For the most part, tests that are supposed to help clinicians decide which personalized drugs are appropriate for a given patient haven’t lived up to their billing, according to a new study from the Tufts Center for the Study of Drug Development at Tufts University School of Medicine.

Number of plans that say companion diagnostic tests are clinically useful (14 insurers)

Joshua Cohen, PhD, and colleagues reviewed eight high-profile drugs and their companion diagnostic tests to determine which tests could be used to guide a prescriber in selecting a drug or in determining dosing tailored to a person’s genetic makeup. This field, pharmacogenomics, is more commonly known as personalized medicine. It explores the ways in which genetic variation in an individual can determine whether a patient will benefit from a drug, will have an adverse reaction to the drug, or will have no reaction at all.

Cohen, a senior research fellow at the center, says that there are clinical, economic, and regulatory obstacles associated with personalized medicine but that the biggest is “a lack of clinically useful diagnostics . . . which leads to an evidence gap in terms of knowledge of drug and diagnostic clinical effectiveness.”

But the future is promising, according to Cohen: He points to “an increase in comparative effectiveness research that may help to close the evidence gap.”

Because of the lack of clinical effectiveness knowledge, many insurers express doubts about companion diagnostics and their clinical usefulness. In other words, it may not matter to payers that a test accurately identifies a subpopulation that has a particular genetic mutation if it does not lead to improved health outcomes.

“Many of these tests were not considered diagnostically accurate — that surprised me. These are FDA-approved tests. Payers were not reluctant to pay for the drug, but they were reluctant to the pay for the test.” He emphasizes that “part of the problem is that a lot of the evidence is not actionable yet. There are very few decision aids or algorithms for providers.”

In conducting his research, Cohen was surprised about the lack of transparency insurers exhibit to members when dealing with companion diagnostics. “Insurers don’t normally tell the average member which diagnostic test they’re paying for. They’ll tell the member about the medication they pay for, the cost tier, prior authorization, step therapy, and all those things. That’s all available to the beneficiary. But insurers will not tell a member about the companion diagnostic and whether or not it’s covered by the plan.”

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