ivSyRMAF - the CAMARADES-NC3Rs in vivo systematic review and meta-analysis facility

动物可以用来提高我们对疾病的理解，并测试新疗法的有效性。将动物研究的结果转化为临床环境中的人类并不总是一帆风顺的。我们率先使用系统回顾和元分析--最初开发用于分析人类临床试验数据的工具--通过分析动物研究的数据来调查这种翻译失败。我们和其他人已经表明，在已发表的体内疾病建模研究报告中，它们的设计和操作往往存在缺陷，报告减少偏见风险的措施的比例很低。我们还表明，有偏倚风险的研究往往会对治疗效果做出夸大(更高)的估计。随着我们取得进展，我们方法的一个中心目标是通过与其他希望在自己的研究领域进行类似审查的人分享我们的专业知识来支持这一发展中的领域。这包括提供方法建议和支持、数据存储库以及对我们的数据管理平台的访问。然而，我们正在接近我们这样做的能力极限，这笔基础设施资金将使我们能够开发一个改进的数据库，提高分析能力和网络界面；并向那些希望进行系统审查和元分析的人提供更有组织的支持，包括用户手册、在线培训材料以及电话和面对面咨询。对活体研究的系统回顾和荟萃分析可以为改变研究实践提供证据；我们的工作已经确定了活体研究中存在偏差和发表偏差的风险，导致了卒中建模的良好实验室实践指南(2009)，并帮助推动了到达指南的制定。我们的工作是在做出资助决定之前与NINDS拨款授予小组分享的，在《自然》杂志上向NINDS/NIH透明度论文(2012年；引用了我们的工作的16篇论文)提供了信息；并因此告知了自然出版集团最近的政策变化，要求报告偏倚项目的风险，如随机化、盲法、纳入和排除标准以及样本量计算。这些问题是3R的基础，部分是因为获得正确的实验规模的关键重要性，其次是因为高偏倚风险的实验比使用相同数量的低偏倚动物的实验提供的有用信息更少；因此，确定偏见项目的风险，以及调查人员如何降低偏见风险，对3R至关重要。我们认为，虽然在过去的10年里已经取得了很大的成就，但通过在更广泛的体内模型中使用这项技术，体内研究的实用性可以得到实质性的提高。这一应用的目的是让我们成为更广泛采用的催化剂(对它的需求已经很明显)，并让那些现在进入该领域的人从我们通过经验吸收的学习和方法发展中受益。简而言之，这将包括：(I)强调实验设计的重要性，以提高动物研究的有效性和统计准确性；(Ii)确定由于观察到的差异，哪些结果衡量标准需要较少的动物；(Iii)支持减少在太小而不能可靠地检测到所寻求的影响或不必要地太大的研究中牺牲的动物的数量；(Iv)确定是否有必要进行高严重性测试或多项测试，较长的实验是否具有附加值，或者持续时间较短的实验是否同样有用；以及(V)评估我们预期结果将被用来推动报告正面、负面和中性结果的出版偏倚。

Animals can be used to improve our understanding of a disease and to test the effectiveness of novel treatments. Translating findings from animal studies to humans in a clinical setting has not always been straightforward. We have pioneered the use of systematic review and meta-analysis - tools initially developed to analyse data from human clinical trials - to investigate such translational failure by analysing data from animal studies. We and others have shown that in published reports of in vivo disease modelling studies there are often flaws in their design and conduct, and there is a low prevalence of reporting of measures to reduce the risk of bias. We have also shown that studies at risk of bias tend to give inflated (higher) estimates of treatment effects. As we have made progress, a central objective of our approach has been to support this developing field by sharing our expertise with others who wish to conduct similar reviews in their own areas of research. This involves offering methodological advice and support, a data repository, and access to our data management platform. However, we are approaching the limits of our capacity to do this, and this infrastructure funding would allow us to develop an improved database, with improved capacity for analysis and a web interface; and to provide more organised support including user manuals, online training materials and telephone and in-person advice to those wishing to conduct systematic reviews and meta-analyses. Systematic review and meta-analysis of in vivo studies can provide evidence to change research practice; our work has identified risk of bias and publication bias in in vivo studies, led to Good Laboratory Practice guidelines for stroke modelling (2009), and helped inform the development of the ARRIVE guidelines. Our work is shared with NINDS grant awarding panels prior to funding decisions, informed the NINDS/NIH Transparency paper in Nature (2012; 16 of 64 references were to our work); and thereby informed the recent change in policy at the Nature Publishing Group, requiring reporting of risk of bias items such as randomisation, blinding, inclusion and exclusion criteria and sample size calculations.These issues are fundamental to the 3Rs, partly because of the critical importance of getting the size of the experiment right, and secondly because an experiment at high risk of bias contributes less useful information than an experiment using the same number of animals at low risk of bias; identifying risk of bias items, and how investigators might reduce the risk of bias, is therefore critical to the 3Rs. It is our view that, while much has been achieved over the last 10 years, the utility of in vivo research could be substantially improved by the use of this technique across a much broader range of in vivo models. The purpose of this application is to allow us to be a catalyst for that much wider adoption (the demand for which is already manifest), and to allow those entering the field now to benefit from the learning and the methodological developments which we assimilated through experience. Briefly, this will involve:(i) highlighting the importance of experimental design to improve the validity and statistical rigour of animal studies; (ii) identifying which outcome measures require fewer animals because of the variance observed, (iii) supporting the reduction of the number of animals sacrificed in studies that are too small to detect reliably the effect being sought or unnecessarily too large, , (iv) determining whether high severity tests or multiple tests are necessary, whether lengthy experiments are of added value or whether those of shorter duration are as useful, and (v) assessing publication bias where we anticipate results will be used to drive a change towards reporting of positive, negative and neutral results.