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

Published on Aug 1, 2017in JAMA Psychiatry15.916
· DOI :10.1001/jamapsychiatry.2017.1763
Danella Hafeman16
Estimated H-index: 16
(University of Pittsburgh),
John Merranko7
Estimated H-index: 7
(University of Pittsburgh)
+ 11 AuthorsBoris Birmaher7
Estimated H-index: 7
(University of Pittsburgh)
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.
  • References (36)
  • Citations (31)
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References36
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#1Francesco Bernardini (University of Perugia)H-Index: 6
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We conducted a systematic, qualitative review of risk prediction models designed and tested for depression, bipolar disorder, generalized anxiety disorder, posttraumatic stress disorder, and psychotic disorders. Our aim was to understand the current state of research on risk prediction models for these 5 disorders and thus future directions as our field moves toward embracing prediction and prevention.Systematic searches of the entire MEDLINE electronic database were conducted independently by 2...
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Last. Philip McGuire ('KCL': King's College London)H-Index: 110
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Importance The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined. Objective To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health c...
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#2Barbara A. Cornblatt (UM: University of Michigan)H-Index: 38
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Objective:As part of the second phase of the North American Prodrome Longitudinal Study (NAPLS-2), Cannon and colleagues report, concurrently with the present article, on a risk calculator for the individualized prediction of a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS-2 psychosis risk calculator using an independent sample of patients at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prev...
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Objective: To evaluate the presence of affective signs and symptoms as precursors of bipolar disorder in prospective studies, including assessment of their prevalence, duration, and predictive value. Data Sources: We followed PRISMA guidelines to search PubMed, CINAHL, PsycINFO, EMBASE, SCOPUS, and ISI Web of Science databases to May 31, 2013, using the terms bipolar disorder AND (antecedent* OR predict* OR prodrom* OR prospect*) AND (diagnosis OR development). Hand searching of identified repor...
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