Terrin Norma, Schmid Christopher H, Lau Joseph
Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, 750 Washington Street, Box 63, Boston, MA 02111, USA.
J Clin Epidemiol. 2005 Sep;58(9):894-901. doi: 10.1016/j.jclinepi.2005.01.006.
Publication bias and related biases can lead to overly optimistic conclusions in systematic reviews. The funnel plot, which is frequently used to detect such biases, has not yet been subjected to empirical evaluation as a visual tool. We sought to determine whether researchers can correctly identify publication bias from visual inspection of funnel plots in typical-size systematic reviews.
A questionnaire with funnel plots containing 10 studies each (the median number in medical meta-analyses) was completed by 41 medical researchers, including clinical research fellows in a meta-analysis class, faculty in clinical care research, and experienced systematic reviewers.
On average, participants correctly identified 52.5% (95% CI 50.6-54.4%) of the plots as being affected or unaffected by publication bias. The weighted mean percent correct, which adjusted for the fact that asymmetric plots are more likely to occur in the presence of publication bias, was also low (48.3 to 62.8%, depending on the presence or absence of publication bias and heterogeneous study effects).
Researchers who assess for publication bias using the funnel plot may be misled by its shape. Authors and readers of systematic reviews need to be aware of the limitations of the funnel plot.
发表偏倚及相关偏倚可能导致系统评价得出过于乐观的结论。漏斗图常用于检测此类偏倚,但作为一种可视化工具,尚未经过实证评估。我们试图确定研究人员能否通过对典型规模系统评价中的漏斗图进行目视检查来正确识别发表偏倚。
41名医学研究人员完成了一份包含漏斗图的问卷,每个漏斗图包含10项研究(医学荟萃分析中的中位数),其中包括荟萃分析课程的临床研究人员、临床护理研究教员以及经验丰富的系统评价员。
参与者平均正确识别出52.5%(95%可信区间50.6 - 54.4%)的漏斗图受或不受发表偏倚影响。加权平均正确百分比也较低(48.3%至62.8%,取决于是否存在发表偏倚和异质性研究效应),该百分比对非对称漏斗图在存在发表偏倚时更可能出现这一事实进行了调整。
使用漏斗图评估发表偏倚的研究人员可能会被其形状误导。系统评价的作者和读者需要意识到漏斗图的局限性。