Before the oncology treatment paradigm can move from a one-size-fits-all model to true personalized medicine, the medical establishment must find a cost-effective way to identify biomarkers.
Before the oncology treatment paradigm can move from a one-size-fits-all model to true personalized medicine, the medical establishment must find a cost-effective way to identify biomarkers that determine which therapies patients should receive.
That is the message in a recent report by two Colorado researchers who performed a cost-effectiveness analysis of targeted therapies for lung cancer, using the biomarker ALK and the targeted therapy crizotinib (Xalkori, Pfizer) to build their model.
In the analysis, published recently in the British Journal of Cancer, the researchers found that costs rose considerably as more people were tested who didn’t have the biological abnormality being sought. However, when the researchers controlled costs by applying methods to target patients for screening who were more likely to test positive, they missed a significant proportion of the patients who could have benefited from targeted therapy.1
D. Ross Camidge, MD, PhD, who performed the analysis with Adam J. Atherly, PhD, said that cost-effectiveness of screening has to be considered when determining the costs of treatment with targeted therapy, and that the high costs of a “test-everyone” approach may not be feasible in today’s healthcare environment.
“The big advances in lung cancer (and many other cancers) have come from not giving one drug to everyone, but developing tests to find out in advance who will get maximal benefit from the drug. If you don’t, the average benefit is very poor. However, the cost of testing now has to be factored into the calculations of determining the cost-effectiveness of any drug used in this way. Bringing down the cost per positive is essential,” explained Camidge, who was involved in early research for the development of crizotinib and helped to develop one of the assays used to test for the ALK gene alteration.
“Assuming you only treat those who come up positive on a test, your cost-effectiveness goes down as you screen more people who don’t have the abnormality you are looking for. It increases the up-front costs of finding those positives,” Camidge said. “For a $1000 test, if the group you screen has a 50% hit rate, you have to add $2000 to the costs of treating every patient. If it is 1%, you have to add $100,000 up front as the money you spend to find even one patient who is positive.
“For me, the message is to the wider community of doctors, insurers, healthcare providers, and patients. Breakthroughs will not be feasibly applicable unless we make the cost-effectiveness realistic.”
In the initial modeling, the researchers explored a range of costs, assuming that costs would vary over time. They found that, if all patients with advanced non—small cell lung cancer were screened for ALK, and the assay cost around $1400, screening would be $106,707 per quality-adjusted life-year (QALY) before any drug-related costs were considered. If the population could be narrowed to only those more likely to test positive, the QALY cost would fall to $4756. However, physicians would miss more than half the patients who would benefit from treatment.
“When you start to think like this, the cost-effectiveness of these breakthroughs becomes a real problem,” Camidge said. “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.”
1. Atherly AJ, Camidge DR. The cost-effectiveness of screening lung cancer patients for targeted drug sensitivity markers. Br J Cancer. 2012; 106(6):1100- 1106. doi:10.1038/bjc.2012.60.