Network meta-analysis (NMA) allow combining efficacy information from multiple comparisons from trials assessing different therapeutic interventions for a given disease and to estimate unobserved comparisons from a network of observed comparisons. Applying NMA on diagnostic accuracy studies is a statistical challenge given the inherent correlation of sensitivity and specificity. A conceptually simple and novel hierarchical arm-based (AB) model which expresses the logit transformed sensitivity and specificity as sum of fixed effects for test, correlated study-effects and a random error associated with various tests evaluated in given study is proposed. We apply the model to previously published meta-analyses assessing the accuracy of diverse cytological and molecular tests used to triage women with minor cervical lesions to detect cervical precancer and the results compared with those from the contrast-based (CB) model which expresses the linear predictor as a contrast to a comparator test. The proposed AB model is more appealing than the CB model in that it yields the marginal means which are easily interpreted and makes use of all available data and easily accommodates more general variance-covariance matrix structures.
Testing for Publication Bias in Diagnostic Meta-Analysis: A Simulation Study
本研究通过模拟的方法研究了几种统计检验在诊断性荟萃分析中检测发表偏倚的性能。虽然双变量模型应用于汇总诊断荟萃分析中主要研究的数据，但诊断准确性的单变量指标更适合检测发表偏倚。与早期的研究相反，早期的研究仅关注诊断比值比或其对数（$\lnω$），这些测试与四种不同的诊断准确性单变量测量相结合。对于检验和单变量测量的每种组合，在不同条件下检查第一类错误率和统计功效。结果表明，在诊断荟萃分析中，不推荐使用基于线性回归或等级相关的检验，因为无论采用何种单变量测量，第一类错误率都被夸大或把握度太低。相比之下，修整和填充与$\lnω$的组合即使在极端情况下（至少当每项荟萃分析的研究数量足够大时），也具有非膨胀或仅轻微膨胀的第一类错误率和中到高功效。因此，我们建议在诊断性荟萃分析中应用修剪和填充结合$\lnω$检测漏斗图不对称性。请引用发表在Statistics in Medicine（https：//doi.org/10.1002/sim.6177）上的这篇论文。
Meta-analysis of diagnostic test accuracy with multiple disease stages: combining stage-specific and merged-stage data
Population Health Sciences, Bristol Medical School, University of Bristol（布里斯托大学布里斯托医学院人口健康科学）；Manchester Centre for Health Economics, University of Manchester（曼彻斯特大学曼彻斯特卫生经济学中心）
Small-study effects on the hierarchical summary ROC curve: latent accuracy and threshold trends in meta-analysis of diagnostic test accuracy
Graduate School of Informatics, Osaka Metropolitan University（大阪公立大学情报学府）；German Research Center for Artificial Intelligence GmbH (DFKI)（德国人工智能研究中心有限公司）；Department of Biostatistics, Nagoya University Graduate School of Medicine（名古屋大学医学研究科生物统计学科）；Department of Clinical Biostatistics, School of Public Health, Graduate School of Medicine, Kyoto University（京都大学医学研究科公共卫生学院临床生物统计学科）
Robust inference methods of diagnostic test accuracy meta-analysis for influential outlying studies via density power divergence
The Graduate Institute for Advanced Studies, The Graduate University for Advanced Studies（高级研究研究生院，高级研究院）；Human Biology Creation Hub, Deep Human Biology Learning, Eisai Co. Ltd.（人类生物学创造中心，深层人类生物学学习，卫材株式会社）；Department of Interdisciplinary Statistical Mathematics, The Institute of Statistical Mathematics（交叉统计数学系，统计数学研究所）；Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center—University of Freiburg（医学生物统计学与统计研究所，医学院及医学中心——弗赖堡大学）
Causally Interpretable Meta-Mediation Analysis With Missing At Random Mediator and Outcome Data
EPILOGY, Institut Mondor of Biomedical Research, INSERM U955（INSERM U955 蒙多尔生物医学研究所 EPILOGY）；Université Paris-Est Créteil（巴黎东克雷泰伊大学）；Mines Paris, Université Paris Sciences Lettres（巴黎矿业学院，巴黎文理研究大学）；Department of Mathematics, Université du Québec à Montréal（蒙特利尔大学数学系）
