The symptom cluster-based approach to individualize patient-centered treatment for major depression.

Abstract

Unipolar major depressive disorder is a common, disabling, and costly disease that is the leading cause of ill health, early death, and suicide in the United States. Primary care doctors, in particular family physicians, are the first responders in this silent epidemic. Although more than a dozen different antidepressants in 7 distinct classes are widely used to treat depression in primary care, there is no evidence that one drug is superior to another. Comparative effectiveness studies have produced mixed results, and no specialty organization has published recommendations on how to choose antidepressants in a rational, evidence-based manner. In this article we present the theory and evidence for an individualized, patient-centered treatment model for major depression designed around a targeted symptom cluster-based approach to antidepressant selection. When using this model for healthy adults with major depressive disorder, the choice of antidepressants should be guided by the presence of 1 of 4 common symptom clusters: anxiety, fatigue, insomnia, and pain. This model was built to foster future research, provide a logical framework for teaching residents how to select antidepressants, and equip primary care doctors with a structured treatment strategy to deliver optimal patient-centered care in the management of a debilitating disease: major depressive disorder.

DOI: 10.3122/jabfm.2014.01.130145
020406020162017
Citations per Year

Citation Velocity: 10

Averaging 10 citations per year over the last 2 years.

Learn more about how we calculate this metric in our FAQ.

Cite this paper

@article{Lin2014TheSC, title={The symptom cluster-based approach to individualize patient-centered treatment for major depression.}, author={Steven Y. Lin and Michael B. Stevens}, journal={Journal of the American Board of Family Medicine : JABFM}, year={2014}, volume={27 1}, pages={151-9} }