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从多个随机试验中计算附加治疗效果可提供组合疗法的有用估计。

Calculating additive treatment effects from multiple randomized trials provides useful estimates of combination therapies.

机构信息

Faculty of Health Sciences, University of Ottawa, 43 Templeton Street, Ottawa, Ontario, Canada.

出版信息

J Clin Epidemiol. 2012 Dec;65(12):1282-8. doi: 10.1016/j.jclinepi.2012.07.012. Epub 2012 Sep 13.

Abstract

OBJECTIVE

Many clinicians and decision makers want to know the combined effects of treatments that have not been evaluated in combination. It is possible to determine such treatment effects by making assumptions about the additive effects. We discuss here the prerequisites and methods of applying additivity assumptions in synthesizing the evidence from randomized trials and multiple treatment meta-analyses.

STUDY DESIGN AND SETTING

Using statistical approaches, we demonstrate the utility of additivity of both pairwise randomized trials and multiple treatment comparison meta-analyses.

RESULTS

We present illustratively an example on estimating the treatment effects of drug combinations for chronic obstructive pulmonary disease. We confirm the additive treatment effects by comparing with direct combination treatment trial results.

CONCLUSION

Additive effects may be a useful tool to estimate the effectiveness of treatment combinations.

摘要

目的

许多临床医生和决策者希望了解尚未联合评估的治疗方法的综合效果。通过对加性效应做出假设,可以确定此类治疗效果。我们在此讨论了在综合随机试验和多种治疗荟萃分析证据时应用加性假设的前提条件和方法。

研究设计和设置

使用统计方法,我们展示了对配对随机试验和多种治疗比较荟萃分析的加性的实用性。

结果

我们以一个慢性阻塞性肺疾病药物联合治疗的例子来说明如何估计药物联合的治疗效果。我们通过与直接联合治疗试验结果进行比较,证实了治疗效果具有加性。

结论

加性效应可能是估计治疗组合有效性的有用工具。

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