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

描述(申请人提供)：针灸通常被认为是治疗慢性疼痛的方法，但其价值仍然存在争议。许多高质量的荟萃分析已经发表，这些分析综合了针灸治疗背痛、头痛和骨性关节炎的随机试验。然而，这些通常会得出相当不确定的结论，很大程度上是因为纳入试验的规模和质量有问题：一个典型的试验每组大约有30名患者，并且没有具体说明分配隐藏的方法。最近，几项大型高质量试验的完成，极大地改变了针灸临床研究的格局。例如，当前提案的PI公布了一项有401名患者参加的随机试验；GERAC组完成了三项试验，每项试验有近1000名患者；四项ARC试验总共随机安排了近10,000名患者。所有这些试验都具有很高的方法学质量。因此，将最近的这些大型针灸试验纳入荟萃分析是针灸研究的高度优先事项。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。这些数据将被组合起来，以创建单个患者级别的数据集。将对该数据集进行分析，以实现各种目标。我们的主要兴趣之一是针灸的有效性。我们将分别对每种慢性疼痛情况的数据进行分析，以确定针灸是否比假针灸更有效，以及是否优于常规护理对照。我们的数据集还将允许我们回答各种其他问题，包括：不同类型的虚假控制是否有所不同？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？针灸的效果因疼痛类型而不同吗？我们的结果对慢性疼痛的临床治疗和针灸研究设计都有重要的意义。在这些分析的主要结果公布后，一个未确认的原始数据集将被公布在一个开放获取网站上，以造福于整个针灸研究社区。拨款提案的形式是主要针灸临床试验的PI之间的合作--针灸试验者合作，他们都已正式同意参与。 公共卫生相关性：无论是针灸临床价值的评估，还是针灸研究的研究设计，都严重依赖于对先前研究数据的仔细综合。我们计划将所有大型、高质量的针灸治疗慢性疼痛随机试验的原始数据合并为一个数据集，以实现单个患者数据的荟萃分析。这些研究大多是最近发表的，还没有被纳入已发表的荟萃分析中。

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.