VOLUME 64   2003   SUPPLEMENT 2

ARTICLES

3 Effectiveness of Antidepressants: Comparative Remission Rates. Michael E. Thase
[Abstract] [PDF]

8 Using Treatment Algorithms to Bring Patients to Remission. Madhukar H. Trivedi
[Abstract] [PDF]

14 The Use of Antidepressants in Novel Combination Therapies. Richard C. Shelton
[Abstract] [PDF]

19 The Role of Algorithms in the Detection and Treatment of Depression in Primary Care. Michael S. Klinkman
[Abstract] [PDF]

24 Treating Generalized Anxiety Disorder. Jack M. Gorman
[Abstract] [PDF]

30 Use of Algorithms to Treat Anxiety in Primary Care. Larry Culpepper
[Abstract] [PDF]

CME SECTION

34 Instructions and Posttest.
[PDF]

36 Registration Form and Evaluation.
[PDF]

Editor’s Choice

Depression remains an important and undertreated chronic illness. Current data suggest that depression in primary care is a heterogeneous entity of mild-to-moderate severity (when compared with illness encountered in psychiatric settings), but even in its mildest forms represents a major source of impairment and disability—apart from its deleterious effects on comorbid somatic illness like coronary artery disease, stroke, and diabetes.

Primary care clinicians tend to miss the diagnosis of depression when patients present with predominately somatic symptoms (vs. emotional symptoms that can be readily tied to a psychosocial stressor) and when symptoms are mild, often preferring watchful waiting to intervention with medication. When they do opt for antidepressants, treatment dosages and duration tend to be suboptimal and patient adherence can be poor. In any clinical setting, treatment outcomes will improve when an organized and evidence-based approach is used. Some favor the use of algorithms to help limit both pseudoresponses and true nonresponses or partial responses that leave patients open to continuing impairment from subsyndromal symptoms and quick relapses when treatment is discontinued.

The Primary Care Companion is pleased to offer our readers a summary of the current state of the art in treatment algorithms for major depression and generalized anxiety disorder. This series of articles begins with Dr. Michael E. Thase comparing the remission rates of various antidepressants, utilizing data from recent meta-analyses of randomized controlled trials. Dr. Madhukar H. Trivedi reviews treatment algorithms for depression and discusses rationale and state of the art. Dr. Richard C. Shelton has written an excellent review of antidepressant combination and augmentation strategies that can be very effective in converting partial responders or nonresponders to remitters. Dr. Michael S. Klinkman, a family physician, broadly discusses depression in primary care and the potential that algorithm use could have in our setting. The series concludes with a discussion of a closely related disorder—generalized anxiety disorder—and Drs. Jack M. Gorman and Larry Culpepper review the importance of treatment remission and the use of algorithms.

We hope this supplement is informative and of ready clinical use. Enjoy.

J. Sloan Manning

Editor in Chief

The Primary Care Companion to the Journal of Clinical Psychiatry