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

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.

Conflict of interest statement

Conflict of Interest Disclosures: Dr Hafeman reported receiving funding from The Klingenstein Third Generation Foundation. Dr T. R. Goldstein reported receiving grant funding from the National Institute of Mental Health (NIMH), the Brain & Behavior Research Foundation, and the American Foundation for Suicide Prevention and reported receiving royalties from Guilford Press. Dr Axelson reported serving as a consultant to Janssen Research, reported receiving grant support from Neuronetics, and reported receiving royalties from UpToDate. Dr Sakolsky reported receiving research support from the NIMH and the National Alliance for Research on Schizophrenia and Depression, reported receiving an honorarium from the American Academy of Child and Adolescent Psychiatry for continuing medical education work, reported serving as an editorial board member of Child and Adolescent Psychopharmacology News, reported serving as a specialty consultant for Prescriber’s Letter, and reported serving as a paid consultant to L.E.K. Consulting. Dr Brent reported receiving royalties from Guilford Press; reported receiving royalties from the electronic self-rated version of the Columbia–Suicide Severity Rating Scale (C-SSRS) from eResearch Technology, Inc (ERT); reported receiving consulting fees from Lundbeck; and reported serving as an UpToDate psychiatry section editor. Dr Kupfer reported serving as a consultant to the American Psychiatric Association (as chair of the DSM-5 Task Force), reported having joint ownership of copyright for the Pittsburgh Sleep Quality Index, reported being a member of the Valdoxan Advisory Board of Servier International, and reported being a stockholder in AliphCom, HealthRhythms, Inc, and Psychiatric Assessments, Inc. Dr Birmaher reported receiving royalties from American Psychiatric Publishing, Random House, Lippincott Williams & Wilkins, and UpToDate and reported serving as a consultant to Janssen Research. No other disclosures were reported.

Figures

Figure 1.. Frequency Distributions of 5-Year Risk Among Converters to Bipolar Spectrum Disorder and Nonconverters

Most nonconverters show risk scores of 0.08 or less, while most converters show risk scores above this value.

Figure 2.. Calibration Plot of Model-Predicted 5-Year Risk

Shown are predicted and observed frequencies of new-onset bipolar spectrum disorder across a range of predicted risks. Predicted and observed frequencies are similar, indicating that the model is well calibrated. The diagonal straight line represents perfect calibration.