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.

Association between resting-state connectivity patterns in the defensive system network and treatment response in spider phobia-a replication approach.

Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.

Mechanisms of action underlying virtual reality exposure treatment in spider phobia: Pivotal role of within-session fear reduction.

Although virtual-reality exposure treatment (VRET) for anxiety disorders is an efficient treatment option for specific phobia, mechanisms of action for immediate and sustained treatment response need to be elucidated. Towards this aim, core therapy process variables were assessed as predictors for short- and long-term VR treatment outcomes. In a bi-centric study, n = 186 patients with spider phobia completed a baseline-assessment, a one-session VRET, a post-therapy assessment, and a 6-month-follow-up assessment (ClinicalTrials.gov, ID: NCT03208400). Short- and long-term outcomes regarding self-reported symptoms in the spider phobia questionnaire (SPQ) and final patient-spider distance in the behavioral avoidance test (BAT) were predicted via logistic regression models with the corresponding baseline score, age, initial fear activation, within-session fear reduction and fear expectancy violation as predictors. To predict long-term remission status at 6-month-follow-up, dimensional short-term changes in the SPQ and BAT were additionally included. Higher within-session fear reductions predicted better treatment outcomes (long-term SPQ; short- and long-term BAT). Lower initial fear activation tended to be associated with better long-term outcomes (SPQ), while fear expectancy violation was not associated with any outcome measure. Short-term change in the SPQ predicted remission status. Findings highlight that in VRET for spider phobia, the experience of fear reduction is central for short- and long-term treatment success and should be focused by therapists.

Parental Mental Illness, Borderline Personality Disorder, and Parenting Behavior: The Moderating Role of Social Support.

PURPOSE OF REVIEW: Parental mental disorders, particularly borderline personality disorder (BPD), impair parenting behavior. Consequently, the children exhibit an elevated risk for psychopathology across their lifespan. Social support for parents is thought to moderate the relationship between parental mental illness and parenting behavior. It may dampen negative effects and serve as starting point for preventive interventions. This paper provides a literature overview regarding the impact of social support on the sequelae of parental mental illness and BPD for parenting behavior. RECENT FINDINGS: Current literature highlights the increased burden of families with a mentally ill parent and associated changes in parenting behavior like increased hostility and affective dysregulation, especially in the context of parental BPD. Literature further demonstrates the powerful impact of social support in buffering such negative outcomes. The effect of social support seems to be moderated itself by further factors like socioeconomic status, gender, or characteristics of the social network. Social support facilitates positive parenting in mentally ill parents and may be particularly important in parents with BPD. However, social support is embedded within a framework of influencing factors, which need consideration when interpreting scientific results.

Clinical predictors of treatment response towards exposure therapy in virtuo in spider phobia: A machine learning and external cross-validation approach.

While being highly effective on average, exposure-based treatments are not equally effective in all patients. The a priori identification of patients with a poor prognosis may enable the application of more personalized psychotherapeutic interventions. We aimed at identifying sociodemographic and clinical pre-treatment predictors for treatment response in spider phobia (SP). N = 174 patients with SP underwent a highly standardized virtual reality exposure therapy (VRET) at two independent sites. Analyses on group-level were used to test the efficacy. We applied a state-of-the-art machine learning protocol (Random Forests) to evaluate the predictive utility of clinical and sociodemographic predictors for a priori identification of individual treatment response assessed directly after treatment and at 6-month follow-up. The reliability and generalizability of predictive models was tested via external cross-validation. Our study shows that one session of VRET is highly effective on a group-level and is among the first to reveal long-term stability of this treatment effect. Individual short-term symptom reductions could be predicted above chance, but accuracies dropped to non-significance in our between-site prediction and for predictions of long-term outcomes. With performance metrics hardly exceeding chance level and the lack of generalizability in the employed between-site replication approach, our study suggests limited clinical utility of clinical and sociodemographic predictors. Predictive models including multimodal predictors may be more promising.