4.7 Article

Biomarker Validation: Common Data Analysis Concerns

Journal

ONCOLOGIST
Volume 19, Issue 8, Pages 886-891

Publisher

WILEY
DOI: 10.1634/theoncologist.2014-0061

Keywords

Biomarker; Selection bias; Confounding factors; Validation studies

Categories

Funding

  1. National Institutes of Health through MD Anderson Cancer Center [CA016672]

Ask authors/readers for more resources

Biomarker validation, like any other confirmatory process based on statistical methodology, must discern associations that occur by chance from those reflecting true biological relationships. Validity of a biomarker is established by authenticating its correlation with clinical outcome. Validated biomarkers can lead to targeted therapy, improve clinical diagnosis, and serve as useful prognostic and predictive factors of clinical outcome. Statistical concerns such as confounding and multiplicity are common in biomarker validation studies. This article discusses four major areas of concern in the biomarker validation process and some of the proposed solutions. Because present-day statistical packages enable the researcher to address these common concerns, the purpose of this discussion is to raise awareness of these statistical issues in the hope of improving the reproducibility of validation study findings. The Oncologist 2014; 19: 886-891

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available