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Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases.

ABSTRACT: Monitoring mental health treatment outcomes for populations requires an understanding as to which patient information is needed in electronic format and is feasible to obtain in routine care.To examine whether bipolar disorder outcomes can be accurately predicted and how much clinical detail is needed to do so. RESEARCH DESIGN, DATA SOURCES, AND PARTICIPANTS: Longitudinal study of bipolar disorder patients treated during 2000 to 2004 in the 19-site Systematic Treatment Enhancement Program for Bipolar Disorder observational study arm (N=3168). Clinical data were obtained at baseline and quarterly for over 1 year. We fit a "gold standard" longitudinal random-effects regression model using a detailed clinical information and estimated the area under the receiver operating characteristic curve (AUC) to predict accuracy using a validation sample. The model was then modified to include patient characteristics feasible in routinely collected electronic data (eg, administrative data). We compared the AUCs for the "limited-detail" and gold standard models, testing for differences between the AUCs using the validation sample.Remission, defined as Montgomery-Asberg Depression Rating Scale score <5 and Young Mania Rating Scale score <4.The gold standard models had baseline AUC=0.80 (95% confidence interval=0.74 to 0.86) and 0.75(0.64 to 0.86) at 1-year follow-up. The predicted accuracies of the limited-detail model were lower at baseline [AUC=0.67(0.60 to 0.75)]; correlated test ?=14.25, P=0.002] and not statistically different from the gold standard model at 1 year [AUC=0.67(0.54-0.80); correlated test ?=2.88, P=0.090].Future work is needed to develop clinically accurate and feasible models to predict bipolar disorder outcomes. Clinically detailed and limited models performed similarly for shorter-term prediction at 1-year; however, there is room for improvement in prediction accuracy.

SUBMITTER: Busch AB

PROVIDER: S-EPMC4979222 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases.

Busch Alisa B AB Neelon Brian B Zelevinsky Katya K He Yulei Y Normand Sharon-Lise T SL

Medical care 20120401 4

<h4>Background</h4>Monitoring mental health treatment outcomes for populations requires an understanding as to which patient information is needed in electronic format and is feasible to obtain in routine care.<h4>Objective</h4>To examine whether bipolar disorder outcomes can be accurately predicted and how much clinical detail is needed to do so. RESEARCH DESIGN, DATA SOURCES, AND PARTICIPANTS: Longitudinal study of bipolar disorder patients treated during 2000 to 2004 in the 19-site Systematic ...[more]

PMID: 22210540

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Project description:ObjectiveThe Course and Outcome of Bipolar Youth study found that children and adolescents with bipolar spectrum disorders followed 1 of 4 distinct mood trajectories over 8 years of follow-up, with as many as 25% of participants showing a predominantly euthymic course. We evaluated whether similar patterns of illness course are observed in adolescents with bipolar I and II disorder who participated in a 2-year clinical trial.MethodA total of 144 adolescents with bipolar I or II disorder, identified shortly after a mood episode, were assessed over a 2-year period. Participants were randomly assigned to one of 2 psychosocial family treatments during the first 9 months of the study, and pharmacotherapy was provided throughout the 2 years. Using latent class growth analyses, we classified participants into distinct courses of illness based on mood ratings collected over the 2 years. We examined demographic and illness variables as predictors of these course classifications.ResultsLatent class growth analyses indicated four mood trajectories: "predominantly euthymic" (29.9% of sample), "ill with significantly improving course" (11.1%), "moderately euthymic" (26.4%), and "ill with moderately improving course" (32.6%). Adolescents in these classes were euthymic 77.7%, 53.6%, 44.1%, and 18.6% of the weeks of follow-up, respectively. Psychosocial treatment condition and baseline medication exposure were not associated with trajectories. However, youth with more severe baseline depressive symptoms, suicidality, lower quality of life scores, and minority race/ethnicity had more symptomatic courses of illness over time.ConclusionA substantial proportion (25%-30%) of youth with bipolar I or II disorder maintain euthymic states over extended periods of follow-up. Identifying youth who are more and less likely to remain stable over time may help guide psychosocial and pharmacological treatments after an illness episode.Clinical trial registration informationEffectiveness of Family-Focused Treatment Plus Pharmacotherapy for Bipolar Disorder in Adolescents; https://clinicaltrials.gov/; NCT00332098.

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Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases.

Publications

Accurately predicting bipolar disorder mood outcomes: implications for the use of electronic databases.

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