Literature DB >> 16012276

Empirical testing of two models for staging antidepressant treatment resistance.

Timothy Petersen1, George I Papakostas, Michael A Posternak, Alexis Kant, Wendy M Guyker, Dan V Iosifescu, Albert S Yeung, Andrew A Nierenberg, Maurizio Fava.   

Abstract

BACKGROUND: An increasing amount of attention has been paid to treatment resistant depression. Although it is quite common to observe nonremission to not just one but consecutive antidepressant treatments during a major depressive episode, a relationship between the likelihood of achieving remission and one's degree of resistance is not clearly known at this time. This study was undertaken to empirically test 2 recent models for staging treatment resistance.
MATERIALS AND METHODS: Psychiatrists from 2 academic sites reviewed charts of patients on their caseloads. Clinical Global Impressions-Severity (CGI-S) and Clinical Global Impressions-Improvement (CGI-I) scales were used to measure severity of depression and response to treatment, and 2 treatment-resistant staging scores were classified for each patient using the Massachusetts General Hospital staging method (MGH-S) and the Thase and Rush staging method (TR-S).
RESULTS: Out of the 115 patient records reviewed, 58 (49.6%) patients remitted at some point during treatment. There was a significant positive correlation between the 2 staging scores, and logistic regression results indicated that greater MGH-S scores, but not TR-S scores, predicted nonremission.
CONCLUSIONS: This study suggests that the hierarchical manner in which the field has typically gauged levels of treatment resistance may not be strongly supported by empirical evidence. This study suggests that the MGH staging model may offer some advantages over the staging method by Thase and Rush, as it generates a continuous score that considers both number of trials and intensity/optimization of each trial.

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Year:  2005        PMID: 16012276     DOI: 10.1097/01.jcp.0000169036.40755.16

Source DB:  PubMed          Journal:  J Clin Psychopharmacol        ISSN: 0271-0749            Impact factor:   3.153


  29 in total

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