Biomarker discovery and development are driving the development of targeted therapies, particularly in cancer, and these need companion tests to ensure that only the people with the right markers (and therefore the people who are most likely to benefit) are treated. But what does it cost?
In a paper in the British Journal of Cancer, two researchers looked at the cost-effectiveness of targeted therapies in cancer combined with companion diagnostics. They used health economic modeling to assess the cost per Quality Adjusted Life Year (QALY) in a (theoretical) population of people with advanced non-small cell lung cancer (NSCLC), and found that costs were high if everyone with advanced cancer was tested, and fell drastically if only a few selected people were tested. However, this preselection meant that some people who might have benefited were missed. D. Ross Camidge, one of the authors, told OncLive that the cost of the diagnostics has to be borne in mind when looking at the overall cost of personalized treatment, and so testing everyone might not be feasible.
"When you start to think like this, the cost-effectiveness of these breakthroughs becomes a real problem," Camidge told OncLive. "We can either enrich the population being screened by other means but run the risk of missing some people, or bring down the cost of finding each positive patient, such as by reducing the cost of the individual test or multiplexing the tests so you get more positives (even if in different markers) per dollar spent."
Personalized medicine can significantly improve the outcomes for patients who test positive or negative--for the patients who test positive, they get a treatment tailored to them and increase their chance of a good outcome, and for patients who test negative, they don't waste time on unnecessary or toxic treatment, and can be moved to the next treatment option more quickly. The healthcare system saves money in both scenarios as well. However, as Camidge says, to make this work, the tests have to be cheaper, or testing needs to be more efficient. Perhaps that's the next challenge for the biomarkers industry. -- Suzanne Elvidge (email)