Risk calculators (RC) to predict clinical outcomes are gaining interest. A RC to estimate risk of bipolar spectrum disorders (BPSD) could help reduce the duration of undiagnosed BPSD and improve outcomes. Our objective was to adapt a RC previously validated in the Pittsburgh Bipolar Offspring study sample (BIOS; Hafeman et al., 2017) to achieve adequate predictive ability in both familial high risk and clinical high risk youth.
Participants (aged 6-12 at baseline) from the Longitudinal Assessment of Manic Symptoms (LAMS) study (N=473) were evaluated semi-annually. Evaluations included a KSADS interview. After testing a RC that closely approximated the original, we made modifications to improve model prediction. Models were trained in the BIOS sample and tested in LAMS. The final model was then trained in LAMS participants, including family history of BPSD as a predictor, and tested in the familial high-risk sample.
Over follow-up, 65 youth newly met criteria for BPSD. The original RC identified youth who developed BPSD only moderately well (AUC = 0.67). Eliminating predictors other than the KSADS screening items for mania and depression improved accuracy (AUC=0.73) and generalizability. The model trained in LAMS, including family history as a predictor, performed well in the BIOS sample (AUC=0.74).
The clinical circumstances under which the assessment of symptoms occurs impacts RC accuracy; focusing on symptoms related to the onset of BPSD improved generalizability. Validation of the RC under clinically-realistic circumstances will be an important next step.

Copyright © 2020. Published by Elsevier Inc.

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