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.

Working out the worries: A randomized controlled trial of high intensity interval training in generalized anxiety disorder.

BACKGROUND: Aerobic exercise (AE) demonstrated an overall medium treatment effect in anxiety disorders (AD) but there is evidence for an "intensity-response" relationship. High intensity interval training (HIIT) was highly effective on a range of (mental) health parameters. However, so far no randomised-controlled trial (RCT) investigated the efficacy of HIIT in AD. METHODS: 33 patients with generalized anxiety disorder (GAD) were randomly assigned to 12-day HIIT or a training of lower intensity (LIT). Anxiety, comorbid depression, stress-related bodily symptoms and perceived control over anxiety related stimuli (PC) were assessed at baseline, post-training and 30 days after baseline by using the Penn State Worry Questionnaire (PSWQ), the Hamilton Inventories for Anxiety and Depression (Ham-A, Ham-D), the Screening for Somatoform Symptoms-7 (SOMS-7) and the Anxiety Control Questionnaire (ACQ-R). RESULTS: Both interventions showed moderate or large effects on all clinical measures. However, effects for HIIT were generally about twice as high as for LIT. PC negatively correlated with GAD severity in the whole sample at baseline but an association of training-induced changes in PC and worrying were exclusively detectable in HIIT. CONCLUSION: HIIT was highly effective and fast acting in GAD. Therefore, it may complement first-line treatment approaches in this condition.

Running for extinction? Aerobic exercise as an augmentation of exposure therapy in panic disorder with agoraphobia.

Exposure-based Cognitive Behavioral Therapy (eb-CBT) represents the most evidence-based psychotherapeutic approach in anxiety disorders. However, its efficacy may be limited by a delay in onset of action and a substantial number of patients does not respond sufficiently to treatment. In this context, aerobic exercise was found to be effective in reducing clinical anxiety as well as to improve (elements of) disorder-specific CBT in some mental disorders. We therefore investigated the effect of aerobic exercise supplementary to an eb-CBT in panic disorder and agoraphobia (PD/AG). 77 patients with PD/AG performed a 30 min treadmill task with moderate or low intensity (70% or 30% of the maximal oxygen uptake [VO2max]) prior to five exposure sessions within a standardized seven-week CBT. At baseline, after completing the treatment period (post) and six month after post (follow-up), several measures of (un)specific psychopathology (Hamilton Anxiety Rating Scale [Ham-A], Mobility Inventory [MI], Panic and Agoraphobia Scale [PAS], Agoraphobic Cognitions Questionnaire [ACQ], Body Sensations Questionnaire [BSQ]) were established to assess for clinical changes. All patients experienced a significant improvement of symptoms from baseline to post (for all measures p < .001) but repeated-measures analyses of variance found a trend towards a significant time × group interaction in the Ham-A in favor for the moderate intense exercise group (f[1, 74] = 4.15, p = .045, α=.025). This trend, however, disappeared at follow-up since the low-intense exercise group further improved significantly in Ham-A after post. Our findings therefore might point to an accelerating effect of moderate-intense exercise within an exposure-based CBT for AG/PD.