Clinical features associated with poor pharmacologic adherence in bipolar disorder: results from the STEP-BD study

• Published in: The journal of clinical psychiatry Vol. 71; no. 3; p. 296
• Main Authors: Perlis, Roy H, Ostacher, Michael J, Miklowitz, David J, Hay, Aleena, Nierenberg, Andrew A, Thase, Michael E, Sachs, Gary S
• Format: Journal Article
• Language: English
• Published: United States 01.03.2010
• Subjects: Adolescent; Adult; Age of Onset; Alcoholism - epidemiology; Antimanic Agents - therapeutic use; Assessment of Medication Adherence; Bipolar Disorder - diagnosis; Bipolar Disorder - drug therapy; Bipolar Disorder - epidemiology; Comorbidity; Diagnostic and Statistical Manual of Mental Disorders; Female; Humans; Logistic Models; Longitudinal Studies; Male; Prospective Studies; Psychiatric Status Rating Scales; Psychotropic Drugs - therapeutic use; Risk Factors; Self Concept; Severity of Illness Index; Suicide, Attempted - statistics & numerical data; Surveys and Questionnaires; Treatment Outcome
• ISSN: 1555-2101
• DOI: 10.4088/JCP.09m05514yel

Poor medication adherence is common among bipolar patients. We examined prospective data from 2 cohorts of individuals from the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study (1999-2005) with bipolar disorder. Clinical and sociodemographic features associated with missing at least 25% of doses of at least 1 medication were assessed using logistic regression, and a risk stratification model was developed and validated. Of 3,640 subjects with 48,287 follow-up visits, 871 (24%) reported nonadherence on 20% or more study visits. Clinical features significantly associated (P < .05) with poor adherence included rapid cycling, suicide attempts, earlier onset of illness, and current anxiety or alcohol use disorder. Nonadherence during the first 3 months of follow-up was associated with less improvement in functioning at 12-month follow-up (P < .03). A risk stratification model using clinical predictors accurately classified 80.6% of visits in an independent validation cohort. Risk for poor medication adherence can be estimated and may be useful in targeting interventions.