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Acupuncture for chronic pain: individual patient data meta-analysis.

ABSTRACT: Although acupuncture is widely used for chronic pain, there remains considerable controversy as to its value. We aimed to determine the effect size of acupuncture for 4 chronic pain conditions: back and neck pain, osteoarthritis, chronic headache, and shoulder pain.We conducted a systematic review to identify randomized controlled trials (RCTs) of acupuncture for chronic pain in which allocation concealment was determined unambiguously to be adequate. Individual patient data meta-analyses were conducted using data from 29 of 31 eligible RCTs, with a total of 17 922 patients analyzed.In the primary analysis, including all eligible RCTs, acupuncture was superior to both sham and no-acupuncture control for each pain condition (P < .001 for all comparisons). After exclusion of an outlying set of RCTs that strongly favored acupuncture, the effect sizes were similar across pain conditions. Patients receiving acupuncture had less pain, with scores that were 0.23 (95% CI, 0.13-0.33), 0.16 (95% CI, 0.07-0.25), and 0.15 (95% CI, 0.07-0.24) SDs lower than sham controls for back and neck pain, osteoarthritis, and chronic headache, respectively; the effect sizes in comparison to no-acupuncture controls were 0.55 (95% CI, 0.51-0.58), 0.57 (95% CI, 0.50-0.64), and 0.42 (95% CI, 0.37-0.46) SDs. These results were robust to a variety of sensitivity analyses, including those related to publication bias.Acupuncture is effective for the treatment of chronic pain and is therefore a reasonable referral option. Significant differences between true and sham acupuncture indicate that acupuncture is more than a placebo. However, these differences are relatively modest, suggesting that factors in addition to the specific effects of needling are important contributors to the therapeutic effects of acupuncture.

SUBMITTER: Vickers AJ

PROVIDER: S-EPMC3658605 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Acupuncture for chronic pain: individual patient data meta-analysis.

Vickers Andrew J AJ Cronin Angel M AM Maschino Alexandra C AC Lewith George G MacPherson Hugh H Foster Nadine E NE Sherman Karen J KJ Witt Claudia M CM Linde Klaus K

Archives of internal medicine 20121001 19

<h4>Background</h4>Although acupuncture is widely used for chronic pain, there remains considerable controversy as to its value. We aimed to determine the effect size of acupuncture for 4 chronic pain conditions: back and neck pain, osteoarthritis, chronic headache, and shoulder pain.<h4>Methods</h4>We conducted a systematic review to identify randomized controlled trials (RCTs) of acupuncture for chronic pain in which allocation concealment was determined unambiguously to be adequate. Individua ...[more]

PMID: 22965186

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Project description:Despite wide use in clinical practice, acupuncture remains a controversial treatment for chronic pain. Our objective was to update an individual patient data meta-analysis to determine the effect size of acupuncture for 4 chronic pain conditions. We searched MEDLINE and the Cochrane Central Registry of Controlled Trials randomized trials published up until December 31, 2015. We included randomized trials of acupuncture needling versus either sham acupuncture or no acupuncture control for nonspecific musculoskeletal pain, osteoarthritis, chronic headache, or shoulder pain. Trials were only included if allocation concealment was unambiguously determined to be adequate. Raw data were obtained from study authors and entered into an individual patient data meta-analysis. The main outcome measures were pain and function. An additional 13 trials were identified, with data received for a total of 20,827 patients from 39 trials. Acupuncture was superior to sham as well as no acupuncture control for each pain condition (all P < .001) with differences between groups close to .5 SDs compared with no acupuncture control and close to .2 SDs compared with sham. We also found clear evidence that the effects of acupuncture persist over time with only a small decrease, approximately 15%, in treatment effect at 1 year. In secondary analyses, we found no obvious association between trial outcome and characteristics of acupuncture treatment, but effect sizes of acupuncture were associated with the type of control group, with smaller effects sizes for sham controlled trials that used a penetrating needle for sham, and for trials that had high intensity of intervention in the control arm. We conclude that acupuncture is effective for the treatment of chronic pain, with treatment effects persisting over time. Although factors in addition to the specific effects of needling at correct acupuncture point locations are important contributors to the treatment effect, decreases in pain after acupuncture cannot be explained solely in terms of placebo effects. Variations in the effect size of acupuncture in different trials are driven predominantly by differences in treatments received by the control group rather than by differences in the characteristics of acupuncture treatment.PerspectiveAcupuncture is effective for the treatment of chronic musculoskeletal, headache, and osteoarthritis pain. Treatment effects of acupuncture persist over time and cannot be explained solely in terms of placebo effects. Referral for a course of acupuncture treatment is a reasonable option for a patient with chronic pain.

Project description:BackgroundThe purpose of clinical trials of acupuncture is to help clinicians and patients make decisions about treatment. Yet this is not straightforward: some trials report acupuncture to be superior to sham (placebo) acupuncture while others show evidence that acupuncture is superior to usual care but not sham, and still others conclude that acupuncture is no better than usual care. Meta-analyses of these trials tend to come to somewhat indeterminate conclusions. This appears to be because, until recently, acupuncture research was dominated by small trials of questionable quality. The Acupuncture Trialists' Collaboration, a group of trialists, statisticians and other researchers, was established to synthesize patient-level data from several recently published large, high-quality trials.MethodsThere are three distinct phases to the Acupuncture Trialists Collaboration: a systematic review to identify eligible studies; collation and harmonization of raw data; statistical analysis. To be eligible, trials must have unambiguous allocation concealment. Eligible pain conditions are osteoarthritis; chronic headache (tension or migraine headache); shoulder pain; and non-specific back or neck pain. Once received, patient-level data will undergo quality checks and the results of prior publications will be replicated. The primary analysis will be to determine the effect size of acupuncture. Each trial will be evaluated by analysis of covariance with the principal endpoint as the dependent variable and, as covariates, the baseline score for the principal endpoint and the variables used to stratify randomization. The effect size for acupuncture from each trial--that is, the coefficient and standard error from the analysis of covariance--will then be entered into a meta-analysis. We will compute effect sizes separately for comparisons of acupuncture with sham acupuncture, and acupuncture with no acupuncture control for each pain condition. Other analyses will investigate the impact of different sham techniques, styles of acupuncture or frequency and duration of treatment sessions.DiscussionIndividual patient data meta-analysis of high-quality trials will provide the most reliable basis for treatment decisions about acupuncture. Above all, however, we hope that our approach can serve as a model for future studies in acupuncture and other complementary therapies.

Project description:BackgroundRecent evidence shows that acupuncture is effective for chronic pain. However we do not know whether there are characteristics of acupuncture or acupuncturists that are associated with better or worse outcomes.MethodsAn existing dataset, developed by the Acupuncture Trialists' Collaboration, included 29 trials of acupuncture for chronic pain with individual data involving 17,922 patients. The available data on characteristics of acupuncture included style of acupuncture, point prescription, location of needles, use of electrical stimulation and moxibustion, number, frequency and duration of sessions, number of needles used and acupuncturist experience. We used random-effects meta-regression to test the effect of each characteristic on the main effect estimate of pain. Where sufficient patient-level data were available, we conducted patient-level analyses.ResultsWhen comparing acupuncture to sham controls, there was little evidence that the effects of acupuncture on pain were modified by any of the acupuncture characteristics evaluated, including style of acupuncture, the number or placement of needles, the number, frequency or duration of sessions, patient-practitioner interactions and the experience of the acupuncturist. When comparing acupuncture to non-acupuncture controls, there was little evidence that these characteristics modified the effect of acupuncture, except better pain outcomes were observed when more needles were used (p=0.010) and, from patient level analysis involving a sub-set of five trials, when a higher number of acupuncture treatment sessions were provided (p<0.001).ConclusionThere was little evidence that different characteristics of acupuncture or acupuncturists modified the effect of treatment on pain outcomes. Increased number of needles and more sessions appear to be associated with better outcomes when comparing acupuncture to non-acupuncture controls, suggesting that dose is important. Potential confounders include differences in control group and sample size between trials. Trials to evaluate potentially small differences in outcome associated with different acupuncture characteristics are likely to require large sample sizes.

Dataset Information

Acupuncture for chronic pain: individual patient data meta-analysis.

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Acupuncture for chronic pain: individual patient data meta-analysis.

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