Diagnostics & Imaging Week National Editor
One of the newer waves in medicine is the "personalized" approach, the provision of therapy that exactly fits a particular patient, with a particular condition. Personalized medicine is being touted as a path to much improved care outcomes and rejects the broad-brush, one-size-fits-all approach, which is an increasing target of criticism.
If effective, it avoids both the lack of efficacy for a generalized therapy and the potential side effects of a therapy that may impact some individuals.
One of the particular sub-sectors of the "personalized" approach is pharmacogenetic analysis, the genetic testing of a patient to help guide the best pharmaceutical therapy and avoid adverse events. Besides offering the "warm fuzzies," one might say, of an obviously beneficial strategy for patients, the approach combines with the "whiz-bang," one might also say, of the hot new field of genomic science.
But there is – to coin still another phrase – a new "sheriff" in town, in the form of increased emphasis on cost-effectiveness.
Yes, these are great new trends, but do they pass the "keeping-costs-down" test? Conversely, will cost-capping efforts keep good therapies from reaching patients?
No, is the answer to the first of these questions in a new, and very narrow, study of a pharmacogenetic approach for the use of the blood thinner warfarin.
Led by researchers at the University of Cincinnati (UC), the study – "Cost-Effectiveness of Using Pharmacogenetic Information in Warfarin Dosing for Patients With Nonvalvular Atrial Fibrillation" – concludes that the large expense of the test, and the required associated care, is not worth the benefit.
Warfarin is commonly prescribed to prevent blood clotting in patients with atrial fibrillation (AF), and genetic testing has been proposed as a method for guiding initial dosing of the drug.
The study concludes that this pharmacogenetic approach is not cost-effective across the AF patient population, though it may be appropriate for patients at higher risk for major bleeding and where the test is available to provide fast results.
Mark Eckman, MD, professor of medicine at UC and lead investigator of the study, noted that the use of genetic testing for warfarin use in AF patients was suggested in labeling changes for the drug made by the FDA in 2007. But he told Diagnostics & Imaging Week that the study indicated that this particular application is clearly not standard of care, "at this point."
He summarized the conclusions by citing the high expense of the test (quoted in the study as, on average, $400, along with a range of expenses for associated medical care and follow-up), noting also that the test is often not readily available and that delays in test results mean delayed delivery of therapy.
Overall, the study concludes that use of the test, while providing better outcomes for some patients, translates to a cost of $170,000 for every Quality-Adjusted Life Year (QALY).
He declined to address the question of whether an emphasis on cost-effectiveness studies would block use of pharmacogenetic testing for patients. But he said that the new study addresses the efficacy of test use, not just cost.
He went on to explain the basis for the pharmacogenetic approach in this case:
"There are certain genes that are known to contribute to an increased sensitivity to warfarin," he said, and that the genetic testing is intended to "help guide the initial, and possibly lower, dose of warfarin for patients found to possess certain variants of the genes cytochrome P450 CYP2C9 and vitamin K epoxide reductase, or VKORC1."
The researchers performed a meta-analysis of the clinical studies published to date to determine the degree to which pharmacogenetic-guided dosing decreases major bleeds in this particular patient group, when compared with standard induction of treatment with warfarin.
But there are only three such studies, and the analysis concludes that the "putative reduction" of bleeding found in those studies was not statistically significant.
And in the conclusion of their study, the researchers make a variety of recommendations for validating the robustness of future studies, "such as the COAG trial funded by the National Institutes of Health" to determine the usefulness of this type of testing, looking, for instance, at "duration of benefit."
In the cost-analysis portion of the study, the researchers say that the $170,000-per-QALY cost of using the test is far above the "willingness-to-pay threshold of $50,000 per QALY."
The study conclusions also note that before publication of the three studies, examined in the meta-analysis, one estimate put the savings resulting from wafarin pharmacogenomics at $1.1 billion per year in the U.S.
"In retrospect," the study states, "many of the assumptions [of that estimate] were optimistic."
While the study concludes that genotype-guided dosing results in better outcomes for some, it estimates only a 10% chance that this strategy is likely to be cost-effective.
Eckman said that the pharmacogenetics strategy in this case could ultimately be worth the costs, based on a variety of "ifs." These are:
• If the test is used for patients at high risk for hemorrhage.
• If it prevents more than 32% of major bleeding events.
• If the results are available within 24 hours.
• And if it costs less than $200.
"This could be accomplished if testing were done in-house, at lower cost and without delays," he said, noting that currently these tests usually need to be sent to outside laboratories and thus can lead to delays in starting treatment and increased cost.
Eckman also suggested that rather than excluding patients at higher risk for bleeding, studies should offer enrollment if it has already been determined that these patients require warfarin.
He said he did not want this study to be generalized to all pharmacogenetics strategies, but that it could be considered helpful as a model and a "very logical way to approach" understanding the value of this type of testing.
He also declined setting any sort of timeframe for the maturation of pharmaco-genetic analysis into standard of care.