The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease
than an illness where a fever accompanies acute infection and resolution of the fever signals a shift to resolving the infection.
In an ideal setting, biomarkers reflect disease course and activity; many good biomarkers are useful in monitoring disease process and complications. In the diagnosis and management of prostate cancer, for example, prostate-specific antigen (PSA) can be measured in a patient’s blood, and PSA levels can be followed as an indicator of whether the cancer is growing or responding to treatment. However, this example illustrates several challenges of using biomarkers. PSA may be elevated in some patients because they have prostate cancer, but it can also be elevated for other reasons. One important finding that has been reported recently is that PSA is not necessarily a good biomarker for population-wide screening for prostate cancer (Sardana et al., 2008). This illustrates the point that biomarkers are effective only to the degree that they are used in the appropriate context. It is critical to note that even a perfect biomarker cannot, with certainty, be used in place of patient outcomes in the evaluation of an intervention.
One step in supporting regulators is to institute an evidence-based, transparent process for biomarker evaluation. Biomarker evaluation is often thought of as two unlinked steps: analytical validation of biomarker tests and biomarker qualification. Biomarker qualification is the evidence-based process of linking a biomarker with one or more clinical endpoints. Decisions to use biomarkers are dependent on the intended applications. Currently, the evaluation of biomarkers is not based on uniform standards or processes, but rather on the gradual development of consensus in the scientific community. The potential value and impact of a more uniform and transparent evaluation process was noted in the 2007 Institute of Medicine (IOM) report, Cancer Biomarkers: The Promises and Challenges ofImproving Detection and Treatment (IOM, 2007), which recommended that government agencies and non-governmental stakeholders “should work together to develop a transparent process for creating well-defined consensus standards and guidelines for biomarker development, validation, qualification, and use to reduce the uncertainty in the process of development and adoption.”
The Cancer Biomarkers recommendation gains even more weight when considered with the emergence of pharmacogenetics, pharmacogenomics, and all of the promising medical breakthroughs of personalized medicine. Pharmacogenetics is the science of understanding how an individual’s genes may interact to impact drug function and metabolism. Personalized determination of drugs that will work for given patients and dosing based on their metabolic profiles has the potential to decrease unnecessary or not helpful treatments and decrease adverse effects from treatments when they are helpful. Pharmacogenomics is the science of understanding genetic variations between populations in disease incidence, progression,