诊断试验准确性Meta分析中分层汇总ROC曲线的小样本效应：潜在准确性与阈值趋势
Small-study effects on the hierarchical summary ROC curve: latent accuracy and threshold trends in meta-analysis of diagnostic test accuracy
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中文总结 AI 辅助
本研究针对诊断试验准确性Meta分析，提出一种基于HSROC模型的似然比检验，用于区分小样本效应中的潜在准确性趋势与阈值趋势，模拟显示其功效优于Deeks检验，并在结直肠癌综述中成功检测被掩盖的潜在准确性趋势。
中文摘要 AI 辅助
诊断性Meta分析通常使用Deeks检验评估小样本效应，该检验检验对数诊断比值比中研究规模趋势。在分层汇总受试者工作特征（HSROC）模型下，该量反映潜在准确性和阈值，除非曲线对称。因此，阈值趋势可以在没有潜在准确性趋势的情况下产生对数诊断比值比趋势，或掩盖已有的潜在准确性趋势。我们开发了一种似然比检验，用于在共同形状二项式HSROC模型下检验潜在准确性趋势，同时允许阈值趋势不受限制。其零假设为汇总曲线在研究规模间不变。使用相同二项式拟合的对数诊断比值比检验提供了不同零假设下的比较。在模拟中，所提出的检验在其零假设下保持接近名义水平，并且在仅有潜在准确性趋势时比Deeks检验具有更高功效。在一项关于粪便免疫化学检测的结直肠癌综述中，它检测到被相反阈值贡献在对数诊断比值比尺度上掩盖的负向潜在准确性趋势。所有三种检验均检测到深静脉血栓形成中阻抗体积描记法的规模趋势，此时拟合曲线近似对称。所提出的检验区分汇总曲线的变化与操作位置的变化。
英文摘要
Diagnostic meta-analyses commonly assess small-study effects using the Deeks test, which tests for a study-size trend in the log diagnostic odds ratio. Under the hierarchical summary receiver operating characteristic (HSROC) model, this quantity reflects both latent accuracy and threshold unless the curve is symmetric. A threshold trend can therefore generate a log diagnostic odds ratio trend without a latent accuracy trend, or conceal an existing one. We develop a likelihood-ratio test of the latent accuracy trend under a common-shape binomial HSROC model, leaving the threshold trend unrestricted. Its null hypothesis states that the summary curve is unchanged across study sizes. A log diagnostic odds ratio test using the same binomial fit provides a comparison with a different null hypothesis. In simulations, the proposed test remained near its nominal level under its null and had higher power than Deeks with a latent accuracy trend alone. In a colorectal cancer review of faecal immunochemical tests, it detected a negative latent accuracy trend obscured on the log diagnostic odds ratio scale by an opposing threshold contribution. All three tests detected size trends for impedance plethysmography in deep-vein thrombosis, where the fitted curve was nearly symmetric. The proposed test distinguishes changes in the summary curve from changes in operating position.
发表机构
- 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）
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