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Identification of primary care patients at risk of nonadherence to antidepressant treatment

Authors Akerblad A, Bengtsson F, Holgersson, von Knorring L, Ekselius L

Published 8 January 2009 Volume 2008:2 Pages 379—386

DOI https://doi.org/10.2147/PPA.S3511

Review by Single-blind

Peer reviewer comments 3

Ann-Charlotte Åkerblad1, Finn Bengtsson2, Margareta Holgersson3, Lars von Knorring1, Lisa Ekselius1

1Department of Neuroscience, Psychiatry, Uppsala University Hospital, Uppsala University, Uppsala, Sweden; 2Division of Clinical Pharmacology, Medicine and Care, Faculty of Health Sciences, Linköping University, Linköping, Sweden; 3Quintiles AB, Uppsala, Sweden

Introduction: Poor adherence to antidepressant treatment is common, and results in increased disability and costs. Several factors are thought to influence patients’ ability and willingness to adhere. So far, however, consensus is lacking regarding patient characteristics that predict nonadherence. The purpose of this study was to identify predictors of nonadherence to antidepressant treatment that can be ascertained at treatment start.

Method: The present study used data from a randomized controlled trial with the main objective of studying the effect of two different compliance-enhancing programs on treatment adherence and treatment response in 1031 primary care patients with major depression. In this study, logistic regression analyses were performed to examine patient- and illness-related characteristics potentially associated with nonadherence.

Results: Nonadherence to antidepressant treatment was predicted by age under 35 or over 64 years, presence of personality disorder, sensation-seeking personality traits, substance abuse, and absence of concomitant medications.

Conclusion: Certain patient- and illness-related characteristics may imply an increased risk of nonadherence to antidepressant treatment. Giving special attention to subjects with such characteristics may improve adherence.

Keywords: unipolar depression, antidepressant, adherence, compliance, SSRI, predictors

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