Biomarker research parallels therapeutic research, with all the same potential biases. Therefore, it is critical in biomarker research to adhere to statistical Navitoclax Bcl-xL principles and follow a sound statistical methodology to minimize bias and maximize precision.In this paper, we first introduce the definition, classification, and some examples of biomarkers in clinical research. Second, we review the typical and current study designs of clinical research using biomarkers in practical studies. Furthermore, we describe statistical issues such as confounding and multiplicity for statistical tests in biomarker research. The final section is a brief summary.2.
?Definition and Inhibitors,Modulators,Libraries Classification of Inhibitors,Modulators,Libraries BiomarkersAn expert working group at the National Institutes of Health (NIH) has defined a biological marker or biomarker as ��a characteristic that is objectively measured and evaluated as an Inhibitors,Modulators,Libraries indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention�� [2]. According to this definition, biomarkers cover a rather wide range of data types, for example, biochemistry laboratory tests on blood, function testing, electrocardiographic testing, and image information such as computed tomography (CT), magnetic resonance imaging (MRI) and positron-emission tomography (PET). Typical examples of such biomarkers are listed in Table 1 [3�C10].Table 1.Examples of biomarker use.Biomarkers can be broadly classified into prognostic biomarkers, predictive biomarkers, pharmacodynamic biomarkers, and surrogate endpoints [5,11].
The biomarker types have been illustrated in a simple Inhibitors,Modulators,Libraries manner in Figure 1. In this paper, we have focused on prognostic and predictive biomarkers and have not discussed pharmacodynamic biomarkers or surrogate endpoints in great detail.Figure 1.Biomarker types. (a) Prognostic biomarker, (b) predictive biomarker, (c) pharmacodynamic biomarker, (d) surrogate endpoint. ��S�� and ��T�� denote standard and test treatments, respectively.2.1. Prognostic BiomarkersA prognostic biomarker classically identifies patients with differing risks of a specific outcome, such as progression or death [12,13]. Recently, the prognostic biomarker was defined as a single trait or signature of traits that separates a population with respect to the outcome of interest, regardless of the types of therapies or treatments [14].
For example, Dacomitinib under this definition, if a specified biomarker were prognostic, the outcome (clinical response) of patients with biomarker-positive status would be better than that of patients with biomarker-negative status in both the test and standard treatments. Additionally, the differences of the outcome between test and standard treatments between the www.selleckchem.com/products/CHIR-258.html biomarker-positive and biomarker-negative populations in Figure 1(a) would be uniform. According to Chakravarty et al.