U.S./U.K. Team Assesses Impact of Personal Behavior Changes

Double-blind randomized controlled trials of new drugs may fail to measure how a medication’s
performance can vary based on patients' lifestyle choices, especially if patients change their habits because they are anticipating treatment, according to a new study published in Plos One.

"Our proposed design has the potential to better evaluate the effectiveness of treatments targeting conditions related to mental health, substance abuse and smoking cessation, in which behavior is known to play an important role," noted co-lead author Sylvain Chassang, a professor of economics and public affairs at Princeton's Woodrow Wilson School of Public and International Affairs (Princeton, NJ).

Chassang and his collaborators ­Erik Snowberg from the California Institute of Technology (Pasadena, CA), Ben Seymour from Cambridge University (Cambridge, U.K.) and Caley Bowles from Harvard University School of Public Health (Boston, MA) studied whether the likelihood of receiving a new treatment changes the overall effectiveness of a drug.

They propose a new clinical trial design that varies the probability of treatment across participant groups. Instead of having a 50/50 chance of receiving treatment, participants are placed in high- and low-probability treatment groups. In the high-probability group, there is a 70% chance of receiving treatment while the low-probability group would have only a 30% chance of receiving treatment. Following current guidelines, all participants are made aware of their likelihood of receiving the new treatment.

"It's a very small change to the design of the trial, but it's important," Snowberg said. "The effect of a treatment has these two constituent parts: pure treatment effect and the treatment-behavior
interaction. Standard blind trials just randomize the likelihood of treatment, but if you want to separate out the pure treatment effects and the treatment-behavior interaction effect, then you have to randomize both the treatment and the behavior."

To test their hypothesis that treatment and behavior interact, the researchers conducted a meta-analysis of data from six clinical trials involving two antidepressants, paroxetine and tricyclic imipramine. By changing the variation in the likelihood of treatment across trials, they were able to determine how much of the overall effect is attributable to behavior change alone, the treatment alone and the interaction between the treatment and behavior.
 

Read the full release here.