No abstract

Objective There has been increasing recognition of the value of personalized medicine where the most effective treatment is selected based on individual characteristics. This study used a new method to identify a composite moderator of response to evidence-based anxiety treatment (CALM) compared to Usual Care. Method Eight hundred seventy-six patients diagnosed with one or multiple anxiety disorders were assigned to CALM or Usual Care. Using the method proposed by Kraemer (2013), thirty-five possible moderators were examined for individual effect sizes then entered into a forward-stepwise regression model predicting differential treatment response. K-fold cross validation was used to identify the number of variables to include in the final moderator. Results Ten variables were selected for a final composite moderator. The composite moderator effect size (r = .20) was twice as large as the strongest individual moderator effect size (r = .10). Although on average patients benefitted more from CALM, 19% of patients had equal or greater treatment response in Usual Care. The effect size for the CALM intervention increased from d = .34 to d = .54 when accounting for the moderator. Conclusions Findings support the utility of composite moderators. Results were used to develop a program that allows mental health professionals to prescribe treatment for anxiety based on baseline characteristics (http://anxiety.psych.ucla.edu/treatmatch.html).