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Longitudinal Trajectories and Associated Baseline Predictors in Youths With Bipolar Spectrum Disorders
Boris Birmaher, M.D.; Mary Kay Gill, M.S.N.; David A. Axelson, M.D.; Benjamin I. Goldstein, M.D., Ph.D.; Tina R. Goldstein, Ph.D.; Haifeng Yu, M.S.; Fangzi Liao, M.S.; Satish Iyengar, Ph.D.; Rasim S. Diler, M.D.; Michael Strober, Ph.D.; Heather Hower, M.S.W.; Shirley Yen, Ph.D.; Jeffrey Hunt, M.D.; John A. Merranko, M.A.; Neal D. Ryan, M.D.; Martin B. Keller, M.D.
Am J Psychiatry 2014;171:990-999. doi:10.1176/appi.ajp.2014.13121577
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Dr. Birmaher has received research support from NIMH and receives royalties from Random House, Lippincott Williams & Wilkins, and UpToDate. Dr. B. Goldstein is a consultant for Bristol-Myers Squibb, has received research support from Pfizer, and has received speaking honoraria from Purdue Pharma. Dr. Strober receives support from the Resnick Endowed Chair in Eating Disorders. Dr. Hunt receives honoraria from Wiley Publishers as a senior editor of the Brown University Child and Adolescent Psychopharmacology Update. Dr. Keller has received research support from NIMH and Pfizer, has received honoraria from Medtronic, Cenerex, and Sierra Neuropharmaceuticals, and is on the advisory board for Cenerex. The other authors report no financial relationships with commercial interests.

Supported by NIMH grant MH059929.

From the Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, Pittsburgh; the Department of Psychiatry, Nationwide Children’s Hospital and Ohio State College of Medicine, Columbus; the Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto Medical Center, Toronto; the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles; the Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, R.I.; the Department of Psychiatry, Bradley Hospital, East Providence, R.I., and the Department of Psychiatry, Butler Hospital, Providence.

Address correspondence to Dr. Birmaher (birmaherb@upmc.edu).

Copyright © 2014 by the American Psychiatric Association

Received December 03, 2013; Revised February 20, 2014; Accepted March 27, 2014.

Abstract

Objective  The authors sought to identify and evaluate longitudinal mood trajectories and associated baseline predictors in youths with bipolar disorder.

Method  A total of 367 outpatient youths (mean age, 12.6 years) with bipolar disorder with at least 4 years of follow-up were included. After intake, participants were interviewed on average 10 times (SD=3.2) over a mean of 93 months (SD=8.3). Youths and parents were interviewed for psychopathology, functioning, treatment, and familial psychopathology and functioning.

Results  Latent class growth analysis showed four different longitudinal mood trajectories: “predominantly euthymic” (24.0%), “moderately euthymic” (34.6%), “ill with improving course” (19.1%), and “predominantly ill” (22.3%). Within each class, youths were euthymic on average 84.4%, 47.3%, 42.8%, and 11.5% of the follow-up time, respectively. Multivariate analyses showed that better course was associated with higher age at onset of mood symptoms, less lifetime family history of bipolar disorder and substance abuse, and less history at baseline of severe depression, manic symptoms, suicidality, subsyndromal mood episodes, and sexual abuse. Most of these factors were more noticeable in the “predominantly euthymic” class. The effects of age at onset were attenuated in youths with lower socioeconomic status, and the effects of depression severity were absent in those with the highest socioeconomic status.

Conclusions  A substantial proportion of youths with bipolar disorder, especially those with adolescent onset and the above-noted factors, appear to be euthymic over extended periods. Nonetheless, continued syndromal and subsyndromal mood symptoms in all four classes underscore the need to optimize treatment.

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FIGURE 1. Latent Class Growth Analysis Based on Percentage of Time Euthymic for Youths With Bipolar Disorder Who Had at Least 4 Years of Follow-Up
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TABLE 1.Duration of Follow-Up and Psychiatric Status Rating Scale Scores for Youths With Bipolar Disorder During Longitudinal Follow-Upa
Table Footer Note

a Superscripts denote significant between-class differences, with p values ≤0.05 after Bonferroni correction.

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b Measured by comparing the mean standard deviations over follow-up.

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TABLE 2.Baseline Demographic and Clinical Characteristics of Youths With Bipolar Disordera
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a Superscripts denote significant between-class differences, with p values ≤0.05 after Bonferroni correction.

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TABLE 3.History of Psychiatric Treatment and Exposure to Psychotropic Medications in Youths With Bipolar Disordera
Table Footer Note

a Superscripts denote significant between-class differences, with p values ≤0.05 after Bonferroni correction.

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TABLE 4.Family (First- and Second-degree), Maternal, and Paternal Lifetime Psychiatric History of Youths With Bipolar Disordera
Table Footer Note

a Superscripts denote significant between-class differences, with p values ≤0.05 after Bonferroni correction. ADHD=attention deficit hyperactivity disorder.

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TABLE 5.Comparison of Significant Variables From the Multivariate Analyses Among the Four Mood Trajectory Classesa
Table Footer Note

a Class 1: predominantly euthymic; class 2: moderately euthymic; class 3: ill with improving course; class 4: predominantly ill.

Table Footer Note

b There were significant interactions between socioeconomic status and child’s age at onset of mood symptoms and child’s severity of depression. The effects of age at onset decreased in youths with lower socioeconomic status, and the effects of depression severity decreased in those with higher socioeconomic status.

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1.
Based on the Psychiatric Status Rating Scale scores that represent euthymia (≤2), what percentages of youths with bipolar spectrum disorders had overall longitudinal courses identified as “predominantly euthymic,” “moderately euthymic,” “ill with improving course,” and “predominantly ill,” respectively?
2.
Which of the following is an observation from this study that reflects a more optimistic perspective on the course of Bipolar Spectrum Disorders as opposed to a universally chronic course?
3.
Which factors were associated with better longitudinal course of bipolar disorder?
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