Anna R Van Meter1, Danella M Hafeman2, John Merranko2, Eric A Youngstrom3, Boris B Birmaher2, Mary A Fristad4, Sarah M Horwitz5, L Eugene Arnold6, Robert L Findling7. 1. The Feinstein Institutes for Medical Research, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, and The Zucker Hillside Hospital, Glen Oaks, New York. Electronic address: avanmeter@northwell.edu. 2. The University of Pittsburgh Medical Center, Pennsylvania. 3. University of North Carolina at Chapel Hill. 4. The Ohio State University College of Medicine, Columbus, Ohio; Nationwide Children's Hospital, Columbus, Ohio. 5. New York University Grossman School of Medicine, New York. 6. The Ohio State University College of Medicine, Columbus, Ohio. 7. Virginia Commonwealth University, Richmond, Virginia.
Abstract
OBJECTIVE: Risk calculators (RC) to predict clinical outcomes are gaining interest. An 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 an RC previously validated in the Pittsburgh Bipolar Offspring Study (BIOS) sample to achieve adequate predictive ability in both familial high-risk and clinical high-risk youths. METHOD: Participants (aged 6-12 years at baseline) from the Longitudinal Assessment of Manic Symptoms (LAMS) study (N = 473) were evaluated semi-annually. Evaluations included a Kiddie Schedule for Affective Disorders (K-SADS) interview. After testing an RC that closely approximated the original, we made modifications to improve model prediction. Models were trained in the BIOS data, which included biennial K-SADS assessments, 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. RESULTS: Over follow-up, 65 youths newly met criteria for BPSD. The original RC identified youths who developed BPSD only moderately well (area under the curve [AUC] = 0.67). Eliminating predictors other than the K-SADS 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). CONCLUSION: The clinical circumstances under which the assessment of symptoms occurs affects 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.
OBJECTIVE: Risk calculators (RC) to predict clinical outcomes are gaining interest. An 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 an RC previously validated in the Pittsburgh Bipolar Offspring Study (BIOS) sample to achieve adequate predictive ability in both familial high-risk and clinical high-risk youths. METHOD: Participants (aged 6-12 years at baseline) from the Longitudinal Assessment of Manic Symptoms (LAMS) study (N = 473) were evaluated semi-annually. Evaluations included a Kiddie Schedule for Affective Disorders (K-SADS) interview. After testing an RC that closely approximated the original, we made modifications to improve model prediction. Models were trained in the BIOS data, which included biennial K-SADS assessments, 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. RESULTS: Over follow-up, 65 youths newly met criteria for BPSD. The original RC identified youths who developed BPSD only moderately well (area under the curve [AUC] = 0.67). Eliminating predictors other than the K-SADS 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). CONCLUSION: The clinical circumstances under which the assessment of symptoms occurs affects 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.
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