Loading…

The Acupuncture Trialists’ Collaboration: individual patient data meta-analysis of chronic pain trials

The Acupuncture Trialists’ Collaboration was established to synthesize data from high quality randomized trials on acupuncture for chronic pain. Trialists joining the collaboration provide raw data from their trial. Each data set is converted into a standardized format and then combined into a singl...

Full description

Saved in:
Bibliographic Details
Published in:Acupuncture in medicine : journal of the British Medical Acupuncture Society 2009-09, Vol.27 (3), p.126-127
Main Authors: Vickers, Andrew J, Maschino, Alexandra C
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The Acupuncture Trialists’ Collaboration was established to synthesize data from high quality randomized trials on acupuncture for chronic pain. Trialists joining the collaboration provide raw data from their trial. Each data set is converted into a standardized format and then combined into a single data set for meta-analysis. The primary question addressed by the collaboration is the effect size of acupuncture in comparison to both sham acupuncture and to usual care control. A number of secondary analyses will be conducted, including evaluating variations in the effects of acupuncture by indication, acupuncture characteristics, and types of sham, as well as an assessment of the time course of acupuncture effects. Analyses will also be conducted to see if the type of acupuncture used, traditional Chinese or Western, affects outcome. At the time of writing, members of the Acupuncture Trialists’ Collaboration have conducted a total of 25 chronic pain trials including over 18,000 patients. We hope that our approach can serve as a model for future studies in acupuncture and other complementary therapies: we strongly believe that it is only by breaking down the oppositional culture of competing trialists, and sharing data in a robust scientific collaboration, that we can best translate clinical trial findings into patient benefit.
ISSN:0964-5284
1759-9873
DOI:10.1136/aim.2009.001313