Abstract
Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical research. In this paper, we highlight several important aspects related to study design and statistical analysis for clinical research incorporating biomarkers. We describe the typical and current study designs for exploring, detecting, and utilizing biomarkers. Furthermore, we introduce statistical issues such as confounding and multiplicity for statistical tests in biomarker research.
Highlights
In recent years, biomarkers have played an increasingly important role in drug discovery, understanding the mechanism of action of a drug, investigating efficacy and toxicity signals at an early stage of pharmaceutical development, and in identifying patients likely to respond to treatment
A diagnostic test for the UGT1A1*28 genotype for irinotecan dosing was approved by the Food and Drug Administration (FDA) in 2005, and the test could be useful for identifying patients with a greater risk of developing irinotecan toxicity
Interested readers can refer to the study published by Fleming and DeMets [22], which provides many examples of surrogate endpoints and which has pointed out that these surrogate endpoints often fail in formal statistical validation
Summary
Biomarkers have played an increasingly important role in drug discovery, understanding the mechanism of action of a drug, investigating efficacy and toxicity signals at an early stage of pharmaceutical development, and in identifying patients likely to respond to treatment. Biomarkers have been utilized to personalize medication or healthcare and in the safety assessment of drugs in clinical practice. A vast number of clinical biomarker studies are conducted and reported. The results in highly cited biomarker studies often significantly overestimate their findings, as seen from meta-analyses of these studies. Many of these studies were relatively small and among the first to report on the association of interest. We first introduce the definition, classification, and some examples of biomarkers in clinical research. We review the typical and current study designs of clinical research using biomarkers in practical studies.
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