ReviewInstruments that prospectively predict bipolar disorder – A systematic review
Introduction
Bipolar disorder (BD) can be a debilitating and recurrent illness and is a leading world-wide cause of medical disability (Whiteford et al., 2013). The universal prevalence and the peak age of onset in the most productive and developmentally significant life years contribute to the magnitude of this disability. Early Intervention (EI) for BD is an evolving concept that may help limit morbidity and improve functional outcomes, as it has for persons with psychotic disorders (Berk et al., 2007). Early intervention refers to the process of detecting incipient or emerging BD and providing interventions in its earliest illness stages. The finding that cognitive and general functioning may be preserved in the pre-illness stages of BD with a decline after the onset of first manic episodes (Lewandowski et al., 2011), provides a strong imperative for interventions as early as feasible in the illness course. The availability of therapeutic approaches such as family-focused treatments (Miklowitz et al., 2013) may also assist in intervention for at-risk youth. However, a strong limitation in the progress of preventive efforts in BD has been the difficulty in identifying people at risk of developing BD due to a lack of validated instruments.
The reviews to date have focused on screening for BD especially among sub-populations such as pregnant and post partum women, children, adolescents and young adults (Chessick and Dimidjian, 2010, Waugh et al., 2014, Youngstrom et al., 2004). While screening may bring diagnosis forward, the detection of pre-manic states requires identification of instruments that have prospective predictive validity for BD. Prospective follow-up studies of a range of different cohorts including depressed patients (Fiedorowicz et al., 2011), youth with ADHD (Biederman et al., 2009), children and adolescent offspring of bipolar (Duffy et al., 2009) and depressed (Meyer et al., 2009) parents, and university (Kwapil et al., 2000) or general population samples (Papachristou et al., 2013) have identified a number of instruments that may have value in predicting BD onset. A few of these studies have specifically examined the predictive properties of instruments with a prioi hypotheses, while others have not. The instruments supported by the former studies may have greater validity and utility in EI settings where prevention of BD may be considered. Thus, the first aim of this paper was to systematically identify the predictive properties of the instruments that have been used for predicting BD onset. The second aim was to examine the utility of these instruments in EI or high-risk settings.
Section snippets
Search strategy
A systematic literature search was conducted in March 2014 using PubMed and PsychINFO using the following search terms: screening, early detection or prediction; bipolar, mania, or hypomania; instrument, schedule, questionnaire, scale, approach or tool; and longitudinal, predictive or prospective. The search was limited to abstracts instead of full texts for PsychINFO. Other reviews on screening of BD, prediction of BD and conversion from other diagnoses to BD were also examined (Cerimele et
Results
Study selection:
Among the 1018 articles that were identified using the search criteria, 959 studies were excluded as: (a) they only reported diagnostic accuracy with respect to screening; (b) the ‘predictive’ properties described were based on cross-sectional data; and/or (c) the reports were not relevant for the review (Fig. 1).
Twenty-four articles were selected for detailed examination of the inclusion and exclusion criteria as they related to prospective evaluations of BD onset. Six studies
Discussion
In this review we identified instruments that were able to detect BD I or II prior to onset in a systematic manner. We also examined the instruments for their validity and utility in predicting BD. The availability of such instruments is of particular significance in primary care and early intervention settings where at-risk individuals may be identified. Individuals so identified to be at an earlier stage of BD may benefit from specific and non-specific interventions that may assist in
Role of the funding source
None.
Contributors
Dr Aswin Ratheesh was responsible for conceptualization of the study, data search, inclusion of studies, extraction of data and preparation of the manuscript.
Drs Christopher Davey, Michael Berk, Patrick McGorry and Susan Cotton were responsible for supervision of and assistance with the conceptualization of the study, development of the search strategy, development of selection criteria, data analysis and manuscript preparation.
Conflicts of interest
Nil.
Acknowledgments
MB is supported by an NHMRC Senior Principal Research Fellowship 1059660. SC and CD are supported by NHMRC Career Development Fellowships 1061998 and 1061757 respectively. Dr Jim Berryman from the University of Melbourne Library assisted in developing the search strategy.
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