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发表偏倚与荟萃分析:一个实际例子。

Publication bias and meta-analyses: a practical example.

作者信息

Burdett Sarah, Stewart Lesley A, Tierney Jayne F

机构信息

Meta-analysis Group, Medical Research Council Clinical Trials Unit, London, UK.

出版信息

Int J Technol Assess Health Care. 2003 Winter;19(1):129-34. doi: 10.1017/s0266462303000126.

Abstract

OBJECTIVES

Publication bias is widely appreciated, but considerable time and effort are needed to locate and obtain data from unpublished randomized controlled trials (RCTs), those published in non-English language journals or those reported in the gray literature; for this publication, we will call this collection of trials the "gray+literature." However, excluding such trials from systematic reviews could introduce bias and give rise to misleading conclusions.

METHODS

We aimed to explore and quantify the impact of inclusion of gray+ literature on the results of all completed individual patient data (IPD) reviews coordinated by our group (13 meta-analyses). For each IPD review, results were calculated for RCTs fully published in English language journals and RCTs fully published in English language journals and the gray+literature.

RESULTS

The IPD meta-analyses based only on RCTs that were fully published in English language journals tended to give more favorable results than those that included RCTs from the gray+literature. Although in most cases the addition of gray+data gave less encouraging results, moving the estimated treatment effect toward a null result, the direction of effect was not always predictable.

CONCLUSIONS

We recommend that all systematic reviews should at least attempt to identify trials reported in the gray+literature and, where possible, obtain data from them.

摘要

目的

发表偏倚已广为人知,但要从未发表的随机对照试验(RCT)、非英文期刊发表的试验或灰色文献报道的试验中查找和获取数据,需要花费大量时间和精力;在本出版物中,我们将这类试验的集合称为“灰色文献”。然而,在系统评价中排除此类试验可能会引入偏倚并导致误导性结论。

方法

我们旨在探索和量化纳入灰色文献对我们小组协调完成的所有个体患者数据(IPD)评价结果(13项荟萃分析)的影响。对于每项IPD评价,分别计算完全发表于英文期刊的RCT以及完全发表于英文期刊和灰色文献的RCT的结果。

结果

仅基于完全发表于英文期刊的RCT的IPD荟萃分析往往比纳入灰色文献中的RCT的分析给出更有利的结果。虽然在大多数情况下,添加灰色文献数据得出的结果不那么令人鼓舞,使估计的治疗效果趋向于无效结果,但效果方向并非总是可预测的。

结论

我们建议所有系统评价至少应尝试识别灰色文献中报道的试验,并尽可能从中获取数据。

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