Neuroimaging, genetic, clinical, and demographic predictors of treatment response in patients with social anxiety disorder
(2020) In Journal of Affective Disorders 261. p.230-237- Abstract
Background: Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD). Methods: Forty-seven SAD patients (mean±SD age 33.9 ± 9.4 years, 24 women) were randomized and commenced 9 weeks’ Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n = 24) or placebo (placebo+CBT, n = 23). Treatment responders were defined from the Clinical Global... (More)
Background: Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD). Methods: Forty-seven SAD patients (mean±SD age 33.9 ± 9.4 years, 24 women) were randomized and commenced 9 weeks’ Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n = 24) or placebo (placebo+CBT, n = 23). Treatment responders were defined from the Clinical Global Impression-Improvement scale (CGI-I ≤ 2). Before treatment, patients underwent functional magnetic resonance imaging and the Multi-Source Interference Task taxing cognitive interference. Support vector machines (SVMs) were trained to separate responders from nonresponders based on pre-treatment neural reactivity in the dorsal anterior cingulate cortex (dACC), amygdala, and occipital cortex, as well as molecular genetic, demographic, and clinical data. SVM models were tested using leave-one-subject-out cross-validation. Results: The best model separated treatment responders (n = 24) from nonresponders based on pre-treatment dACC reactivity (83% accuracy, P = 0.001). Responders had greater pre-treatment dACC reactivity than nonresponders especially in the SSRI+CBT group. No other variable was associated with clinical response or added predictive accuracy to the dACC SVM model. Limitations: Small sample size, especially for genetic analyses. No replication or validation samples were available. Conclusions: The findings demonstrate that treatment outcome predictions based on neural cingulate activity, at the individual level, outperform genetic, demographic, and clinical variables for medication-assisted Internet-delivered CBT, supporting the use of neuroimaging in precision psychiatry.
(Less)
- author
- Frick, Andreas ; Engman, Jonas ; Alaie, Iman ; Björkstrand, Johannes LU ; Gingnell, Malin ; Larsson, Elna Marie LU ; Eriksson, Elias ; Wahlstedt, Kurt ; Fredrikson, Mats and Furmark, Tomas
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- CBT, Pattern recognition, Personalized medicine, Social phobia, SSRI, SVM
- in
- Journal of Affective Disorders
- volume
- 261
- pages
- 8 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85073678312
- pmid:31655378
- ISSN
- 0165-0327
- DOI
- 10.1016/j.jad.2019.10.027
- language
- English
- LU publication?
- yes
- id
- ce9415ed-c96f-4a0b-bc34-6ffc9633ee96
- date added to LUP
- 2019-10-29 14:11:44
- date last changed
- 2024-04-16 21:47:25
@article{ce9415ed-c96f-4a0b-bc34-6ffc9633ee96,
abstract = {{<p>Background: Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD). Methods: Forty-seven SAD patients (mean±SD age 33.9 ± 9.4 years, 24 women) were randomized and commenced 9 weeks’ Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n = 24) or placebo (placebo+CBT, n = 23). Treatment responders were defined from the Clinical Global Impression-Improvement scale (CGI-I ≤ 2). Before treatment, patients underwent functional magnetic resonance imaging and the Multi-Source Interference Task taxing cognitive interference. Support vector machines (SVMs) were trained to separate responders from nonresponders based on pre-treatment neural reactivity in the dorsal anterior cingulate cortex (dACC), amygdala, and occipital cortex, as well as molecular genetic, demographic, and clinical data. SVM models were tested using leave-one-subject-out cross-validation. Results: The best model separated treatment responders (n = 24) from nonresponders based on pre-treatment dACC reactivity (83% accuracy, P = 0.001). Responders had greater pre-treatment dACC reactivity than nonresponders especially in the SSRI+CBT group. No other variable was associated with clinical response or added predictive accuracy to the dACC SVM model. Limitations: Small sample size, especially for genetic analyses. No replication or validation samples were available. Conclusions: The findings demonstrate that treatment outcome predictions based on neural cingulate activity, at the individual level, outperform genetic, demographic, and clinical variables for medication-assisted Internet-delivered CBT, supporting the use of neuroimaging in precision psychiatry.</p>}},
author = {{Frick, Andreas and Engman, Jonas and Alaie, Iman and Björkstrand, Johannes and Gingnell, Malin and Larsson, Elna Marie and Eriksson, Elias and Wahlstedt, Kurt and Fredrikson, Mats and Furmark, Tomas}},
issn = {{0165-0327}},
keywords = {{CBT; Pattern recognition; Personalized medicine; Social phobia; SSRI; SVM}},
language = {{eng}},
pages = {{230--237}},
publisher = {{Elsevier}},
series = {{Journal of Affective Disorders}},
title = {{Neuroimaging, genetic, clinical, and demographic predictors of treatment response in patients with social anxiety disorder}},
url = {{http://dx.doi.org/10.1016/j.jad.2019.10.027}},
doi = {{10.1016/j.jad.2019.10.027}},
volume = {{261}},
year = {{2020}},
}