The use of biomarkers in basic and clinical research as well as in clinical practice has become so commonplace that their presence as primary endpoints in clinical trials is now accepted almost without question (Strimbu & Tavel 2011) and 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 (Gosho et al. 2012). Therefore, biomarkers have been utilized to personalize medication or healthcare and in the safety assessment of drugs in clinical practice.
The National Institutes of Health Biomarkers Definitions Working Group (NIH) defined a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (Biomarkers Definitions Working 2001).
Examples of biomarkers include everything from pulse and blood pressure through basic chemistries to more complex laboratory tests of blood and other tissues (Strimbu & Tavel 2011). Assessment of these biomarkers is complex but valuable in perioperative and critical care medicine as markers of diagnosis, disease severity, and risk (Ray et al. 2010).
There are several important hierarchical steps in demonstrating the clinical interest of a biomarker (Ray et al. 2010):
- Demonstrate that the biomarker is significantly modified in diseased patients as compared to control.
- Assess the diagnostic properties of the biomarkers.
- Compare the diagnostic properties of the biomarker to existing tests.
- Demonstrate that the diagnostic properties of the biomarker increase the ability of the physician to make a decision; this might be difficult to analyze because timing of diagnosis may be crucial and not easy to identify.
- Assess the usefulness of the biomarker, which should be clearly distinguished to the quality of diagnostic information provided. Assessment of the usefulness mainly involves both characteristics of the test itself such as cost, invasiveness, technical difficulties, rapidity, and characteristics of the clinical context (prevalence of the disease, consequences of outcome, cost, and consequences of therapeutic options).
- Demonstrate that the measurement of the biomarkers modifies outcome (intervention studies). However, intervention studies are lacking for many novel biomarkers or give conflicting results for others.
Biomarkers can be broadly classified into prognostic biomarkers, predictive biomarkers, pharmacodynamic biomarkers, and surrogate endpoints (Gosho et al. 2012).
A prognostic biomarker identifies patients with differing risks of a specific outcome, such as progression or death. 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 (Gosho et al. 2012).
A predictive biomarker predicts the differential outcome of a particular therapy or treatment – only biomarker-positive patients will respond to the specific treatment or to a greater degree than those who are biomarker negative (Sargent et al. 2005).
The biomarker could be used as a pharmacodynamic biomarker (biomarker of the drug activity) to demonstrate proof of principle and be used to optimize the dosing schedule of the drug during the earlier phases of the drug development program (in vitro studies, animal experiments, and phase I trials), while clinical biomarkers are used in phase II and III clinical trials (Gosho et al. 2012).
A surrogate endpoint is defined as “a biomarker intended to substitute for a clinical endpoint”. A clinical investigator uses epidemiological, therapeutic, pathophysiological, or other scientific evidence to select a surrogate endpoint that is expected to predict clinical benefit or lack of benefit or harm (Biomarkers Definitions Working 2001). In clinical trials, a surrogate endpoint (or marker) is a measure of the effect of a certain treatment that may correlate with a true endpoint but does not necessarily have a guaranteed relationship with it (Gosho et al. 2012).
The use of biomarkers, and in particular laboratory-measured biomarkers, in clinical research is somewhat newer, and the best approaches to this practice are still being developed and refined (Strimbu & Tavel 2011). However, despite all the problems of morphology based assays such as immunohistochemistry (IHC), when a protein is the target, identification of that protein by IHC in tissue remains the gold standard for tumour biomarkers and becomes extremely valorous when the proteins undergo post-translational modification such as phosphorylation and/or are up regulated (Dunstan et al. 2011).
Biomarkers Definitions Working, 2001. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clinical pharmacology and therapeutics, 69(3), pp.89–95.
Dunstan, R.W. et al., 2011. The use of immunohistochemistry for biomarker assessment–can it compete with other technologies? Toxicologic pathology, 39(6), pp.988–1002.
Gosho, M., Nagashima, K. & Sato, Y., 2012. Study Designs and statistical analyses for biomarker research. Sensors (Switzerland), 12(7), pp.8966–8986.
Ray, P. et al., 2010. Statistical evaluation of a biomarker. Anesthesiology, 112(4), pp.1023–1040.
Sargent, D.J. et al., 2005. Clinical Trial Designs for Predictive Marker Validation in Cancer Treatment Trials. Journal of Clinical Oncology, 23(9), pp.2020–2027.
Strimbu, K. & Tavel, J. a, 2011. What are Biomarkers? Curr Opin HIV AIDS, 5(6), pp.463–466.