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Analysis of bipolar maintenance treatment with lithium versus olanzapine utilizing Multi‐state Outcome Analysis of Treatments ( MOAT )
Author(s) -
Tohen Mauricio,
Mintz Jim,
Bowden Charles L
Publication year - 2016
Publication title -
bipolar disorders
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.285
H-Index - 129
eISSN - 1399-5618
pISSN - 1398-5647
DOI - 10.1111/bdi.12383
Subject(s) - olanzapine , lithium (medication) , mania , bipolar disorder , outcome (game theory) , depression (economics) , psychology , survival analysis , medicine , clinical psychology , psychiatry , psychotherapist , schizophrenia (object oriented programming) , mathematics , mathematical economics , economics , macroeconomics
Objectives Survival analysis has superseded most other analytic techniques for maintenance treatment studies over recent decades, despite providing results based solely on a single time‐point predefined event. The aim of the present study was to develop the Multi‐state Outcome Analysis of Treatments (MOAT), to provide more pragmatic information for clinicians and investigators in guiding maintenance treatment decisions. The present study was one of two published studies on the development of MOAT procedures, involving a one‐year comparison of olanzapine versus lithium in recently manic patients. Methods MOAT partitions total survival time into clinically distinct periods that are operationally defined by cut points on established rating scales. For bipolar disorders, the clinical states are remission, subsyndromal and syndromal mania, mixed states, and subsyndromal and syndromal depression. Results MOAT re‐analyses of the clinical trial revealed clinically important findings not identified when utilizing Kaplan–Meier survival analyses. Compared to patients treated with lithium, patients taking olanzapine experienced significantly more time in subsyndromal depression. Patients taking lithium spent significantly more time in mixed states than did patients taking olanzapine. Conclusions MOAT provided detailed information on treatment outcomes that was not provided by Kaplan–Meier survival analysis. Its capability to identify and aggregate time in different clinical states of bipolar disorder may aid in identifying drug effects that are important in selecting and conducting maintenance treatment.

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