Meta-analysis of CAM therapies for HIV

描述（由申请人提供）：HIV感染的常规疗法已经取得了很大进展，但它们仍然复杂、昂贵并且有许多副作用。 HIV 感染患者正在使用许多补充和替代医学 (CAM) 疗法，但其中哪些疗法（如果有的话）实际上是有益的尚不清楚，而且它们的使用是否具有经济意义也更不清楚。确定适当治疗的最佳方法是随机对照试验（RCT）。然而，由于多种原因，在护理提供者需要做出决定时可能无法获得明确的结果。美国国家医学图书馆在 PubMed 中索引的有关艾滋病毒 CAM 疗法的医学文献正在呈指数级增长，但随机对照试验的数量虽然增长迅速，但与其他类型的研究相比仍然相对较少。此外，互联网和其他地方存在大量且快速增长的各种非标准和不太严格的信息源，它们可能提供有用的信息，但难以访问，甚至更难以评估。有许多技术，包括荟萃分析（通常称为系统评价）、决策分析和成本效益分析，这些技术使用现有或可估计的信息，试图为必须制定卫生政策和治疗决策的人提供临时答案。最近，由于计算能力的提高和基于模拟的方法（例如马尔可夫链蒙特卡罗（MCMC）方法）的发展，贝叶斯统计技术得到了快速发展和越来越多的使用。贝叶斯方法的主要优点是它允许在单个连贯模型中综合所有可用的证据来源（即随机对照试验、观察性研究、专家判断）。本研究的目标是利用这些技术缩短首次报告艾滋病毒新 CAM 治疗方式后的滞后期，直到临床医生可以做出以下四个决定之一： 1. 永远不应该或很少使用它。 2. 只能在某些明确可识别的情况或患者中使用。 3、可常规使用。 4.以上三者不能选其一，需进一步临床研究。 我们将主要侧重于澄清 CAM 疗法作为辅助疗法的使用，这些辅助疗法可能会推迟开始使用更昂贵的疗法（例如抗逆转录病毒药物）或与更昂贵的疗法（例如抗逆转录病毒药物）协同作用，用于症状管理，以及治疗与 HIV 相关的机会性感染和合并症，例如使用维生素 D、益生菌、水飞蓟、减压等（随着数据的出现）。

DESCRIPTION (provided by applicant): Conventional therapies for HIV infection have made great progress, but they remain complex, expensive and have many side effects. Many Complementary and Alternative Medicine (CAM) therapies are being used by patients with HIV infection, but which of them (if any) are in fact beneficial is still unclear, and whether their use makes economic sense is even less clear. The optimal method of determining appropriate treatments is the randomized control trial (RCT). However, for many reasons, definitive results may not be available at the time care providers need to make decisions. The medical literature dealing with CAM therapies for HIV, as indexed by the National Library of Medicine in PubMed, is growing exponentially, but the number of RCTs, while growing rapidly, still remains relatively small compared to other types of studies. In addition, there is a large and rapidly growing variety of non-standard and less rigorous information sources, on the Internet and elsewhere, which may provide useful information, but are difficult to access and even more difficult to evaluate. There are a number of techniques including meta-analysis (often called systematic review), decision analysis and cost-effectiveness analysis, which use information which is already available, or which can be estimated, to attempt to provide interim answers for those who must make health policy and treatment decisions. Recently, there has been rapid development and increasing use of Bayesian statistical techniques, facilitated by the increase in computing power and the development of simulation based approaches such as Markov chain Monte Carlo (MCMC) methods. The main advantage of a Bayesian approach is that it allows the synthesis of all the available sources of evidence (i.e., RCTs, observational studies, expert judgment) within a single coherent model. The goal of this research is to use these techniques to shorten the lag period after the first report of a new CAM treatment modality for HIV to the time when clinicians can make one of the following four decisions: 1. It should never or rarely be employed. 2. It should be employed only in certain clearly identifiable circumstances or patients. 3. It can be routinely employed. 4. The choice of one of the above three cannot be made and further clinical research is indicated. We will focus primarily on clarifying the use of CAM therapies as adjuncts that may delay the need to start, or synergize with, more expensive therapies such as antiretrovirals, be used for symptom management, and in treatment of the opportunistic infections and comorbidities associated with HIV, e.g., use of Vitamin D, probiotics, milk thistle, stress reduction, and others as data emerge.