A multi-step classifier addressing cohort heterogeneity improves performance of prognostic biomarkers in three cancer types.

ABSTRACT: Cancer 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 misclassif

SUBMITTER: Patrick E 

PROVIDER: S-EPMC5356843 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature