Acupuncture is often considered for the treatment of chronic pain, but its value remains controversial. The Acupuncture Trialists'Collaboration was established in 2006 to provide best evidence on the effects of acupuncture on chronic pain. The collaboration obtains individual patient level data from high quality randomized trials of acupuncture for chronic pain, standardizes the data in order to combine it in a single data set, and then conducts analyses t to address questions concerning both acupuncture effectiveness and acupuncture study design. NCCAM awarded the collaboration R21 funding in support of its work in 2008. The Acupuncture Trialists'Collaboration now consists of an international group of 31 physicians, clinical trialists, biostatisticians, practicing acupuncturists and other specialists including many of the most widely recognized names in acupuncture research. It has been extremely successful in obtaining raw data from trialists in the pain conditions under its remit: osteoarthritis, non- specific back and neck pain, chronic headache, and shoulder pain. Of the 31 trials that met the stringent eligibility criteria for inclusion in the collaboration data set, usable individual patient data have been obtained from 29 trials. Data from all 29 trials have been checked, relabeled and added to the collaboration database, which now includes nearly 18,000 randomized patients. The initial analyses of these data are complete. In particular, we found strong evidence that acupuncture is superior both to no acupuncture control and to sham acupuncture for each of the pain conditions included. We also found evidence that the effect size of acupuncture depended on the comparator, for example, there were smaller differences between true acupuncture and sham techniques involving needle penetration, than between true acupuncture and a non-penetrating sham device. The Acupuncture Trialists'Collaboration therefore has a proven track record of bringing high-impact acupuncture research to fruition. Here we propose to update our database of trials, and analyses thereof, with an additional 5 years of data. Continuation funding for the collaboration will also allow us to extend our analyses to comparisons of acupuncture with drug therapy and to address four additional questions pertaining to acupuncture: predictors of acupuncture benefit;the time course of acupuncture effects;whether there are acupuncture 'responders'that have exceptional improvements after acupuncture therapy;whether outcomes vary between practitioners.
Both the assessment of the clinical value of acupuncture, and research design of acupuncture studies, depend critically on the careful synthesis of prior research data. We plan to combine raw data from all large, high-quality randomized trials of acupuncture for chronic pain into a single data set to enable individual patient data meta- analysis. This will allow us to address questions both about the effectiveness of acupuncture and factors, such as the number of treatments given, that impact its effectiveness.
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|MacPherson, Hugh; Vertosick, Emily; Lewith, George et al. (2014) Influence of control group on effect size in trials of acupuncture for chronic pain: a secondary analysis of an individual patient data meta-analysis. PLoS One 9:e93739|
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|Vickers, Andrew J; Maschino, Alexandra C; Lewith, George et al. (2013) Responses to the Acupuncture Trialists' Collaboration individual patient data meta-analysis. Acupunct Med 31:98-100|
|Vickers, Andrew J; Acupuncture Trialists' Collaboration (2013) In reply. JAMA Intern Med 173:714|
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