Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

Doehrmann, Oliver; Ghosh, Samik; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, S.; Pollack, Mark H.; Gabrieli, John D. E.

doi:10.1001/2013.jamapsychiatry.5

Cited by 221 publications

(152 citation statements)

References 62 publications

(98 reference statements)

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“…For each participant, contrast images of brain activity were generated for second-level analysis. As processing of both angry and fearful faces has been shown to predict treatment response (Doehrmann et al, 2013;McClure et al, 2007a), we collapsed across these face types to evaluate activation to threatening (ie, angry/fearful) faces vs shapes and activation to non-threatening (ie, happy) faces vs shapes.…”

Section: Methodsmentioning

confidence: 99%

“…linked to emotion regulation and treatment response in adult anxiety (Ball et al, 2014b;Doehrmann et al, 2013;Kohn et al, 2014). Hierarchical multiple regression analyses were computed predicting change in PARS with age, pretreatment PARS, study site, treatment, number of session, and dlPFC or vlPFC activation in Step 1, followed by dlPFC or vlPFC interactions with site, treatment, and number of sessions in…”

Section: Fmri Predictors Of Treatment Responsementioning

confidence: 99%

“…Consistent with this, activation in the amydala, involved in signaling the presence of threat, has been shown to predict response to treatment in anxiety (McClure et al, 2007a;Whalen et al, 2008); however, results have been inconsistent. Less amygdala reactivity in adults with GAD predicted better response to venlafaxine (Whalen et al, 2008), yet greater amygdala activation predicted better response to CBT or fluoxetine in anxious youth (McClure et al, 2007a), and other studies have failed to find amygdala effects (Doehrmann et al, 2013;Klumpp et al, 2013;Nitschke et al, 2009). Other work has indicated that greater activation to threatening faces in visual processing regions (ie, occipital and temporal gyri) involved in detecting and appraising emotional cues predicted better response to CBT among adults with social anxiety disorder (Doehrmann et al, 2013;Klumpp et al, 2013), possibly indicating greater initial threat reactivity which can be modified by treatment.…”

Section: Introductionmentioning

confidence: 99%

“…For example, greater ACC activation during threat processing predicted better response to medication and CBT for adults with GAD (Nitschke et al, 2009;Whalen et al, 2008) and social anxiety disorder (Klumpp et al, 2013). Greater dorsolateral PFC (dlPFC) activation during emotion regulation predicted response to treatment in adults with GAD or panic disorder (Ball et al, 2014b), and dlPFC and ventrolateral PFC (vlPFC) activation to threat predicted CBT response in socially anxious adults (Doehrmann et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Given the limited existing work on predictors of treatment response in anxious youth, analyses examined whole-brain activation to emotional faces to identify predictors of change in anxiety severity following treatment. As previous fMRI work in anxious adults has indicated that brain activation during threat processing predicts response to treatment (eg, Ball et al, 2014b;Doehrmann et al, 2013;Klumpp et al, 2013), our primary analyses focused on responses to threatening (ie, angry and fearful) faces, with secondary analyses examining response to happy faces. To maximize power, our primary analyses examined predictors across treatment types, and additional post-hoc analyses examined whether effects were moderated by treatment or clinical characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Prefrontal Reactivity to Social Signals of Threat as a Predictor of Treatment Response in Anxious Youth

Kujawa

Swain

Hanna

et al. 2015

Neuropsychopharmacol

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Neuroimaging has shown promise as a tool to predict likelihood of treatment response in adult anxiety disorders, with potential implications for clinical decision-making. Despite the relatively high prevalence and emergence of anxiety disorders in youth, very little work has evaluated neural predictors of response to treatment. The goal of the current study was to examine brain function during emotional face processing as a predictor of response to treatment in children and adolescents (age 7-19 years; N = 41) with generalized, social, and/ or separation anxiety disorder. Prior to beginning treatment with the selective serotonin reuptake inhibitor (SSRI) sertraline or cognitive behavior therapy (CBT), participants completed an emotional faces matching task during functional magnetic resonance imaging (fMRI). Whole brain responses to threatening (ie, angry and fearful) and happy faces were examined as predictors of change in anxiety severity following treatment. Greater activation in inferior and superior frontal gyri, including dorsolateral prefrontal cortex and ventrolateral prefrontal cortex, as well as precentral/postcentral gyri during processing of threatening faces predicted greater response to CBT and SSRI treatment. For processing of happy faces, activation in postcentral gyrus was a significant predictor of treatment response. Post-hoc analyses indicated that effects were not significantly moderated by type of treatment. Findings suggest that greater activation in prefrontal regions involved in appraising and regulating responses to social signals of threat predict better response to SSRI and CBT treatment in anxious youth and that neuroimaging may be a useful tool for predicting how youth will respond to treatment.

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Section: Methodsmentioning

confidence: 99%

Section: Fmri Predictors Of Treatment Responsementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Prefrontal Reactivity to Social Signals of Threat as a Predictor of Treatment Response in Anxious Youth

Kujawa

Swain

Hanna

et al. 2015

Neuropsychopharmacol

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Impact of Cognitive Behavioral Therapy for Social Anxiety Disorder on the Neural Dynamics of Cognitive Reappraisal of Negative Self-beliefs

Goldin¹,

Ziv²,

Jazaieri³

et al. 2013

JAMA Psychiatry

137

110

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Predicting Treatment Response to Cognitive Behavioral Therapy in Panic Disorder With Agoraphobia by Integrating Local Neural Information

et al. 2015

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IMPORTANCE Although neuroimaging research has made substantial progress in identifying the large-scale neural substrate of anxiety disorders, its value for clinical application lags behind expectations. Machine-learning approaches have predictive potential for individual-patient prognostic purposes and might thus aid translational efforts in psychiatric research. OBJECTIVE To predict treatment response to cognitive behavioral therapy (CBT) on an individual-patient level based on functional magnetic resonance imaging data in patients with panic disorder with agoraphobia (PD/AG). DESIGN, SETTING, AND PARTICIPANTS We included 49 patients free of medication for at least 4 weeks and with a primary diagnosis of PD/AG in a longitudinal study performed at 8 clinical research institutes and outpatient centers across Germany. The functional magnetic resonance imaging study was conducted between July 2007 and March 2010. INTERVENTIONS Twelve CBT sessions conducted 2 times a week focusing on behavioral exposure. MAIN OUTCOMES AND MEASURES Treatment response was defined as exceeding a 50% reduction in Hamilton Anxiety Rating Scale scores. Blood oxygenation level-dependent signal was measured during a differential fear-conditioning task. Regional and whole-brain gaussian process classifiers using a nested leave-one-out cross-validation were used to predict the treatment response from data acquired before CBT. RESULTS Although no single brain region was predictive of treatment response, integrating regional classifiers based on data from the acquisition and the extinction phases of the fear-conditioning task for the whole brain yielded good predictive performance (accuracy, 82%; sensitivity, 92%; specificity, 72%; P < .001). Data from the acquisition phase enabled 73% correct individual-patient classifications (sensitivity, 80%; specificity, 67%; P < .001), whereas data from the extinction phase led to an accuracy of 74% (sensitivity, 64%; specificity, 83%; P < .001). Conservative reanalyses under consideration of potential confounders yielded nominally lower but comparable accuracy rates (acquisition phase, 70%; extinction phase, 71%; combined, 79%). CONCLUSIONS AND RELEVANCE Predicting treatment response to CBT based on functional neuroimaging data in PD/AG is possible with high accuracy on an individual-patient level. This novel machine-learning approach brings personalized medicine within reach, directly supporting clinical decisions for the selection of treatment options, thus helping to improve response rates.

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Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

Cited by 221 publications

References 62 publications

Prefrontal Reactivity to Social Signals of Threat as a Predictor of Treatment Response in Anxious Youth

Prefrontal Reactivity to Social Signals of Threat as a Predictor of Treatment Response in Anxious Youth

Impact of Cognitive Behavioral Therapy for Social Anxiety Disorder on the Neural Dynamics of Cognitive Reappraisal of Negative Self-beliefs

Predicting Treatment Response to Cognitive Behavioral Therapy in Panic Disorder With Agoraphobia by Integrating Local Neural Information

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