Sandercock P
Department of Clinical Neurosciences, Western General Hospital, Edinburgh, Scotland.
Ann N Y Acad Sci. 1993 Dec 31;703:149-54; discussion 154-5. doi: 10.1111/j.1749-6632.1993.tb26344.x.
Formal overviews (or meta-analyses) are now widely accepted as the most reliable way to evaluate the evidence from several randomized controlled trials that have all assessed a particular form of therapy. If a limited amount of trial data has accumulated, overviews can be undertaken at a relatively simple level, assembling just summary data extracted from published reports. Such overviews are likely to be incomplete and biased and may (because of the restricted number of analyses that are possible) not answer all the clinically important questions that might be addressed. Where a particularly large body of data from randomized trials has accumulated, more thorough and detailed overview analyses are needed. Such detailed reviews are greatly facilitated if a collaborative group of all the trialists is formed. Such groups have sought to collate individual patient data (a very few key items for every patient randomized). A central statistical secretariat then coordinates the process of data collection, checking, and analysis. Analyses are presented to the whole group for discussion and final reports are published in the name of the whole group. Experience from two very large groups that have followed this model, the Antiplatelet Trialists' Collaboration and the Early Breast Cancer Trialists' Collaborative Group, has shown that detailed collaborative overviews have many benefits: the results are particularly clear and therefore have substantial public health impact; the areas of statistical and medical agreement on the evidence can be defined; the areas of uncertainty (and hence future research priorities) are clarified; and the group can disseminate the results particularly widely and rapidly.
正规综述(或荟萃分析)如今已被广泛认可为评估来自多项均对某种特定治疗形式进行评估的随机对照试验证据的最可靠方法。如果积累的试验数据量有限,可以在相对简单的层面进行综述,仅汇总从已发表报告中提取的总结数据。此类综述可能不完整且有偏差,并且(由于可能进行的分析数量有限)可能无法回答所有可能涉及的临床重要问题。当积累了来自随机试验的特别大量的数据时,就需要更全面、详细的综述分析。如果由所有试验者组成一个协作组,将极大地促进此类详细综述。这样的小组试图整理个体患者数据(对每个随机分组的患者记录很少的关键项目)。然后由一个中央统计秘书处协调数据收集、核查和分析过程。分析结果提交给整个小组进行讨论,最终报告以整个小组的名义发表。遵循这种模式的两个非常大型的小组,即抗血小板试验协作组和早期乳腺癌试验协作组的经验表明,详细的协作综述有诸多益处:结果特别清晰,因此对公共卫生有重大影响;可以界定证据在统计学和医学方面达成一致的领域;明确不确定性领域(以及未来的研究重点);并且该小组能够特别广泛和迅速地传播结果。