随机对照试验的荟萃分析与质量评价

Seung Wook Lee
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引用次数: 3

摘要

荟萃分析是两个或多个独立研究结果的统计组合。荟萃分析的潜在优势包括:能力的增强、准确性的提高、回答个别研究没有提出的问题的能力,以及解决由相互矛盾的主张引起的争议的机会。然而,它们也有可能产生严重的误导,特别是如果没有仔细考虑特定的研究设计、研究内偏差、研究间的差异和报告偏差。熟悉个体研究中测量结果的数据类型(如二分类、连续),并选择合适的效果测量方法来比较干预组是很重要的。大多数元分析方法是对不同研究的效果估计的加权平均值的变化。必须考虑研究间的差异(异质性)。随机效应荟萃分析通过假设潜在效应遵循正态分布来考虑异质性。在准备荟萃分析的过程中需要各种判断。其中,随机对照试验的质量评价尤为重要。有几种评估临床试验方法学质量的方法,包括量表、个体标记物和检查表。对研究质量的分析使meta分析的结果更加可靠。敏感性分析应用于检查总体发现对潜在影响决策是否稳健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meta-Analysis and Quality Assessment of Randomized Controlled Trials
Meta-analysis is the statistical combination of results from two or more separate studies. Potential advantages of meta-analyses include an increase in power, an improvement in precision, the ability to answer questions not posed by individual studies, and the opportunity to settle controversies arising from conflicting claims. However, they also have the potential to mislead seriously, particularly if specific study designs, within-study biases, variation across studies, and reporting biases are not carefully considered. It is important to be familiar with the type of data (e.g. dichotomous, continuous) that result from measurement of an outcome in an individual study, and to choose suitable effect measures for comparing intervention groups. Most meta-analysis methods are variations on a weighted average of the effect estimates from the different studies. Variation across studies (heterogeneity) must be considered. Random-effects meta-analyses allow for heterogeneity by assuming that underlying effects follow a normal distribution. Various judgments are required in the process of preparing a meta-analysis. Especially, quality assessment of randomized controlled trial is essential. There are several methods to assess the methodological quality of clinical trials, including scales, individual markers, and checklists. Analyzing the quality of studies makes the results of meta-analysis more reliable. Sensitivity analyses should be used to examine whether overall findings are robust to potentially influential decisions.
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