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

针灸试验者的合作：慢性疼痛试验的荟萃分析

• 批准号: 7587465
• 负责人: Andrew J Vickers
• 金额: $ 18.7万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7587465
• 关键词: Accounting; Acupuncture procedure; Address; Applications Grants; Back Pain; Caring; Characteristics; Classification; Clinical; Clinical Management; Clinical Research; Clinical Trials; Clinical assessments; Collaborations; Communities; Data; Data Analyses; Data Set; Databases; Degenerative polyarthritis; Effectiveness; Ensure; Headache; Individual; Intervention; Meta-Analysis; Methods; Musculoskeletal; Neck Pain; Outcome; Pain; Pain Research; Patients; Pharmaceutical Preparations; Publications; Published Database; Publishing; Randomized; Randomized Controlled Clinical Trials; Research; Research Design; Research Personnel; Sample Size; Shoulder Pain; Specific qualifier value; Tension Headache; Waiting Lists; chronic back pain; chronic pain; design; flexibility; interest; prevent; public health relevance; research clinical testing; standard care; treatment as usual; web site

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.

描述（由申请人提供）：针灸通常是用于治疗慢性疼痛的，但其价值仍然有争议。许多高质量的荟萃分析已发表，综合针灸的随机试验，用于背痛，头痛和骨关节炎。但是，这些通常是不确定的结论，这很大程度上是由于包括的试验的规模和质量可疑：典型试验每组约有30名患者，并且没有指定一种分配隐藏方法。最近，通过完成了几项大型高质量试验，针灸临床研究的景观最近发生了巨大变化。例如，当前提案的PI已与401名患者发表了一项随机试验。 GERAC组已完成三项试验，每人接近1000名患者，四项ARC试验总共将接近10,000名患者随机分配。所有这些试验均具有高度的方法论质量。因此，这些针灸最近的大型试验纳入荟萃分析是针灸研究的高度优先级。我们建议从针灸随机试验中获得慢性疼痛的单个患者水平数据。这些数据将合并以创建单个患者级别的数据集。该数据集将进行分析以解决各种目标。我们的主要利益之一是针灸的有效性。我们将分别分析每种类型的慢性疼痛状况的数据，以确定针灸是否比假针刺更有效，以及它是否优于通常的护理控制。我们的数据集还将使我们能够回答各种其他问题，包括：不同类型的假控制是否有所不同？针灸的哪些特征，例如治疗方式或治疗课程，与良好的临床结局有关？针灸的作用因疼痛类型而有所不同吗？我们的结果对慢性疼痛的临床管理和针灸研究设计都有重要意义。在发布了这些分析的主要结果后，将在开放访问网站上发布一个取消识别的原始数据集，以使针灸研究社区的整个受益。赠款提案的形式是合作的形式 - 针灸审判员的合作 - PI的主要针灸临床试验，所有这些人都正式同意参加。 公共卫生相关性：针灸的临床价值的评估和针灸研究的研究设计都取决于仔细综合先前的研究数据。我们计划将针灸的所有大型，高质量的随机试验的原始数据结合在一起，以使单个数据集中，以实现单个患者数据元分析。这些研究大多数最近发表了，尚未纳入已发表的荟萃分析中。