Acupuncture Trialists' Collaboration: meta-analysis of chronic pain trials

描述（由申请人提供）：针灸通常被认为是治疗慢性疼痛，但其价值仍然存在争议。许多高质量的荟萃分析已经发表，综合针灸治疗背痛，头痛和骨关节炎的随机试验。然而，这些通常得出相当不确定的结论，主要是因为纳入试验的规模和质量值得怀疑：一项典型的试验每组可能有30例患者，并且没有指定分配隐藏的方法。针灸临床研究的景观最近已经大大改变了几个大的，高质量的试验完成。例如，当前提案的PI已经发表了一项包含401例患者的随机试验; GERAC组已经完成了3项试验，每项试验包含近1000例患者，而4项ARC试验总共随机化了近10，000例患者。所有这些试验都具有很高的方法学质量。因此，将这些最近的大型针灸试验纳入荟萃分析是针灸研究的一个高度优先事项。我们建议从针灸治疗慢性疼痛的随机试验中获得个体患者水平的数据。这些数据将被合并以创建个体患者水平数据集。将对该数据集进行分析，以解决各种目标。我们的主要兴趣之一是针灸的有效性。我们将分析数据，分别为每种类型的慢性疼痛条件，以确定是否针灸是更有效的比假针灸，它是否是上级，以通常的护理控制。我们的数据集还将使我们能够回答各种其他问题，包括：不同类型的假对照是否有差异？针灸的哪些特征，如治疗方式或治疗次数，与良好的临床结果相关？针灸的效果是否因疼痛类型而异？我们的研究结果对慢性疼痛的临床管理和针灸的研究设计都有重要意义。在这些分析的主要结果发表后，一个去识别的原始数据集将发布在开放获取网站上，以造福整个针灸研究界。该拨款提案是以合作的形式-针灸试验者合作-在主要针灸临床试验的PI之间，所有人都正式同意参加。 公共卫生相关性：针灸临床价值的评估和针灸研究的研究设计，关键取决于对先前研究数据的仔细综合。我们计划将联合收割机的原始数据，从所有大型，高质量的随机试验针灸慢性疼痛到一个单一的数据集，使个别患者的数据Meta分析。这些研究大多是最近发表的，尚未纳入已发表的荟萃分析。

DESCRIPTION (provided by applicant): Acupuncture is often considered for the treatment of chronic pain, but its value remains controversial. Many good quality meta-analyses have been published synthesizing randomized trials of acupuncture for back pain, headache and osteoarthritis. However, these have typically come to rather indeterminate conclusions, largely because of the questionable size and quality of the included trials: a typical trial has perhaps 30 patients per group and did not specify a method of allocation concealment. The landscape of clinical research in acupuncture has recently been dramatically altered by the completion of several large, high quality trials. For example, the PI of the current proposal has published a randomized trial with 401 patients; the GERAC group has completed three trials with close to 1000 patients each, and the four ARC trials have randomized close to 10,000 patients in total. All of these trials are of high methodologic quality. The incorporation of these recent large trials of acupuncture into meta-analysis is therefore a high priority of acupuncture research. We propose obtaining individual patient level data from randomized trials of acupuncture for chronic pain. These data will be combined to create an individual patient level data set. This data set will be analyzed to address a variety of objectives. One of our main interests concerns the effectiveness of acupuncture. We will analyze the data, separately for each type of chronic pain condition, to determine whether acupuncture is more effective than sham acupuncture and whether it is superior to usual care control. Our data set will also allow us to answer a variety of other questions including: do different types of sham control differ? What characteristics of acupuncture, such as treatment style or number of treatment sessions, are associated with good clinical outcomes? Do the effects of acupuncture differ by type of pain? Our results have important implications both for the clinical management of chronic pain and for research design in acupuncture. After publication of the principal results of these analyses, a de-identified raw data set will be posted on an Open Access website for the benefit of the acupuncture research community as a whole. The grant proposal is in the form of a collaboration - the Acupuncture Trialists' Collaboration - between the PI's of major acupuncture clinical trials, all of whom have formally agreed to take part. PUBLIC HEALTH RELEVANCE: 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. Most of these studies were published recently and have not been incorporated into published meta-analyses.