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A Risk Calculator to Predict the Individual Risk of Conversion From Subthreshold Bipolar Symptoms to Bipolar Disorder I or II in Youth

Published on Oct 1, 2018in Journal of the American Academy of Child and Adolescent Psychiatry6.39
· DOI :10.1016/j.jaac.2018.05.023
Boris Birmaher91
Estimated H-index: 91
(University of Pittsburgh),
John Merranko7
Estimated H-index: 7
(University of Pittsburgh)
+ 10 AuthorsMartin B. Keller116
Estimated H-index: 116
(Brown University)
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Abstract
Objective Youth with subthreshold mania are at increased risk of conversion to bipolar disorder (BP) I/II. Predictors for conversion have been published for the group as a whole. However, risk factors are heterogeneous, indicating the need for personalized risk assessment. Method One hundred forty youth with BP not otherwise specified (BP-NOS; 6–17 years old) followed through the Course and Outcome of Bipolar Youth (COBY) study with at least 1 follow-up assessment before conversion to BP-I/II were included. Youths were assessed on average every 7 months (median 11.5 years) using standard instruments. Risk predictors reported in the literature were used to build a 5-year risk calculator. Discrimination was measured using the time-dependent area under the curve after 1,000 bootstrap resamples. Calibration was evaluated by comparing observed with predicted probability of conversion. External validation was performed using an independent sample of 58 youths with BP-NOS recruited from the Pittsburgh Bipolar Offspring Study. Results Seventy-five (53.6%) COBY youths with BP-NOS converted to BP-I/II, of which 57 (76.0%) converted within 5 years. Earlier-onset BP-NOS, familial hypomania/mania, and high mania, anxiety, and mood lability symptoms were important predictors of conversion. The calculator showed excellent consistency between the predicted and observed risks of conversion, good discrimination between converters and non-converters (area under the curve 0.71, CI 0.67–0.74), and a proportionally increasing rate of converters at each successive risk class. Discrimination in the external validation sample was good (area under the curve 0.75). Conclusion If replicated, the risk calculator would provide a useful tool to predict personalized risk of conversion from subsyndromal mania to BP-I/II and inform individualized interventions and research.
  • References (42)
  • Citations (2)
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References42
Newest
Published on Sep 1, 2018in Statistical Methods in Medical Research2.39
Booil Jo31
Estimated H-index: 31
(Stanford University),
Robert L. Findling71
Estimated H-index: 71
(Johns Hopkins University)
+ 8 AuthorsMary Kay Gill25
Estimated H-index: 25
(University of Pittsburgh)
In establishing prognostic models, often aided by machine learning methods, much effort is concentrated in identifying good predictors. However, the same level of rigor is often absent in improving the outcome side of the models. In this study, we focus on this rather neglected aspect of model development. We are particularly interested in the use of longitudinal information as a way of improving the outcome side of prognostic models. This involves optimally characterizing individuals’ outcome s...
Published on Aug 1, 2017in JAMA Psychiatry15.92
Danella Hafeman16
Estimated H-index: 16
(University of Pittsburgh),
John Merranko7
Estimated H-index: 7
(University of Pittsburgh)
+ 11 AuthorsSatish Iyengar50
Estimated H-index: 50
(University of Pittsburgh)
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 ...
Published on May 24, 2017in The Journal of Clinical Psychiatry4.02
Francesco Bernardini6
Estimated H-index: 6
(University of Perugia),
Luigi Attademo6
Estimated H-index: 6
(University of Perugia)
+ 4 AuthorsMichael T. Compton42
Estimated H-index: 42
(Hofstra University)
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...
Published on May 1, 2017in JAMA Psychiatry15.92
Paolo Fusar-Poli62
Estimated H-index: 62
(NIHR: National Institute for Health Research),
Grazia Rutigliano13
Estimated H-index: 13
(UniPi: University of Pisa)
+ 4 AuthorsPhilip McGuire105
Estimated H-index: 105
('KCL': King's College London)
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...
Published on May 1, 2017in Bipolar Disorders4.94
Janet Wozniak48
Estimated H-index: 48
(Harvard University),
Mai Uchida12
Estimated H-index: 12
(Harvard University)
+ 6 AuthorsJoseph Biederman161
Estimated H-index: 161
(Harvard University)
Objectives To examine the validity of subthreshold pediatric bipolar I disorder (BP-I), we compared the familial risk for BP-I in the child probands who had either full BP-I, subthreshold BP-I, ADHD, or were controls that neither had ADHD nor bipolar disorder. Methods BP-I probands were youth aged 6−17 years meeting criteria for BP-I, full (N=239) or subthreshold (N=43), and also included were their first-degree relatives (N=687 and N=120, respectively). Comparators were youth with ADHD (N=162),...
Published on Apr 1, 2017in Early Intervention in Psychiatry3.32
Aswin Ratheesh10
Estimated H-index: 10
(University of Melbourne),
Sue Cottone43
Estimated H-index: 43
(University of Melbourne)
+ 5 AuthorsPatrick D. McGorry104
Estimated H-index: 104
(University of Melbourne)
Aim Early intervention and prevention of serious mental disorders such as bipolar disorder has the promise of decreasing the burden associated with these disorders. With increasing early and preventive intervention efforts among cohorts such as those with a familial risk for bipolar disorder, there is a need to examine the associated ethical concerns. The aim of this review was to examine the ethical issues underpinning the clinical research on pre-onset identification and preventive interventio...
Published on Oct 1, 2016in American Journal of Psychiatry13.65
Tyrone D. Cannon87
Estimated H-index: 87
(Yale University),
Changhong Yu1
Estimated H-index: 1
(Yale University)
+ 13 AuthorsThomas H. McGlashan99
Estimated H-index: 99
(Yale University)
Objective:Approximately 20%–35% of individuals 12–35 years old who meet criteria for a prodromal risk syndrome convert to psychosis within 2 years. However, this estimate ignores the fact that clinical high-risk cases vary considerably in risk. The authors sought to create a risk calculator, based on profiles of risk indicators, that can ascertain the probability of conversion to psychosis in individual patients.Method:The study subjects were 596 clinical high-risk participants from the second p...
Published on Oct 1, 2016in American Journal of Psychiatry13.65
Ricardo E. Carrión2
Estimated H-index: 2
(UM: University of Michigan),
Barbara A. Cornblatt40
Estimated H-index: 40
(UM: University of Michigan)
+ 9 AuthorsTamara Sale5
Estimated H-index: 5
(UM: University of Michigan)
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...
Anna Van Meter8
Estimated H-index: 8
(Yeshiva University),
Coty Burke2
Estimated H-index: 2
(UNC: University of North Carolina at Chapel Hill)
+ 2 AuthorsChristoph U. Correll59
Estimated H-index: 59
(Hofstra University)
Objective The aim of this study was to meta-analyze the prevalence of symptoms before an initial mood episode of bipolar disorder (BD) and the prevalence of subthreshold symptoms before a BD mood episode recurrence, to facilitate early identification and prevention. Method Systematic literature reviews were conducted in PsycINFO and PubMed for prospective or retrospective studies reporting on the prevalence and longest duration of symptoms before an initial or recurrent mood episode of BD. Rando...
Published on Jul 1, 2016in American Journal of Psychiatry13.65
Danella Hafeman16
Estimated H-index: 16
,
John Merranko7
Estimated H-index: 7
+ 10 AuthorsSatish Iyengar50
Estimated H-index: 50
Objective:The authors sought to assess dimensional symptomatic predictors of new-onset bipolar spectrum disorders in youths at familial risk of bipolar disorder (“at-risk” youths).Method:Offspring 6–18 years old of parents with bipolar I or II disorder (N=359) and community comparison offspring (N=220) were recruited. At baseline, 8.4% of the offspring of bipolar parents had a bipolar spectrum disorder. Over 8 years, 14.7% of offspring for whom follow-up data were available (44/299) developed a ...
Cited By2
Newest
Published on Jun 1, 2019in Journal of Affective Disorders4.08
Tania Perich9
Estimated H-index: 9
(UNSW: University of New South Wales),
P Mitchell79
Estimated H-index: 79
(UNSW: University of New South Wales)
Abstract Objectives Several studies have recently been conducted that have explored the benefits of psychological interventions in reducing symptomatology or improving outcomes in young people at-risk of developing bipolar disorder. The aim of this review was to explore if such interventions reduce current psychiatric symptoms and prevent the development of new symptoms. Methods A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA...
Published on Feb 1, 2019in Child and Adolescent Mental Health1.44
Argyris Stringaris31
Estimated H-index: 31
(NIH: National Institutes of Health)