Researchers press for risk-stratified analysis of clinical trial data

Current practice determines the average effect for the population at large but often fails to take into account patient variability.

By Victoria Stagg Elliott, AMNews staff. Dec. 12, 2005.

Rodney Hayward, MD, professor of medicine and public health at the University of Michigan Medical School, Ann Arbor, doesn't always feel like he has the information he needs to tailor prescribing to his patients, even when he can draw on the knowledge produced by large randomized trials.

He knows, for instance, that hormone therapy can increase the risk of heart disease in the population of older women as a whole, but what he wants to know is how it affects the risk of an individual patient based on her other cardiovascular characteristics.

"If I have a 50-year-old in my office and she has a lot of hot flashes, I can't tell what her risk for a [hormone therapy-related] adverse event is," said Dr. Hayward, who is also the director of the VA Center for Practice Management and Outcomes Research in Ann Arbor. "All we have are the average results, and they may or may not apply. The harm may be very, very small in some individuals."

It is this kind of frustration, coupled with recent controversies surrounding adverse events that emerge long after a drug hits the market, that has researchers looking for new ways to make clinical trial data more individually applicable. They are increasingly recognizing that risk and benefit are far from evenly distributed, and they hope to develop tools to determine who is more likely to be harmed or benefited by a particular drug.

"Clinical trials are basically done to determine whether a drug works in groups of people and the answer applies to the group," said Curt Furberg, MD, PhD, a former member of the Food and Drug Administration's Drug Safety & Risk Management Advisory Committee and professor of public health sciences at Wake Forest University School of Medicine in Winston-Salem, N.C. "But people are different, and their responses to drugs are different."