The apparent efficacy of d-cycloserine (DCS) for enhancing exposure treatment for anxiety disorders appears to have declined over the past 14 years. We examined whether variations in how DCS has... Show moreThe apparent efficacy of d-cycloserine (DCS) for enhancing exposure treatment for anxiety disorders appears to have declined over the past 14 years. We examined whether variations in how DCS has been administered can account for this “declining effect”. We also investigated the association between DCS administration characteristics and treatment outcome to find optimal dosing parameters. We conducted a secondary analysis of individual participant data obtained from 1047 participants in 21 studies testing the efficacy of DCS-augmented exposure treatments. Different outcome measures in different studies were harmonized to a 0-100 scale. Intent-to-treat analyses showed that, in participants randomized to DCS augmentation (n = 523), fewer DCS doses, later timing of DCS dose, and lower baseline severity appear to account for this decline effect. More DCS doses were related to better outcomes, but this advantage leveled-off at nine doses. Administering DCS more than 60 minutes before exposures was also related to better outcomes. These predictors were not significant in the placebo arm (n = 521). Results suggested that optimal DCS administration could increase pre-to-follow-up DCS effect size by 50%. In conclusion, the apparent declining effectiveness of DCS over time may be accounted for by how it has been administered. Optimal DCS administration may substantially improve outcomes. Show less
Objective: Network analysis allows us to identify the most interconnected (i.e., central) symptoms, and multiple authors have suggested that these symptoms might be important treatment targets.... Show moreObjective: Network analysis allows us to identify the most interconnected (i.e., central) symptoms, and multiple authors have suggested that these symptoms might be important treatment targets. This is because change in central symptoms (relative to others) should have greater impact on change in all other symptoms. It has been argued that networks derived from cross-sectional data may help identify such important symptoms. We tested this hypothesis in social anxiety disorder. Method: We first estimated a state-of-the-art regularized partial correlation network based on participants with social anxiety disorder (n = 910) to determine which symptoms were more central. Next, we tested whether change in these central symptoms were indeed more related to overall symptom change in a separate dataset of participants with social anxiety disorder who underwent a variety of treatments (n = 244). We also tested whether relatively superficial item properties (infrequency of endorsement and variance of items) might account for any effects shown for central symptoms. Results: Centrality indices successfully predicted how strongly changes in items correlated with change in the remainder of the items. Findings were limited to the measure used in the network and did not generalize to three other measures related to social anxiety severity. In contrast, infrequency of endorsement showed associations across all measures. Conclusions: The transfer of recently published results from cross-sectional network analyses to treatment data is unlikely to be straightforward. (PsycINFO Database Record (c) 2018 APA, all rights reserved) Show less
Mataix-Cols, D.; Fernandez de la Cruz, L.; Monzani, B.; Rosenfield, D.; Andersson, E.; Perez-Vigil, A.; ... ; C. 2017
