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Using CER to Evaluate Companion Diagnostics


Eileen Koutnik-Fotopoulos

Boston—Personalized medicine is playing an increasing role in drug development, and many drugs already have biomarkers to treat diseases, particularly cancer, and more are on the horizon, according to Robert Dubois, MD, PhD, chief financial officer, National Pharmaceutical Council, who was 1 of 3 presenters to discuss evaluating companion diagnostics using comparative effectiveness research (CER) at a session during the AMCP meeting.

Dr. Dubois cited data from the Personalized Medicine Coalition’s 2014 publication Personalized Medicine by the Numbers that quantifies the progress of personalized medicine. The report indicated that 137 FDA-approved drugs have pharmacogenomic information in their labeling, and 155 pharmacogenomic biomarkers are included on the FDA-approved drug label.

Furthermore, the report highlighted the percentage of treatments that rely on biomarker data:
• 30% of all treatments in late clinical development
• 50% of all treatments in early clinical development
• 60% of all treatments in preclinical development

Companion diagnostic tests (CDTs) are a growing and vital technology in the effectiveness of many drug therapies and show promise in the emerging science of personalized medicine. When used appropriately, these tests offer numerous benefits, such as improved effectiveness. Despite the potential benefits, CDTs enter the market with different levels of evidence to support their use in routine practice, posing challenges for managed care. While managed care needs to assess evidence for CDTs associated with targeted treatment, the assessment is challenging. Managed care needs to examine what factors to consider, what evidence is relevant, and when is it worthwhile to perform an in-depth evaluation, according to the presentation.

The methods of CER can be used to address some of these concerns. “CER is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care,” said Dr. Dubois. He said evidence can help determine value of companion diagnostics.

Personalized medicine is more than just genetic tests. It includes any means of predicting individual responses and varying treatment accordingly, explained John B. Watkins, PharmD, MPh, BCPS, pharmacy manager, Premera Blue Cross. He focused his presentation on the payer perspective on companion diagnostics.

Dr. Watkins identified methodologic challenges for payers in evaluating the evidence, which includes small patient numbers, new study types (eg, whole genome sequencing), utility and affordability, and generalizability of study results. He said payers want evidence that demonstrates the clinical utility of tests and companion drugs and the cost-effectiveness of different testing strategies.

A need exists for decision-makers to have a framework for assessing the value of CDTs and to understand the complex factors and their interactions that affect the value of CDTs. David Veenstra, PharmD, PhD, professor, department of dermatology, University of Washington, rounded out the session by discussing a tool to assist managed care decision-makers in evaluating companion diagnostics—the Companion Diagnostic Assessment Tool (CAT). The tool was designed for individuals within managed care organizations tasked with the clinical and economic review of an emerging CDT, said Dr. Veenstra. It was also designed to complement existing resources, such as the AMCP Companion Diagnostics Addendum.
CAT was tested with a broad range of test types, with examples including crizotinib and anaplastic lymphoma kinase testing and the OncotypeDX breast cancer assay. The framework for CAT was also evaluated for relevance and ease of use via cognitive interviews with representatives from managed care and test developers, explained Dr. Veenstra.

“The CDT assessment tool offers a triage process for payers,” he said. “It identifies when a full technology review is warranted and identifies key value drivers for CDTs.”—Eileen Koutnik-Fotopoulos

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