Validation and Extension of a Risk Calculator to Predict Mood Recurrence in Young People with Bipolar Disorder

Given the episodic nature of bipolar disorder (BD) and the variability in mood episode recurrence across individuals, accurate recurrence prediction is critical. The original COBY recurrence risk calculator (RC) was developed in a longitudinal youth cohort to estimate threshold recurrence risk. However, its accuracy for predicting subthreshold recurrences had not been fully evaluated. The objective of this study was to extend the previously developed COBY mood recurrence RC to predict both threshold and subthreshold mood recurrences and evaluate its performance in an independent sample.

Adolescents and young adults with BD-I/II (N= 51; BD-I: 38, BD-II: 13; 14-24 years old) were interviewed with standard instruments at intake and during the follow-up on average every 6 months for a median of 54 weeks. We assessed the degree to which the COBY RC predicted mood recurrence (threshold or subthreshold) in this independent sample. Discrimination was measured using the area under the receiver operating characteristic curves (AUC); calibration and variable importance were also assessed.

The model demonstrated good prediction of any recurrence within the next six months (any threshold recurrence AUC = 0.72, any subthreshold or worse recurrence AUC = 0.77). Calibration analysis demonstrated the model tended to overestimate risk in the external sample, plausibly attributable to differences in recurrence ascertainment strategy (prospective vs retrospective) or the significant difference in prior remission length, a key predictor. Recalibration greatly improved calibration without loss of discrimination.

The mood recurrence RC demonstrated good discrimination for both threshold and subthreshold mood recurrences in an independent young adult cohort, consistent with prior youth and adult validations. Validation now spans across developmental stages and different degrees of severity of mood symptoms opening the opportunity for clinical implementation to provide personalized monitoring and early intervention for people with BD.