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Original Investigation
August 2017

Assessment of a Person-Level Risk Calculator to Predict New-Onset Bipolar Spectrum Disorder in Youth at Familial Risk

Author Affiliations
  • 1Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 2Department of Psychiatry, Ohio State University, Columbus
  • 3Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
  • 4Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania
  • 5Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
JAMA Psychiatry. 2017;74(8):841-847. doi:10.1001/jamapsychiatry.2017.1763
Key Points

Question  Can a risk calculator be developed to predict, on the individual level, the risk of developing bipolar spectrum disorder in youth at familial risk for the disorder?

Findings  In an ongoing cohort study that included 412 offspring of parents with bipolar disorder (54 of whom developed bipolar spectrum disorder during follow-up), predictors from the literature were used to construct a risk calculator to distinguish those who would develop bipolar spectrum disorder in the next 5 years vs those who would not. The model (which included mood and anxiety symptoms, general psychosocial functioning, and parental age at mood disorder onset) discriminated with an area under the curve of 0.76, indicating good discrimination, comparable to risk calculators used clinically in other areas of medicine.

Meaning  This risk calculator is an important practical tool to inform clinical decisions (eg, frequency of monitoring) and research studies (eg, to help identify an ultra–high-risk group for studies of biomarkers and prevention).

Abstract

Importance  Early identification of individuals at high risk for the onset of bipolar spectrum disorder (BPSD) is key from both a clinical and research perspective. While previous work has identified the presence of a bipolar prodrome, the predictive implications for the individual have not been assessed, to date.

Objective  To build a risk calculator to predict the 5-year onset of BPSD in youth at familial risk for BPSD.

Design, Setting, and Participants  The Pittsburgh Bipolar Offspring Study is an ongoing community-based longitudinal cohort investigation of offspring of parents with bipolar I or II (and community controls), recruited between November 2001 and July 2007, with a median follow-up period of more than 9 years. Recruitment has ended, but follow-up is ongoing. The present analysis included offspring of parents with bipolar I or II (aged 6-17 years) who had not yet developed BPSD at baseline.

Main Outcomes and Measures  This study tested the degree to which a time-to-event model, including measures of mood and anxiety, general psychosocial functioning, age at mood disorder onset in the bipolar parent, and age at each visit, predicted new-onset BPSD. To fully use longitudinal data, the study assessed each visit separately, clustering within individuals. Discrimination was measured using the time-dependent area under the curve (AUC), predicting 5-year risk; internal validation was performed using 1000 bootstrapped resamples. Calibration was assessed by comparing observed vs predicted probability of new-onset BPSD.

Results  There were 412 at-risk offspring (202 [49.0%] female), with a mean (SD) visit age of 12.0 (3.5) years and a mean (SD) age at new-onset BPSD of 14.2 (4.5) years. Among them, 54 (13.1%) developed BPSD during follow-up (18 with BD I or II); these participants contributed a total of 1058 visits, 67 (6.3%) of which preceded new-onset BPSD within the next 5 years. Using internal validation to account for overfitting, the model provided good discrimination between converting vs nonconverting visits (AUC, 0.76; bootstrapped 95% CI, 0.71-0.82). Important univariate predictors of outcome (AUC range, 0.66-0.70) were dimensional measures of mania, depression, anxiety, and mood lability; psychosocial functioning; and parental age at mood disorder.

Conclusions and Relevance  This risk calculator provides a practical tool for assessing the probability that a youth at familial risk for BPSD will develop new-onset BPSD within the next 5 years. Such a tool may be used by clinicians to inform frequency of monitoring and treatment options and for research studies to better identify potential participants at ultra high risk of conversion.

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