Boston, MA (October 23, 2013) - Should everyone with high cholesterol take cholesterol-lowering medication? A better scenario would be for those who are most likely to benefit to take the medication but not those who are unlikely to benefit. With that idea in mind, the National Institutes of Health (NIH) has awarded $2 million to Tufts Predictive Analytics and Comparative Effectiveness (PACE) Center and the Center for the Evaluation of Value and Risk (CEVR), both at Tufts Medical Center in Boston. The goal is to develop models to predict which populations are most likely to benefit from different health treatments.
“The idea is to personalize the information so doctors and patients can make decisions based on which patients will derive the most benefit from a drug, for example,” said David Kent, M.D., director of the PACE Center and the Graduate Program in Clinical and Translational Science, Sackler School of Graduate Biomedical Sciences, and associate professor of medicine in neurology and clinical and translational science at Tufts University. Kent is co-principal investigator for the project along with CEVR Director Peter J. Neumann, Sc.D.
“Because most medical evidence is based on studies of large groups of people and cost effectiveness analysis is also based on population averages, this information doesn’t necessarily translate well when it comes time for a doctor and patient to decide on a medical treatment for an individual patient,” Kent said. Individual patients can vary substantially in their probability of benefiting from a given intervention, or in their outcome- or treatment-related preferences.
“It makes sense from both a clinical and economic standpoint,” said Neumann, “With today’s limited resources, everyone is better off if we can identify which patients are most likely to benefit from a drug or other treatment.”
Responding to a call from the NIH to develop an economic framework for personalized medicine, the PACE Center and CEVR collaborated on a proposal to explore the value of providing to clinicians and patients information regarding each patient's individualized risk of having bad health outcomes so that clinicians can better tailor care. The project leverages key assets of these two groups, including the PACE Center's on-going Patient Centered Outcomes Research Institute-sponsored project examining how risks and treatment effects can vary across the population of several dozen clinical trials and CEVR's Cost Effectiveness Analysis Registry (CEAR).
This 5-year, $2M project also aims to develop new tools and methods to help recognize when a new risk factor (e.g., a new biomarker) may provide clinically useful information, and when it is unlikely to do so. Finally, researchers will explore the potential for improving health through doctor and patient incentives to make decisions that better match patient risks, values and preference. The two groups at Tufts Medical Center will also be collaborating closely with the Medical Decision Making group at Erasmus Medical Center in Rotterdam, The Netherlands.
Key investigators on this project include: David Kent, M.D., Peter Neumann, Sc.D., Ewout Steyerberg, Ph.D., Joshua Cohen, Ph.D. John Wong, M.D., and Lesley Inker, M.D.