August 2015, Vol 4, No 4

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Regulatory Processes Slow Application of Genetic Tests


Research into molecular biomarkers is bringing powerful insights to the identification of disease with considerable potential for prevention and treatment, but current regulatory paradigms may not be adequate to address this new potential, said Andrew Stainthorpe, PhD, at PMO Live 2015.

Stainthorpe, head of the National Health Services Research Development Unit, Bristol, UK, provided an overview of the regulatory landscape of precision medicine tests in the United States and European countries.

The growth in molecular biomarkers for precision medicine has been rapid. After biomarker discovery and development, “does it actually get into use?” he asked. “That’s where the regulatory and the HTA [health technology assessment] processes come into their own.”

He argued that the potential of biomarker technology has been slow to be realized. The growth in biomarker discovery has not translated into the introduction of biomarker technologies, such as companion and complementary diagnostics, into the marketplace. The result is an absence of a revolution of clinical care, he said.

The US Food and Drug Administration has the authority to assess genetic tests for safety and efficacy, but to date, it has only regulated the relatively small number of genetic tests sold to laboratories as kits. The Centers for Medicare & Medicaid Services regulates clinical laboratories; it does not examine whether the tests performed are clinically meaningful.

“For the most part, European markets are open to new genetic tests; as long as you get a CE mark, that’s the crucial step,” said Stainthorpe. “Various countries have taken different approaches to this, but in reality, there’s access to the tests. The United Kingdom is very open to this, and there are many tests being brought to market.”

The outcomes of economic appraisals of genetics tests have been very similar across Europe, resulting in few positive recommendations for the use of genetic tests, he said.

The National Institute for Health and Care Excellence (NICE) does its own technology appraisals and also has a diagnostic assessment program “that has not been terribly active,” he said. “Most of the outcomes are negative recommendations.” Positive NICE recommendations were granted for the use of dabrafenib for treating unresectable or metastatic BRAF V600 mutation–positive melanoma and for vemurafenib for treating locally advanced or metastatic BRAF V600 mutation–positive malignant melanoma. In an assessment of 10 epidermal growth factor receptor tyrosine kinase mutation tests in adults with locally advanced or metastatic non–small-cell lung cancer, 5 were recommended as options and 5 were considered to have insufficient data. Most recently, the PROGENSA PCA3 assay and Prostate Health Index for diagnosing prostate cancer were not recommended for use.

“The point I want to make is that there are not many going through the HTA processes successfully,” he said.

“I have some various reservations about the paradigms that are currently being used; when you’re getting down to very small “N’s” or “N’s-of-1”…and whether there needs to be a different approach to the valuing of medicines and how you pay for them,” Stainthorpe said.

The Payers’ Perspective and the Fallacy of N-of-1

Michael Kolodziej, MD, addressed the payers’ perspective to precision medicine. “The health plan sees that cancer is expensive, and it’s going up really fast,” he said. “And people don’t think they are getting a whole heck of a lot for their money.” One reason is the lack of correlation between the price of a cancer drug and the value it brings in terms of progression-free or overall survival.

He issued a plea for developing biomarkers that help us get the right drug to the right patient at the right time. “Anything less is a disaster,” said Kolodziej, National Medical Director, Oncology Solutions, Aetna.

Kolodziej contrasted the viability of N-of-1 drug evaluations with evidence-based cancer treatment pathways, also known as population management. “If we regress to N-of-1, we will never know what to do with any patient who walks into the office to see us,” he said. “It’s N of just the right amount of people like the one in front of you to help you make a decision.”

Personalized medicine goes beyond the genome and must consider the phenotype. “Context actually matters,” he said. “We need to be able to sort the patients that we take care of into groups that we can make a difference for, and we should use all the data that are at our disposal.” In this regard, information technology is perhaps just as important a component of precision medicine as is next-generation sequencing.

To be able to assess the accuracy and clinical relevance of a genomic test, assessment of analytical performance, clinical validity, clinical utility, and economic value is a necessity. These measures are interrelated, as analytic performance must be evaluated in the context of clinical use, and clinical validity must be assessed in the context of analytic performance.

“We need to get the data in the public domain so people can make the right decision for their patients,” said Kolodziej. Instead, “phonebooks” of genetic mutations are often presented, and clinicians have no idea how to use this information to treat patients.

The view of cancer as a linear disease in which treatment is chosen based on a known mutation is simplistic and doesn’t necessarily lead to better outcomes, he argued. He pointed to the American Society of Clinical Oncology’s CancerLinQ as one way to obtain better data. Patients undergoing genomic profiling and receiving treatment based on the results are entered into a national registry in which outcomes are tracked.

Payers are catching on to the value of pathways, he said. A pilot study to measure adherence to evidence-based medicine found that prior to institution of a clinical decision support system, for every 100 patients treated in 6 oncology practices over 6 months, only 62 patients received an evidence-based treatment plan. Following use of the clinical decision support system, adherence to evidence-based treatment increased to 87 of 100 patients over 6 months, or a 43% relative improvement.

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