Friday, October 31, 2014

Clinical evidence support for biomarkers on FDA-approved drug labels

A recent article by Wang et al. in JAMA Internal Medicine reviews the clinical evidence support found on FDA-approved drug labels that are listed on the FDA's Table of Pharmacogenomic Biomarkers in Drug Labeling.  The authors found that many labels on the list did not contain, or reference, "convincing evidence" of the biomarker's clinical validity or utility.  The authors used published guidelines from the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group to grade the evidence.

October's SNPits summary from the University of Florida's Personalized Medicine Program highlights this article and provides a discussion about the clinical implications and some limitations of the paper.  They note that post-market label updates regarding safety decisions will often depend on retrospective data that will fall short of proving clinical utility. Additionally, the clinical evidence provided on labels may not reflect the totality of the available evidence because it is difficult for label revisions to keep up with the pace of emerging literature.

Almost a year ago, PharmGKB blogged about lack of clarity regarding the actionability of pharmacogenomic information on FDA-approved drug labels.  This is a separate issue from that of clinical evidence support for biomarker information on the labels discussed in the JAMA Internal Medicine article.  Both issues suggest the need for clearer language and guidance for clinicians on labels. 

As the SNPits summary points out, resources do exist for clinicians to gather information outside of what is provided on the label.  "Prescribers frequently rely on data sources other than the package insert in clinical decision making, including drug databases, published information in guidelines, journal articles, and others." Though there is room for improvement on FDA-approved drug labels, the provided pharmacogenomic information can be integrated with other information clinicians use while making prescribing decisions.