Using pre-treatment de novo threat conditioning outcomes to predict treatment response to DCS augmentation of exposure-based CBT.
J Psychiatr Res
; 164: 357-363, 2023 08.
Article
em En
| MEDLINE
| ID: mdl-37399757
BACKGROUND: Over a decade and a half of research has resulted in inconsistent evidence for the efficacy of d-cycloserine (DCS), a partial glutamatergic N-methyl-D-aspartate agonist, for augmenting exposure-based cognitive behavioral therapy (CBT) for anxiety- and fear-based disorders. These variable findings have motivated the search for moderators of DCS augmentation efficacy. METHODS: In this secondary analysis of a previous randomized clinical trial, we evaluated the value of de novo threat conditioning outcomes-degree of threat acquisition, extinction, and extinction retention-for predicting treatment response to exposure-based CBT for social anxiety disorder, applied with and without DCS augmentation in a sample of 59 outpatients. RESULTS: We found that average differential skin conductance response (SCR) during extinction and extinction retention significantly moderated the prediction of clinical response to DCS: participants with poorer extinction and extinction retention showed relatively improved treatment response with DCS. No such effects were found for expectancy ratings, consistent with accounts of DCS selectively aiding lower-order but not higher-order extinction learning. CONCLUSIONS: These findings provide support for extinction and extinction retention outcomes from threat conditioning as potential pre-treatment biomarkers for DCS augmentation benefits. Independent of DCS augmentation, the current study did not support threat conditioning outcomes as useful for predicting response to exposure-based CBT.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Terapia Cognitivo-Comportamental
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Ciclosserina
Tipo de estudo:
Clinical_trials
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Evaluation_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
J Psychiatr Res
Ano de publicação:
2023
Tipo de documento:
Article