Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder

J Santiago,K T Cosgrove,Robin L Aupperle,M G Craske,B Mathis,T J Mcdermott,E Akeman,C Martell,M Paulus,J Abelson,A N Clausen,N Kirlic,W K Thompson,K Wolitzky-Taylor,J Bodurka

doi:10.1186/s13063-019-3802-9

Abstract

BackgroundOnly 40–60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of “personalized medicine.” Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder.Methods/designWe are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder–7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods.DiscussionThis protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome.Trial registrationThe study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results.

Highlights

40–60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions
We developed a human avoidance conflict (AAC) task [23, 24] for use in functional magnetic resonance imaging work, and we have shown that approach behavior was linked to caudate and anterior cingulate cortex activation, whereas difficulties arbitrating conflict were linked to self-reported anxiety and dorsolateral prefrontal cortex activation
To enhance treatment effectiveness and efficiency for individuals with anxiety and depression, it will be beneficial to understand why many patients do not respond optimally to gold standard therapies and to be able to predict, before treatment begins which patients will respond to which treatments

Summary

Introduction

40–60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Research suggests that reward and threat processing (approach/ avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. Only 40–60% of patients experience improvement with these treatments [9, 10], and 15–25% of those who improve relapse within 1 year [9] This creates both clinical and socioeconomic challenges because these treatments are costly and time-consuming [11]. Behavioral, or neural factors that predict outcomes and can perhaps be targeted in an individualized fashion, we can move toward personalized approaches that assign each patient to the optimal treatment for them

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