Distinguishing prognostic and predictive biomarkers: an information theoretic approach.

ABSTRACT:

Motivation

The identification of biomarkers to support decision-making is central to personalized medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. Th

SUBMITTER: Sechidis K 

PROVIDER: S-EPMC6157098 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature