Strengths and limitations of meta-analysis: Larger studies may be more reliable
Strengths and limitations of meta-analysis: Larger studies may be more reliable
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DOI：
10.1016/s0197-2456(97)00024-x
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发表时间：
1997-12-01
期刊：
影响因子：
--
通讯作者：
Yusuf, S
中科院分区：
文献类型：
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作者：
Flather, MD;Farkouh, ME;Yusuf, S
随机对照试验的荟萃分析结合了解决类似问题的独立研究的信息，以提供更可靠的治疗效果估计。目前，荟萃分析的方法和有用性正在审查中。在本文的第一部分，我们总结了荟萃分析的局限性，并提出了改进建议。在第二部分中，我们使用元分析和随后的大型试验来说明解决同一问题的优势和局限性。我们发展的假设，荟萃分析的大小可能是一个有用的措施的可靠性。小型荟萃分析（即，少于200个结果事件的那些）可能仅对总结可用信息和为未来研究产生假设有用。即使p值显示出极端的统计学显著性，也应谨慎对待小型荟萃分析的结果。大型荟萃分析（即，具有几百个事件的那些）可能更可靠并且可能在临床上有用。使用个体患者数据对大型试验进行的良好荟萃分析可能提供队列总体和临床重要亚组中治疗效果的最佳估计。(C)Elsevier Science Inc. 1997.
Meta-analysis of randomized controlled trials combines information from independent studies that address a similar question to provide more reliable estimates of treatment effects. At the present time, the methodology and usefulness of meta-analysis is under scrutiny. In the first part of this paper, we summarize the limitations of meta-analysis and make suggestions for improvements. In the second part, we illustrate strengths and limitations using examples of meta-analyses and subsequent large trials that address the same question. We develop the hypothesis that the size of the meta-analysis may be a useful measure of reliability. Small meta-analyses (i.e., those with less than 200 outcome events) may only be useful for summarizing the available information and generating hypotheses for future research. the results of small meta-analyses should be regarded with caution, even if the p value shows extreme statistical significance. Larger meta-analyses (i.e., those with several hundred events) are likely to be more reliable and may be clinically useful. Well-conducted meta-analyses of large trials using individual patient data may provide the best estimates of treatment effects in the cohort overall and in clinically important subgroups. (C) Elsevier Science Inc. 1997.