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Although there have been many attempts to find predictors of therapeutic response to antidepressant treatment of obsessive-compulsive disorder (OCD), few reports have evaluated the joint predictive value of a number of clinical characteristics. This study aimed to identify clinical predictors of outcome in OCD, and to develop an easily applicable method to predict response to drug treatment. One hundred and fifty patients with primary OCD according to DSM-IV criteria were randomly assigned in a 12-week, double-blind, comparison trial with a selective serotonin reuptake inhibitor (paroxetine), and a serotonin-noradrenaline reuptake inhibitor (venlafaxine). The primary efficacy parameter was the Yale-Brown obsessive-compulsive scale (Y-BOCS) score, and response to treatment was prospectively defined as a >/= 35% decrease from the beginning. A stepwise multivariate analysis was used to identify predictors. The absence of previous therapies, moderate baseline severity of obsessive-compulsive symptoms (Y-BOCS score < 23), and low Hamilton Depressive Rating Scale scores (6-15) were found to be prognostic determinants of good response to pharmacotherapy. The prognostic ability of the prediction model to discriminate between responders and non-responders was quantified as the area under the receiver operating/operator characteristic curve (ROC area), which was 0.71 (95% confidence interval 0.63-0.8), demonstrating a reasonable discriminatory power. This study is the first to present a model that can estimate by the use of prediction rules the probability of treatment response to antidepressants in patients with OCD.
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