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Oncologist. 2014 Aug;19(8):886-91. doi: 10.1634/theoncologist.2014-0061. Epub 2014 Jul 7.

Biomarker validation: common data analysis concerns.

Author information

1
The University of Texas MD Anderson Cancer Center, Houston, Texas, USA joensor@mdanderson.org.

Abstract

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.

KEYWORDS:

Biomarker; Confounding factors; Selection bias; Validation studies

PMID:
25001264
PMCID:
PMC4122484
DOI:
10.1634/theoncologist.2014-0061
[Indexed for MEDLINE]
Free PMC Article

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