Deeks Jonathan J, Macaskill Petra, Irwig Les
Screening and Test Evaluation Program, School of Public Health, University of Sydney, Sydney, New South Wales 2006, Australia.
J Clin Epidemiol. 2005 Sep;58(9):882-93. doi: 10.1016/j.jclinepi.2005.01.016.
Publication bias and other sample size effects are issues for meta-analyses of test accuracy, as for randomized trials. We investigate limitations of standard funnel plots and tests when applied to meta-analyses of test accuracy and look for improved methods.
Type I and type II error rates for existing and alternative tests of sample size effects were estimated and compared in simulated meta-analyses of test accuracy.
Type I error rates for the Begg, Egger, and Macaskill tests are inflated for typical diagnostic odds ratios (DOR), when disease prevalence differs from 50% and when thresholds favor sensitivity over specificity or vice versa. Regression and correlation tests based on functions of effective sample size are valid, if occasionally conservative, tests for sample size effects. Empirical evidence suggests that they have adequate power to be useful tests. When DORs are heterogeneous, however, all tests of funnel plot asymmetry have low power.
Existing tests that use standard errors of odds ratios are likely to be seriously misleading if applied to meta-analyses of test accuracy. The effective sample size funnel plot and associated regression test of asymmetry should be used to detect publication bias and other sample size related effects.
如同随机试验一样，发表偏倚和其他样本量效应是测试准确性的Meta分析中存在的问题。我们研究了标准漏斗图和检验应用于测试准确性的Meta分析时的局限性，并寻找改进方法。
在模拟的测试准确性Meta分析中，估计并比较现有样本量效应检验和替代检验的I型和II型错误率。
当疾病患病率不同于50%，且阈值更倾向于敏感性而非特异性或相反时，对于典型的诊断比值比（DOR），Begg检验、Egger检验和Macaskill检验的I型错误率会膨胀。基于有效样本量函数的回归检验和相关性检验对于样本量效应是有效的检验，尽管偶尔较为保守。经验证据表明它们有足够的效能成为有用的检验。然而，当DORs存在异质性时，所有漏斗图不对称性检验的效能都很低。
如果将使用比值比标准误的现有检验应用于测试准确性的Meta分析，很可能会产生严重误导。应使用有效样本量漏斗图和相关的不对称性回归检验来检测发表偏倚和其他与样本量相关的效应。
