Research report
Personal and familial correlates of bipolar (BP)-I disorder in children with a diagnosis of BP-I disorder with a positive child behavior checklist (CBCL)-severe dysregulation profile: A controlled study

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Abstract

Background

Although the DSM-IV provides explicit criteria for the diagnosis of BP-I disorder, this is a complex diagnosis that requires high levels of clinical expertise. Previous work shows children with a unique profile of the CBCL of high scores (2SD) on the attention problems (AP), aggressive behavior (AGG), and anxious-depressed (AD) (A–A–A) subscales are more likely than other children to meet criteria for BP-I disorder in both epidemiological and clinical samples. However, since not all BP-I disorder children have a positive profile questions remain as to its informativeness, particularly in the absence of an expert diagnostician.

Methods

Analyses were conducted comparing personal and familial correlates of BP-I disorder in 140 youth with a structured interview and an expert clinician based DSM-IV diagnosis of BP-I disorder with (N=80) and without (N=60) a positive CBCL- Severe Dysregulation profile, and 129 controls of similar age and sex without ADHD or a mood disorder. Subjects were comprehensively assessed with structured diagnostic interviews and wide range of functional measures. We defined the CBCL-severe dysregulation profile as an aggregate cut-off score of ≥210 on the A–A–A scales.

Results

BP-I probands with and without a positive CBCL-severe dysregulation profile significantly differed from Controls in patterns of psychiatric comorbidity, psychosocial and psychoeducational dysfunction, and cognitive deficits, as well as in their risk for BP-I disorder in first degree relatives.

Limitations

Because the sample was referred and largely Caucasian, findings may not generalize to community samples and other ethnic groups.

Conclusion

A positive CBCL-severe dysregulation profile identifies a severe subgroup of BP-I disorder youth.

Introduction

An emerging pediatric literature documents that pediatric bipolar disorder (BP) is a prevalent and highly morbid disorder worldwide. Merikangas et al. (2010) reported a 2.9% prevalence of bipolar disorder in a large epidemiological sample of over 10,000 adolescents in the US. A meta-analysis of international epidemiological studies estimated the prevalence of pediatric BP and bipolar spectrum disorder to be 1.8% and found no significant difference in prevalence between the United States and other countries (Van Meter et al., 2011).

Although the DSM-IV provides explicit criteria for the diagnosis of BP-I disorder, this is a complex diagnosis that requires high levels of clinical expertise not readily available in clinical practice. This state of affairs calls for easy to use, cost-effective methods to aid in the identification of such children in clinical practice, and particularly in the primary care setting.

Because of its empirical nature, its excellent psychometric properties and its ease of use as a paper and pencil instrument, the child behavior checklist (CBCL) (Achenbach, 1991) has been examined as a potential tool to aid in the identification of children at high risk for BP-I disorder (Althoff et al., 2006, Faraone et al., 2005, Hudziak et al., 2005, Mick et al., 2003). Several groups have shown that children with a unique profile of the CBCL of high scores (2SD) on the attention problems (AP), aggressive behavior (AGG), and anxious-depressed (AD) (A–A–A) subscales are more likely than other children to meet DSM-based diagnosis of BP-I disorder in both epidemiological and clinical samples (Achenbach, 1991, Carlson and Kelly, 1998, Geller et al., 1998, Hazell et al., 1999, Mick et al., 2003, Wals et al., 2001). This profile has been variedly referred to as the CBCL-pediatric bipolar disorder profile or CBCL-severe dysregulation profile (Mick et al., 2003) (henceforth referred to as CBCL-Severe Dysregulation profile).

Using conditional probability analysis, we recently documented that children with a clinical and structured interview diagnosis of BP-I disorder were significantly more likely than both control (Odds Ratio (OR): 173.2; 95% Confidence Interval (CI): 21.2, 1413.8; p<0.001) and ADHD children (OR:14.6; 95% CI: 6.2, 34.3; p<0.001) to have a positive CBCL-severe dysregulation profile (A–A–A scores of ≥210) (Positive Predictive Power: 99%; false positive rate:< 0.2%). However, this study also showed that a sizeable number of children with a documented diagnosis of BP-I disorder did not have a positive profile thereby raising questions as to the general informativeness of this profile.

One approach to shed light on this important issue would be to examine whether the subgroup of BP-I disorder children with a positive CBCL-severe dysregulation profile would have external correlates of BP-I disorder such as patterns of psychiatric comorbidity and dysfunction and familial rates of BP-I disorder in first degree relatives. We reasoned that for a positive CBCL profile to be informative in clinical practice it should be associated with meaningful correlates of BP-I disorder.

The main aim of the present work was to further investigate the informativeness of the CBCL-severe dysregulation profile to aid in the identification of children with a suspected diagnosis of BP-I disorder. To this end, we compared personal (symptom profile, psychiatric comorbidity and psychosocial dysfunction) and familial correlates (rates of familiality of BP-I disorder), in BP-I disorder children with and without a positive CBCL-severe dysregulation profile and Controls. We hypothesized the positive profile will be associated with a picture compatible with a diagnosis of BP-I disorder.

Section snippets

Subjects

Detailed study methods have been previously described (Wozniak et al., 2012). Briefly, children with BP-I disorder 6–17 years of age of both sexes were recruited and assessed at the Clinical and Research Program in Pediatric Psychopharmacology at the Massachusetts General Hospital based on the presence of a diagnosis of bipolar-I disorder in the proband youth by structured diagnostic interview and clinical assessment (Wozniak et al., 2005, Wozniak et al., 2010). Comparators were youth with and

Results

Our analyses compared BP-I probands with and without a positive CBCL-severe dysregulation profile with Control probands without ADHD or a mood disorder. As shown in Table 1, there were no meaningful differences between the groups in the age and sex distributions. However, there were small, but statistically significant differences in the socio-economic backgrounds of the families. Probands with a positive CBCL profile had a lower SES. Accordingly, all subsequent tests were adjusted for SES.

As

Discussion

Our results show that BP-I probands with and without a positive CBCL-severe dysregulation profile significantly differed from Controls in patterns of psychiatric comorbidity, psychosocial and psychoeducational dysfunction, cognitive deficits as well as in their risk for BP-I disorder in first degree relatives. These results add to the emerging evidence for the utility of CBCL-Severe Dysregulation to help identify children very likely to receive a diagnosis of pediatric BP-I disorder if they

Role of funding source

The study sponsors had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.

Conflict of interest

Dr. Joseph Biederman is currently receiving research support from the following sources: Elminda, Janssen, McNeil, and Shire. In 2012, Dr. Joseph Biederman received an honorarium from the MGH Psychiatry Academy for a tuition-funded CME course. In 2011, Dr. Joseph Biederman gave a single unpaid talk for Juste Pharmaceutical Spain, received honoraria from the MGH Psychiatry Academy for a tuition-funded CME course, and received an honorarium for presenting at an international scientific conference

Acknowledgements

This work was supported by NIH grants K08MH001503 and R01MH066237 to Dr Wozniak and R01MH050657 and R01HD036317 to Dr Biederman. This work was also supported by a grant from the Heinz C. Prechter Bipolar Research Fund, the support of members of the MGH Pediatric Psychopharmacology Council, and the Susan G. Berk Endowed Fund for Juvenile Bipolar Disorder.

References (34)

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