Meta-analysis for diagnostic test accuracy (DTA) has been a standard research method for synthesizing evidence from diagnostic studies. In DTA meta-analysis, although publication bias is an important source of bias, no certain methods similar to the Egger test in univariate meta-analysis have been developed to detect such bias. However, several recent studies have discussed these methods in the framework of multivariate meta-analysis, and some generalized Egger tests have been developed. The R package MVPBT (https://cran.r-project.org/web/packages/MVPBT/) was developed to implement the generalized Egger tests developed by Noma (2020; Biometrics 76, 1255-1259) for DTA meta-analysis. Noma's publication bias tests effectively incorporate the correlation information between multiple outcomes and are expected to improve the statistical powers. The present paper provides a nontechnical introduction and practical examples of data analyses of the publication bias tests of DTA meta-analysis using the MVPBT package.

翻译：诊断试验准确性（DTA）荟萃分析已成为综合诊断研究证据的标准研究方法。在DTA荟萃分析中，尽管发表偏倚是偏倚的重要来源，但尚未开发出类似单变量荟萃分析中Egger检验的确定方法用于检测此类偏倚。然而，近期多项研究已在多变量荟萃分析框架下探讨了这些方法，并开发了一些广义Egger检验。R软件包MVPBT（https://cran.r-project.org/web/packages/MVPBT/）旨在实现Noma（2020；Biometrics 76, 1255-1259）为DTA荟萃分析开发的广义Egger检验。Noma的发表偏倚检验有效整合了多个结局指标间的相关性信息，有望提升统计检验效能。本文提供了使用MVPBT软件包进行DTA荟萃分析发表偏倚检验的非技术性介绍及实际数据分析案例。