Cumulative morbidity and prognostic staging of illness in the systematic treatment enhancement program for Bipolar Disorder (STEP-BD)

Objective: Staging models may provide heuristic utility for intervention selection in psychiatry. Although a few proposals have been put forth, there is a need for empirical validation if they are to be adopted. Using data from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD), we tested a previously elaborated hypothesis on the utility of using the number of previous episodes as a relevant prognostic variable for staging in bipolar disorder.

Methods: This report utilizes data from the multisite, prospective, open-label study ‘Standard Care Pathways’ and the subset of patients with acute depressive episodes who participated in the randomized trial of adjunctive antidepressant treatment. Outpatients meeting DSM-IV diagnostic criteria for bipolar disorder (n = 3345) were included. For the randomized pathway, patients met criteria for an acute depressive episode (n = 376). The number of previous episodes was categorized as less than 5, 5–10 and more than 10. We used disability at baseline, number of days well in the first year and longitudinal scores of depressive and manic symptoms, quality of life and functioning as validators of models constructed a priori.

Results: Patients with multiple previous episodes had consistently poorer cross-sectional and prospective outcomes. Functioning and quality of life were worse, disability more common, and symptoms more chronic and severe. There was no significant effect for staging with regard to antidepressant response in the randomized trial.

Conclusions: These findings confirm that bipolar disorder can be staged with prognostic validity. Stages can be used to stratify subjects in clinical trials and develop specific treatments.

Age at onset, course of illness and response to psychotherapy in bipolar disorder: Results from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD)

Background. The course of bipolar disorder progressively worsens in some patients. Although responses to pharmacotherapy appear to diminish with greater chronicity, less is known about whether patients' prior courses of illness are related to responses to psychotherapy.

Affective instability and the course of bipolar depression: results from the STEP-BD randomised controlled trial of psychosocial treatment

BACKGROUND: Little is known about predictors of recovery from bipolar depression. AIMS: We investigated affective instability (a pattern of frequent and large mood shifts over time) as a predictor of recovery from episodes of bipolar depression and as a moderator of response to psychosocial treatment for acute depression. METHOD: A total of 252 out-patients with DSM-IV bipolar I or II disorder and who were depressed enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) and were randomised to one of three types of intensive psychotherapy for depression (n = 141) or a brief psychoeducational intervention (n = 111). All analyses were by intention-to-treat. RESULTS: Degree of instability of symptoms of depression and mania predicted a lower likelihood of recovery and longer time until recovery, independent of the concurrent effects of symptom severity. Affective instability did not moderate the effects of psychosocial treatment on recovery from depression. CONCLUSIONS: Affective instability may be a clinically relevant characteristic that influences the course of bipolar depression.

Specific mood symptoms confer risk for subsequent suicidal ideation in bipolar disorder with and without suicide attempt history: multi-wave data from STEP-BD

BACKGROUND: Little is known about specific mood symptoms that may confer risk for suicidal ideation (SI) among patients with bipolar disorder (BD). We evaluated prospectively whether particular symptoms of depression and mania precede the onset or worsening of SI, among adults with or without a history of a suicide attempt. METHODS: We examined prospective data from a large (N = 2,741) cohort of patients participating in the Systematic Treatment Enhancement Program for BD (STEP-BD). We evaluated history of suicide attempts at baseline, and symptoms of depression and mania at baseline and follow-up visits. Hierarchical linear modeling tested whether specific mood symptoms predicted subsequent levels of SI, and whether the strength of the associations differed based on suicide attempt history, after accounting for the influence of other mood symptoms and current SI. RESULTS: Beyond overall current depression and mania symptom severity, baseline SI, and illness characteristics, several mood symptoms, including guilt, reduced self-esteem, psychomotor retardation and agitation, increases in appetite, and distractibility predicted more severe levels of subsequent SI. Problems with concentration, distraction, sleep loss and decreased need for sleep predicted subsequent SI more strongly among individuals with a suicide attempt history. CONCLUSIONS: Several specific mood symptoms may confer risk for the onset or worsening of SI among treatment-seeking patients with BD. Individuals with a previous suicide attempt may be at greater risk in part due to greater reactivity to certain mood symptoms in the form of SI. However, overall, effect sizes were small, suggesting the need to identify additional proximal predictors of SI.

A cluster analytic approach to identifying predictors and moderators of psychosocial treatment for bipolar depression: results from STEP-BD

Background We sought to address how predictors and moderators of psychotherapy for bipolar depression - identified individually in prior analyses - can inform the development of a metric for prospectively classifying treatment outcome in intensive psychotherapy (IP) versus collaborative care (CC) adjunctive to pharmacotherapy in the Systematic Treatment Enhancement Program (STEP-BD) study. Methods We conducted post-hoc analyses on 135 STEP-BD participants using cluster analysis to identify subsets of participants with similar clinical profiles and investigated this combined metric as a moderator and predictor of response to IP. We used agglomerative hierarchical cluster analyses and k-means clustering to determine the content of the clinical profiles. Logistic regression and Cox proportional hazard models were used to evaluate whether the resulting clusters predicted or moderated likelihood of recovery or time until recovery. Results The cluster analysis yielded a two-cluster solution: 1) "less-recurrent/severe" and 2) "chronic/recurrent." Rates of recovery in IP were similar for less-recurrent/severe and chronic/recurrent participants. Less-recurrent/severe patients were more likely than chronic/recurrent patients to achieve recovery in CC (p=.040, OR=4.56). IP yielded a faster recovery for chronic/recurrent participants, whereas CC led to recovery sooner in the less-recurrent/severe cluster (p=.034, OR=2.62). Limitations Cluster analyses require list-wise deletion of cases with missing data so we were unable to conduct analyses on all STEP-BD participants. Conclusions A well-powered, parametric approach can distinguish patients based on illness history and provide clinicians with symptom profiles of patients that confer differential prognosis in CC vs. IP.

Illness burden and medical comorbidity in the systematic treatment enhancement program for bipolar disorder

Objective:  Coexisting chronic medical conditions are common in bipolar disorder. Here, we report the prevalence and correlates of medical comorbidity in patients enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). We were particularly interested in associations between variables reflecting illness chronicity and burden with comorbid medical conditions.

Method:  We used intake data from the open-label component of the STEP-BD. History of medical comorbidity was obtained from the affective disorders evaluation, and its presence was the outcome of interest. The sample size in analyses varied from 3399 to 3534. We used multiple Poisson regression to obtain prevalence ratios.

Results:  The prevalence of any medical comorbidity in the sample was 58.8%. In addition to demographic variable, several clinical characteristics were associated with the frequency of medical comorbidity. Having more than 10 previous mood episodes, childhood onset, smoking, lifetime comorbidity with anxiety, and substance use disorders were independently associated with having a medical comorbidity in the final multivariate model.

Conclusion:  The results presented here reveal strong associations between variables related to illness chronicity and medical burden in bipolar disorder. This lends further support to recent multidimensional models incorporating medical morbidity as a core feature of bipolar disorder.

Staging systems in bipolar disorder: an International Society for Bipolar Disorders Task Force report

We discuss the rationale behind staging systems described specifically for bipolar disorders. Current applications, future directions and research gaps in clinical staging models for bipolar disorders are outlined.

Impact of sunlight on the age of onset of bipolar disorder

Bauer M, Glenn T, Alda M, Andreassen OA, Ardau R, Bellivier F, Berk M, Bjella TD, Bossini L, Del Zompo M, Dodd S, Fagiolini A, Frye MA, Gonzalez-Pinto A, Henry C, Kapczinski F, Kliwicki S, Konig B, Kunz M, Lafer B, Lopez-Jaramillo C, Manchia M, Marsh W, Martinez-Cengotitabengoa M, Melle I, Morken G, Munoz R, Nery FG, ODonovan C, Pfennig A, Quiroz D, Rasgon N, Reif A, Rybakowski J, Sagduyu K, Simhandl C, Torrent C, Vieta E, Zetin M, Whybrow PC. Impact of sunlight on the age of onset of bipolar disorder. Bipolar Disord 2012: 14: 654663. (c) 2012 The Authors. Journal compilation (c) 2012 John Wiley & Sons A/S. Objective: Although bipolar disorder has high heritability, the onset occurs during several decades of life, suggesting that social and environmental factors may have considerable influence on disease onset. This study examined the association between the age of onset and sunlight at the location of onset. Method: Data were obtained from 2414 patients with a diagnosis of bipolar I disorder, according to DSM-IV criteria. Data were collected at 24 sites in 13 countries spanning latitudes 6.3 to 63.4 degrees from the equator, including data from both hemispheres. The age of onset and location of onset were obtained retrospectively, from patient records and/or direct interviews. Solar insolation data, or the amount of electromagnetic energy striking the surface of the earth, were obtained from the NASA Surface Meteorology and Solar Energy (SSE) database for each location of onset. Results: The larger the maximum monthly increase in solar insolation at the location of onset, the younger the age of onset (coefficient= -4.724, 95% CI: -8.124 to -1.323, p = 0.006), controlling for each countrys median age. The maximum monthly increase in solar insolation occurred in springtime. No relationships were found between the age of onset and latitude, yearly total solar insolation, and the maximum monthly decrease in solar insolation. The largest maximum monthly increases in solar insolation occurred in diverse environments, including Norway, arid areas in California, and Chile. Conclusion: The large maximum monthly increase in sunlight in springtime may have an important influence on the onset of bipolar disorder.

Caregiver burden as a predictor of depression among family and friends who provide care for persons with bipolar disorder

OBJECTIVES: Over one-third of caregivers of people with bipolar disorder report clinically significant levels of depressive symptoms. This study examined the causal relationship between depression and caregiver burden in a large sample of caregivers of adult patients with bipolar disorder. METHODS: Participants were 500 primary caregivers of persons with bipolar disorder enrolled in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD).This study evaluates the strength and direction of the associations between caregiver burden and depressive symptoms at baseline and at six- and 12-month follow-up using cross-lagged panel analyses, controlling for the clinical status of patients and sociodemographic variables. RESULTS: Higher levels of overall caregiver burden at baseline were associated with increased levels of depressive symptoms among caregivers at follow-up (F = 8.70, df = 1,290, p < 0.001), after controlling for baseline caregiver depression, gender, race, age, social support, and patients' clinical status. By contrast, caregiver depression at baseline was not significantly associated with caregiver burden at follow-up (F = 1.65, p = 0.20). CONCLUSIONS: Caregiver burden is a stronger predictor of caregiver depressive symptoms over time than the reverse. Interventions that help alleviate caregiver burden may decrease depressive symptoms.