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STAR*D: helping to close the gap between science and practice.

David L Shern¹, Hazel Moran

¹Mental Health America, Alexandria, VA 22311, USA. dshern@mentalhealth america.net

Psychiatric Services (Washington, D.C.)

|November 3, 2009

Summary

The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial showed a 70% remission rate in real-world depression treatment. Many patients needed medication changes, highlighting the need for accessible, varied treatment options.

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Area of Science:

Clinical Psychology
Psychiatric Research
Public Health Policy

Background:

Traditional randomized controlled trials (RCTs) have limitations in reflecting real-world clinical practice.
The STAR*D (Sequenced Treatment Alternatives to Relieve Depression) trial was designed as a practical clinical trial to address these limitations.

Purpose of the Study:

To evaluate the effectiveness of a stepped-care approach in treating major depression in a real-world setting.
To assess remission rates and identify factors associated with treatment success or failure.

Main Methods:

The STAR*D trial enrolled a large, diverse patient population with major depressive disorder.
Participants received sequential treatment with different antidepressant medications, including augmentation and switching strategies.
Remission was defined as a score below a certain threshold on a depression rating scale.

Main Results:

The STAR*D trial achieved a 70% remission rate among participants.
Achieving remission often required medication switching or augmentation, indicating the need for flexible treatment strategies.
A significant portion of participants (30%) did not achieve remission, and high attrition rates were observed.

Conclusions:

Practical clinical trials like STAR*D are valuable for understanding depression treatment in real-world conditions.
Accessible and diverse treatment options, including medication adjustments, are crucial for improving depression remission rates.
Future research should prioritize patient involvement in trial design and interpretation, and address high attrition rates.