Advancing Personalized Medicine: Application of a Novel Statistical Method to Identify Treatment Moderators in the Coordinated Anxiety Learning and Management Study.

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. 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), 35 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. 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. 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).

Response rates for CBT for anxiety disorders: Need for standardized criteria.

Full appreciation of the effectiveness of cognitive behavioral therapy (CBT) requires both effect size data and individual rates of positive response. Response rates are particularly helpful for clinicians when choosing among treatment options. However, systematic reviews on cross-study response rates have not been conducted, possibly due to the absence of a standardized metric for calculating response rates. We conducted a systematic review of the treatment outcome literature to determine overall response rates to CBT for anxiety disorders and whether current methods of defining treatment response influence overall response rates. Our database search (2000-2014) resulted in 87 studies that reported response rates and included at least one CBT condition. Results showed that overall treatment response rates across anxiety disorders averaged 49.5% at post-treatment and 53.6% at follow-up. Response rates varied significantly as a function of the properties used to define them. Measures that incorporated more than one criterion, the combination of a reliable change index with a clinical cutoff (a clinically significant change), and intent-to-treat samples yielded lower response rates at post-treatment. Blinded independent assessors yielded higher response rates than unblinded assessors. Based on previous empirical and theoretical work, we recommend that future studies use a clinically significant change index, in an intent-to-treat analysis (using a mixed-model approach), reflecting multiple modalities, and assessed by independent blinded assessors. Our results indicate that such measures are likely to reduce response rates, but may result in a less biased and more accurate representation of improvement and achievement of normative functioning.