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dc.contributor.authorPatrick, Ellisen_US
dc.contributor.authorSchramm, Sarah-Janeen_US
dc.contributor.authorOrmerod, John Ten_US
dc.contributor.authorScolyer, Richard Aen_US
dc.contributor.authorMann, Graham Jen_US
dc.contributor.authorMueller, Samuelen_US
dc.contributor.authorYang, Jean Y.H.en_US
dc.date.accessioned2017-05-01T19:26:34Z
dc.date.issued2017en_US
dc.identifier.citationPatrick, Ellis, Sarah-Jane Schramm, John T Ormerod, Richard A Scolyer, Graham J Mann, Samuel Mueller, and Jean Y.H. Yang. 2017. “A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types.” Oncotarget 8 (2): 2807-2815. doi:10.18632/oncotarget.13203. http://dx.doi.org/10.18632/oncotarget.13203.en
dc.identifier.issnen
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:32630432
dc.description.abstractCancer research continues to highlight the extensive genetic diversity that exists both between and within tumors. This intrinsic heterogeneity poses one of the central challenges to predicting patient clinical outcome and the personalization of treatments. Despite progress in some individual tumor types, it is not yet possible to prospectively, accurately classify patients by expected survival. One hypothesis proposed to explain this is that the prognostic classifiers developed to date are insufficiently sensitive and specific; however it is also possible that patients are not equally easy to classify by any given biomarker. We demonstrate in a cohort of 45 AJCC stage III melanoma patients that clinico-pathologic biomarkers can identify those patients that are most likely to be misclassified by a molecular biomarker. The process of modelling the classifiability of patients was then replicated in a cohort of 49 stage II breast cancer patients and 53 stage III colon cancer patients. A multi-step procedure incorporating this information not only improved classification accuracy but also indicated the specific clinical attributes that had made classification problematic in each cohort. These findings show that, even when cohorts are of moderate size, including features that explain the patient-specific performance of a prognostic biomarker in a classification framework can improve the modelling and estimation of survival.en
dc.language.isoen_USen
dc.publisherImpact Journals LLCen
dc.relation.isversionofdoi:10.18632/oncotarget.13203en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356843/pdf/en
dash.licenseLAAen_US
dc.subjectbiomarkeren
dc.subjectclassificationen
dc.subjectcanceren
dc.subjectpathologyen
dc.subjectprognosisen
dc.titleA multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer typesen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalOncotargeten
dash.depositing.authorPatrick, Ellisen_US
dc.date.available2017-05-01T19:26:34Z
dc.identifier.doi10.18632/oncotarget.13203*
dash.contributor.affiliatedPatrick, Ellis


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