS/KRAS-mutated subtypes in our validation analyses, which were included in two of the validated classifications. Of the two MSI subtypes, one defined by additional presence of CIMP-high and BRAF-mutation and the other by tumors negative for CIMP, BRAF and KRAS-mutations, we could not confirm associations with better prognosis as suggested by one of the classifications. For two of the published classifications, we were able to provide results for additional subgroups not included in the original studies (men, other disease stages, other locations).External validation of three previously proposed classifications confirmed findings of worse survival for CRC patients with MSS subtypes and BRAF or KRAS mutations. Regarding MSI subtypes, other patient characteristics such as stage of the tumor, may influence the potential survival benefit. Further integration of methylation, genetic, and immunological information is needed to develop and validate a comprehensive classification that will have relevance for use in clinical practice.
000144333 536__ $$0G:(DE-HGF)POF3-313$$a313 - Cancer risk factors and prevention (POF3-313)$$cPOF3-313$$fPOF III$$x0
000144333 588__ $$aDataset connected to CrossRef, PubMed,
000144333 7001_ $$aBläker, Hendrik$$b1
000144333 7001_ $$0P:(DE-He78)6c2a1ea8cce3580fe2d1c1df120a92b9$$aWalter, Viola$$b2$$udkfz
000144333 7001_ $$0P:(DE-He78)bbfe0ebad1e3b608bca2b49d4f86bd09$$aJansen, Lina$$b3$$udkfz
000144333 7001_ $$aKloor, Matthias$$b4
000144333 7001_ $$aArnold, Alexander$$b5
000144333 7001_ $$aSieber-Frank, Julia$$b6
000144333 7001_ $$aHerpel, Esther$$b7
000144333 7001_ $$aTagscherer, Katrin E$$b8
000144333 7001_ $$aRoth, Wilfried$$b9
000144333 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b10$$udkfz
000144333 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b11$$udkfz
000144333 7001_ $$0P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f$$aHoffmeister, Michael$$b12$$eLast author$$udkfz
000144333 773__ $$0PERI:(DE-600)2041352-X$$a10.1186/s12885-019-5842-7$$gVol. 19, no. 1, p. 681$$n1$$p681$$tBMC cancer$$v19$$x1471-2407$$y2019
000144333 909CO $$ooai:inrepo02.dkfz.de:144333$$pVDB
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)9b2a61b2abe4a64ca23b6783b7c4fe63$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)6c2a1ea8cce3580fe2d1c1df120a92b9$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)bbfe0ebad1e3b608bca2b49d4f86bd09$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aDeutsches Krebsforschungszentrum$$b10$$kDKFZ
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aDeutsches Krebsforschungszentrum$$b11$$kDKFZ
000144333 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f$$aDeutsches Krebsforschungszentrum$$b12$$kDKFZ
000144333 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
000144333 9141_ $$y2019
000144333 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBMC CANCER : 2017
000144333 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000144333 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000144333 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000144333 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central
000144333 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000144333 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000144333 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Open peer review
000144333 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ
000144333 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000144333 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000144333 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000144333 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000144333 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000144333 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine
000144333 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000144333 9201_ $$0I:(DE-He78)C070-20160331$$kC070$$lC070 Klinische Epidemiologie und Alternf.$$x0
000144333 9201_ $$0I:(DE-He78)C120-20160331$$kC120$$lPräventive Onkologie$$x1
000144333 9201_ $$0I:(DE-He78)C020-20160331$$kC020$$lC020 Epidemiologie von Krebs$$x2
000144333 9201_ $$0I:(DE-He78)L101-20160331$$kL101$$lDKTK Heidelberg$$x3
000144333 980__ $$ajournal
000144333 980__ $$aVDB
000144333 980__ $$aI:(DE-He78)C070-20160331
000144333 980__ $$aI:(DE-He78)C120-20160331
000144333 980__ $$aI:(DE-He78)C020-20160331
000144333 980__ $$aI:(DE-He78)L101-20160331
000144333 980__ $$aUNRESTRICTED