A risk calculator to predict suicide attempts among individuals with early-onset bipolar disorder

Objectives To build a one-year risk calculator (RC) to predict individualized risk for suicide attempt in early-onset bipolar disorder. Methods Youth numbering 394 with bipolar disorder who completed >= 2 follow-up assessments (median follow-up length = 13.1 years) in the longitudinal Course and Outcome of Bipolar Youth (COBY) study were included. Suicide attempt over follow-up was assessed via the A-LIFE Self-Injurious/Suicidal Behavior scale. Predictors from the literature on suicidal behavior in bipolar disorder that are readily assessed in clinical practice were selected and trichotomized as appropriate (presence past 6 months/lifetime history only/no lifetime history). The RC was trained via boosted multinomial classification trees; predictions were calibrated via Platt scaling. Half of the sample was used to train, and the other half to independently test the RC. Results There were 249 suicide attempts among 106 individuals. Ten predictors accounted for >90% of the cross-validated relative influence in the model (AUC = 0.82; in order of relative influence): (1) age of mood disorder onset; (2) non-suicidal self-injurious behavior (trichotomized); (3) current age; (4) psychosis (trichotomized); (5) socioeconomic status; (6) most severe depressive symptoms in past 6 months (trichotomized none/subthreshold/threshold); (7) history of suicide attempt (trichotomized); (8) family history of suicidal behavior; (9) substance use disorder (trichotomized); (10) lifetime history of physical/sexual abuse. For all trichotomized variables, presence in the past 6 months reliably predicted higher risk than lifetime history. Conclusions This RC holds promise as a clinical and research tool for prospective identification of individualized high-risk periods for suicide attempt in early-onset bipolar disorder.

Automated summary

The study aims to establish a risk calculator for predicting the individualized risk for suicide attempts in early-onset bipolar disorder. The researchers selected readily assessed predictors from the literature and trained the risk calculator using boosted multinomial classification trees. The results show that the risk calculator holds promise for prospective identification of high-risk periods for suicide attempts in individuals with early-onset bipolar disorder.