NPC’s Dr. Graff: Individual Treatment Effects Matter
Dr. Jennifer Graff, NPC’s director for comparative effectiveness research, highlighted one of the key challenges in determining the best treatment options for patients during her presentation at the Community Oncology Alliance conference in Orlando, Florida on March 22.
Dr. Jennifer Graff, NPC’s director for comparative effectiveness research, highlighted one of the key challenges in determining the best treatment options for patients during her presentation at the Community Oncology Alliance conference in Orlando, Florida on March 22.
During “The Myth of Average: Why Individual Patient Differences Matter,” Dr. Graff said it is important for health care decision makers to be aware of the reasons for heterogeneity, or variation in treatment responses, especially when dealing with conditions like late-stage cancer, where there is no margin for treatment error. “A treatment that is safe and effective for some, does not mean that it is safe and effective for all,” she said. “And at the same time, a treatment that is not safe and not effective for some does not mean that it is not safe and not effective for all.”
Figuring out what works best for an individual patient is not clear cut, especially since most studies are conducted with population averages in mind. There are a variety of factors that could be causing different treatment responses, such as age, gender, disease severity, use of medications, care settings, comorbidities, diet, and genetics. In some areas, there may be multiple factors or gene phenotypes that may indicate what works best for an individual. But it isn’t always possible to go back to research studies and analyze the data for these factors, said Dr. Graff.
There are some ways to determine when there is a higher risk and clinical impact seen from heterogeneity, Dr. Graff noted. “We know that the impact is bigger if there is greater underlying patient diversity for a particular condition. For example, is there a lack of predictable genetic markers for the condition? Are there multiple clinical benefits or risks, such as some patients may be seeking remission, but they may also be at greater risk of infection?
“In addition, we can ask whether patients with this condition are likely to respond to similar treatments, or whether they are all over the map. And what are the clinical consequences of delaying optimal treatment while we figure out what works best—is it an irreversible condition or is there little chance of treatment success? And finally, what are the patient preferences in terms of quality of life and the impact on daily activities?” said Dr. Graff.
To make it easier for health care decision makers to recognize some of these challenges, NPC and Precision Health Economics have been working on the development of an electronic tool to assess the potential impact of applying population decisions to individual patients. The tool is currently being pilot tested and is expected to be launched later this year. “If we can make sure that patients are getting the right treatment earlier, it can go a long way in improving health care outcomes, not only for society but also for each of us as individual patients,” Dr. Graff said.