The state of personalized treatment for anxiety disorders: A systematic review of treatment moderators

Schneider, Rebecca L.; Arch, Joanna J.; Wolitzky-Taylor, Kate

doi:10.1016/j.cpr.2015.02.004

Cited by 107 publications

(82 citation statements)

References 72 publications

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“…Although there are more studies testing prescriptive predictors of treatment response in face-to-face treatment of depression 69 and anxiety 70 , findings in the iCBT literature have similarly been disappointing with few consistent moderators identified. Given the large sample sizes required to provide adequately powered tests of predictors of differential response to two or more treatments, 70 most existing studies may be underpowered to detect statistically significant treatment moderators.…”

Section: For Whom Is Icbt Most Effective?mentioning

confidence: 99%

“…Given the large sample sizes required to provide adequately powered tests of predictors of differential response to two or more treatments, 70 most existing studies may be underpowered to detect statistically significant treatment moderators. In addition, the above studies tested the role of individual moderating variables in predicting response to iCBT.…”

Section: For Whom Is Icbt Most Effective?mentioning

confidence: 99%

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Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions

Webb

Rosso

Rauch

2017

Harv Rev Psychiatry

187

114

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The World Health Organization (WHO) estimates that during a given 12-month period approximately 34 million people suffering from major depressive disorder go untreated in Europe and the Americas alone.1 Barriers to treatment include geographic distance, lack of mental health insurance, prohibitive cost of treatment, long wait-lists, and perceived stigma. Over the past two decades internet-based cognitive behavioral therapy (iCBT) programs have proliferated. A growing body of research supports the efficacy of iCBT for depression and other psychiatric conditions, and these programs may help address barriers that hinder access to effective treatment. The present review describes common iCBT programs along with the evidence base supporting their efficacy in reducing symptoms of depression, reviews research on moderators of treatment response, and provides suggestions for future directions in research and care.

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Section: For Whom Is Icbt Most Effective?mentioning

confidence: 99%

Section: For Whom Is Icbt Most Effective?mentioning

confidence: 99%

Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions

Webb

Rosso

Rauch

2017

Harv Rev Psychiatry

187

114

View full text Add to dashboard Cite

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“…While there is a clinically significant proportion of non-responders (26, 28, 30), there is only incipient but rapidly increasing knowledge of moderators and predictors of CBT response (12, 31, 32). Neural correlates of CBT in PD/AG have been investigated in fMRI group comparison studies suggesting a role of altered neural activity in networks regulating negative emotions as well as fear conditioning and extinction (12, 18, 21, 33–36).…”

Section: Introductionmentioning

confidence: 99%

Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia

et al. 2017

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BackgroundThe approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG.MethodsThis analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated.ResultsSVM did not reach sufficient overall predictive accuracies (38.0–54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons.ConclusionIn contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

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“…treatment moderators), has received increasing attention (Simon & Perlis, 2010) as evidenced by the $215 million Precision Medicine Initiative (National Institute of Health, 2016). However, the research on moderators for anxiety disorder treatment is severely lacking due to insufficient sample sizes and underpowered statistical methods (Schneider, Arch, & Wolitzky-Taylor, 2015). Prior moderation analyses typically have compared response to two evidence-based treatments.…”

mentioning

confidence: 99%

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

et al. 2017

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Objective 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. Method 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), thirty-five 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. Results 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. Conclusions 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).

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The state of personalized treatment for anxiety disorders: A systematic review of treatment moderators

Cited by 107 publications

References 72 publications

Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions

Internet-Based Cognitive-Behavioral Therapy for Depression: Current Progress and Future Directions

Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia

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

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