Low trait anxiety, high resilience, and their interaction as possible predictors for treatment response in patients with depression.

BACKGROUND: Although many demographic and clinical characteristics have been suggested to predict treatment outcome of depression, they provide only a weak prediction for clinical response. Based on the predictive values of trauma and biological markers involved in stress response, we investigated the roles of baseline trait anxiety and resilience, which were assumed as vulnerability and resilience factors, respectively, in predicting treatment response in naturalistically treated outpatients with depressive disorders.
METHODS: A total of 178 outpatients with depressive disorders were consecutively recruited and completed measures of trauma experiences, psychological symptoms, and resilience at baseline. Response was defined by Clinical Global Impression (CGI)-Improvement score ≤2 at last visit during a 6month-treatment period. Univariate analyses and multiple logistic regression analysis were performed to determine predictors of treatment response.
RESULTS: Among demographic and clinical variables, treatment response was associated with increased age, longer treatment duration, higher resilience, and lower trait anxiety. In logistic regression analysis, resilience, trait anxiety, and their interaction significantly predicted treatment response after adjusting for age and treatment duration. Interaction between resilience and trait anxiety remained significant in the final model. Examining the interaction between the two, patients with low trait anxiety were only significantly affected by the level of resilience in response rate.
CONCLUSIONS: Low trait anxiety, high resilience, and their interaction might contribute to better treatment response in depressed patients. Our result suggested that individual differences in responding to stress might be important in predicting treatment outcome of depression in addition to other demographic and clinical factors.