The predictors of remission in major depressive disorder
Date
2013
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Abstract
Background: We aimed to determine the predictors of remission in major depressive disorder (MDD) with antidepressant treatment (AT). Methods: The subjects were recruited from the databases of the previous four studies. 178 patients were separated in to two groups at the final visit regarding remission. The patients were analyzed in terms of sociodemographic and clinical features regardless of their AT. Results: The difference in sociodemographic and clinical features was insignificant between the groups. Remitted patients had lower scores on the Hamilton Depression Rating Scale (HDRS), Montgomery-Asberg Depression Scale, Hamilton Anxiety Rating Scale, and the Clinical Global Impression Scale compared to baseline whereas Social Adaptation Self-evaluation Scale (SASS) scores were higher. To evaluate the impact of basal scores of HDRS and SASS on non remission rates, logistic regression analysis was performed. The analysis result was significant (p<0.001). Valid classification rate was 66% for this model. For this model, the scores of HDRS and SASS at visit 1 are significant risk factors for non-remission (p<0.001). As the value of HDRS increases, the risk of non-remission increases 1.095 fold (Odds ratio 95%, confidence interval: 1.045-1.147), whereas as the value of SASS decreases the risk of non-remission increases 1, 076 fold (Odds ratio 95%, confidence interval: 1.042-1.114). For each patient non-remission possibility can be predicted by "p(non remission)=1/[(1+exp (-0, 093xV1HDRS+0, 075xV1SASS)]" equivalent via this model. Conclusion: The findings of the present study suggest that severe level of depression, anxiety and social maladaptation at baseline are more likely to predict remission.
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Keywords
Neurosciences & neurology, Major depressive disorder, Remission, Antidepressant, Post-hoc analysis, Clinical predictors, Treatment response, Family-history, Rating-scale, Double-blind, Efficacy, Sertraline, Tolerability
Citation
Zengin, S. (2013). “The predictors of remission in major depressive disorder”. Noropsikiyatri Arsivi, 50(2), 122-129.