Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Enhancing the effectiveness of CBT for patients with unipolar depression by integrating digital interventions into treatment: A pilot randomized controlled trial.

OBJECTIVE: Blended cognitive behavioral therapy (bCBT) combines face-to-face therapy with digital elements, such as digital health apps. This pilot study aimed to explore the effectiveness and safety of a novel bCBT application for treating unipolar depression in adults combined with cognitive behavioral therapy (CBT) compared to CBT alone in routine care. METHODS: Patients (N = 82) were randomly assigned to bCBT (n = 42) or CBT (n = 40) over 12 weeks. bCBT consisted of weekly CBT sessions accompanied by the elona therapy depression module (a bCBT application for unipolar depression) for use between sessions. Standard CBT consisted of weekly CBT sessions. Outcomes (6,12 weeks) were analyzed with linear mixed models. RESULTS: Improvements in depressive symptoms (BDI-II, PHQ-9) were descriptively larger for the bCBT group. Yet, this difference did not reach statistical significance. bCBT was superior to standard CBT in secondary outcome measures of psychological health (d = .50) and generalized anxiety symptoms (d = -.45). In other secondary outcomes (BAI, PSWQ, GSE, WHOQOL-BREF), improvements were descriptively larger for bCBT compared to CBT. CONCLUSION: This pilot study provided preliminary evidence that bCBT might be advantageous in comparison to CBT alone in the treatment of depression, but larger RCTs of the bCBT application are needed.

Efficacy of temporally intensified exposure for anxiety disorders: A multicenter randomized clinical trial.

BACKGROUND: The need to optimize exposure treatments for anxiety disorders may be addressed by temporally intensified exposure sessions. Effects on symptom reduction and public health benefits should be examined across different anxiety disorders with comorbid conditions. METHODS: This multicenter randomized controlled trial compared two variants of prediction error-based exposure therapy (PeEx) in various anxiety disorders (both 12 sessions + 2 booster sessions, 100 min/session): temporally intensified exposure (PeEx-I) with exposure sessions condensed to 2 weeks (n = 358) and standard nonintensified exposure (PeEx-S) with weekly exposure sessions (n = 368). Primary outcomes were anxiety symptoms (pre, post, and 6-months follow-up). Secondary outcomes were global severity (across sessions), quality of life, disability days, and comorbid depression. RESULTS: Both treatments resulted in substantial improvements at post (PeEx-I: dwithin = 1.50, PeEx-S: dwithin = 1.78) and follow-up (PeEx-I: dwithin = 2.34; PeEx-S: dwithin = 2.03). Both groups showed formally equivalent symptom reduction at post and follow-up. However, time until response during treatment was 32% shorter in PeEx-I (median = 68 days) than PeEx-S (108 days; TRPeEx-I = 0.68). Interestingly, drop-out rates were lower during intensified exposure. PeEx-I was also superior in reducing disability days and improving quality of life at follow-up without increasing relapse. CONCLUSIONS: Both treatment variants focusing on the transdiagnostic exposure-based violation of threat beliefs were effective in reducing symptom severity and disability in severe anxiety disorders. Temporally intensified exposure resulted in faster treatment response with substantial public health benefits and lower drop-out during the exposure phase, without higher relapse. Clinicians can expect better or at least comparable outcomes when delivering exposure in a temporally intensified manner.

Effective-and Tolerable: Acceptance and Side Effects of Intensified Exposure for Anxiety Disorders.

Despite striking empirical support, exposure-based treatments for anxiety disorders are underutilized. This is partially due to clinicians' concerns that patients may reject exposure or experience severe side effects, particularly in intensive forms of exposure. We examined acceptance and side effects of two randomly assigned variants of prediction error-based exposure treatment differing in temporal density (1 vs. 3 sessions/week) in 681 patients with panic disorder, agoraphobia, social anxiety disorder, and multiple specific phobias. Treatment acceptance included treatment satisfaction and credibility, engagement (i.e., homework completion), and tolerability (i.e., side effects, dropout, and perceived treatment burden). Side effects were measured with the Inventory for the Balanced Assessment of Negative Effects of Psychotherapy (INEP). We found treatment satisfaction, credibility, and engagement to be equally high in both variants of exposure-based treatment, despite higher treatment burden (ß = 0.25) and stronger side effects (ß = 0.15) in intensified treatment. 94.1% of patients reported positive effects in the INEP. 42.2% reported side effects, with treatment stigma (16.6%), low mood (14.8%) and the experience to depend on the therapist (10.9%) being the most frequently reported. The mean intensity of side effects was low. We conclude that prediction error-based exposure treatment is well accepted by patients with different anxiety disorders and that patients also tolerate temporally intensified treatment, despite higher perceived treatment burden and stronger side effects. Clinicians should be aware of the most frequent side effects to take appropriate countermeasures. In sum, temporal intensification appears to be an acceptable strategy to achieve faster symptom reduction, given patients' well-informed consent.

Combining baseline characteristics to disentangle response differences to disorder-specific versus supportive psychotherapy in patients with persistent depressive disorder.

Does the pre-treatment profile of individuals with persistent depressive disorder (PDD) moderate their benefit from disorder-specific Cognitive Behavioral System of Psychotherapy (CBASP) versus supportive psychotherapy (SP)? We investigated this question by analyzing data from a multi-center randomized clinical trial comparing the effectiveness of 48 weeks of CBASP to SP in n  =  237 patients with early-onset PDD who were not taking antidepressant medication. We statistically developed an optimal composite moderator as a weighted combination of 13 preselected baseline variables and used it for identifying and characterizing subgroups for which CABSP may be preferable to SP or vice versa. We identified two distinct subgroups: 58.65% of the patients had a better treatment outcome with CBASP, while the remaining 41.35% had a better outcome with SP. At baseline, patients responding more favorably to CBASP were more severely depressed and more likely affected by moderate-to-severe childhood trauma including early emotional, physical, or sexual abuse, as well as emotional or physical neglect. In contrast, patients responding more favorably to SP had a higher pre-treatment global and social functioning level, a higher life quality and more often a recurrent illness pattern without complete remission between the episodes. These findings emphasize the relevance of considering pre-treatment characteristics when selecting between disorder-specific CBASP and SP for treating PDD. The practical implementation of this approach would advance personalized medicine for PDD by supporting mental health practitioners in their selection of the most effective psychotherapy for an individual patient.

Optimizing exposure-based CBT for anxiety disorders via enhanced extinction: Design and methods of a multicentre randomized clinical trial.

Exposure-based psychological interventions currently represent the empirically best established first line form of cognitive-behavioural therapy for all types of anxiety disorders. Although shown to be highly effective in both randomized clinical and other studies, there are important deficits: (1) the core mechanisms of action are still under debate, (2) it is not known whether such treatments work equally well in all forms of anxiety disorders, including comorbid diagnoses like depression, (3) it is not known whether an intensified treatment with more frequent sessions in a shorter period of time provides better outcome than distributed sessions over longer time intervals. This paper reports the methods and design of a large-scale multicentre randomized clinical trial (RCT) involving up to 700 patients designed to answer these questions. Based on substantial advances in basic research we regard extinction as the putative core candidate model to explain the mechanism of action of exposure-based treatments. The RCT is flanked by four add-on projects that apply experimental neurophysiological and psychophysiological, (epi)genetic and ecological momentary assessment methods to examine extinction and its potential moderators. Beyond the focus on extinction we also involve stakeholders and routine psychotherapists in preparation for more effective dissemination into clinical practice.