Article

Clinical characteristics and treatment outcome in a representative sample of depressed inpatients - Findings from the Munich Antidepressant Response Signature (MARS) project

Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany.
Journal of Psychiatric Research (Impact Factor: 4.09). 07/2008; 43(3):215-29. DOI: 10.1016/j.jpsychires.2008.05.002
Source: PubMed

ABSTRACT Depression is a common and often difficult-to-treat clinical condition with a high rate of patients showing insufficient treatment response and persistence of symptoms. We report the characteristics of a representative sample of depressed inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Eight hundred and forty-two inpatients admitted to a psychiatric hospital for treatment of a major depressive episode, recurrent or bipolar depression were thoroughly characterized with respect to demographic factors, clinical history, and the degree of HPA-axis dysregulation evaluated by means of combined dex/CRH tests, and the predictive value of these factors for treatment outcome is investigated. 80.8% of patients responded to treatment (i.e., improvement in symptom severity of at least 50%) and 57.9% reached remission (i.e., near absence of residual depressive symptoms) at discharge after a mean treatment period of 11.8 weeks. Regression analysis identified early partial response (within 2 weeks) as the most important positive predictor for achieving remission. Previous ineffective treatment trials in the current episode and presence of a migration background are potent negative predictors for treatment outcome. In addition, remitters were characterized by a more pronounced normalization of an initially dysregulated HPA-axis. We could show that a large majority of inpatients suffering from depression benefits from antidepressant treatment during hospitalization. However, a considerable number of patients failed to achieve remission. We demonstrated that this subgroup can be characterized by a set of demographic, clinical and neuroendocrine variables allowing to predict unfavorable outcome at an early stage of treatment.

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    • ". Furthermore, neuroimaging studies that combine cognitive assessments with functional neuroimaging have potential for predicting antidepressant treatment response [138]. Combination of clinical and neuroendocrine features also improves prediction of treatment outcome [139]. The multifactorial nature of depressive illness suggests that a multifactorial approach will provide the most accurate predictions of treatment outcome. "
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