多阈值诊断准确性研究的元分析:模拟研究中各种方法的比较

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Biometrical Journal Pub Date : 2024-09-27 DOI:10.1002/bimj.202300101
Antonia Zapf, Cornelia Frömke, Juliane Hardt, Gerta Rücker, Dina Voeltz, Annika Hoyer
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引用次数: 0

摘要

诊断测试准确性(DTA)元分析方法的开发仍是一个活跃的研究领域。在标准情况下,每项研究只报告一对敏感性和特异性,这种方法如今几乎已成为常规应用,但对接收者操作特征曲线(ROC)进行元分析的方法却没有得到广泛应用。这种情况更为复杂,因为每项主要的 DTA 研究都可能报告多对灵敏度和特异性,每对灵敏度和特异性都对应不同的阈值。在早前发表的一项案例研究中,我们在一个真实世界的数据示例中应用了多种方法对具有多个阈值的 DTA 研究进行元分析(Zapf 等人,《生物计量学杂志》。2021; 63(4):699-711).迄今为止,还没有模拟研究系统地比较不同方法在已知真相的各种情况下的性能。本文旨在填补这一空白,并介绍了一项模拟研究的结果,该研究比较了 ROC 曲线元分析的三种频数主义方法。我们根据医学研究中的一个例子进行了系统的模拟研究。在模拟中,所有三种方法都部分运行良好。霍耶及其同事的方法在大多数情况下略胜一筹,在实践中值得推荐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Meta-Analysis of Diagnostic Accuracy Studies With Multiple Thresholds: Comparison of Approaches in a Simulation Study

The development of methods for the meta-analysis of diagnostic test accuracy (DTA) studies is still an active area of research. While methods for the standard case where each study reports a single pair of sensitivity and specificity are nearly routinely applied nowadays, methods to meta-analyze receiver operating characteristic (ROC) curves are not widely used. This situation is more complex, as each primary DTA study may report on several pairs of sensitivity and specificity, each corresponding to a different threshold. In a case study published earlier, we applied a number of methods for meta-analyzing DTA studies with multiple thresholds to a real-world data example (Zapf et al., Biometrical Journal. 2021; 63(4): 699–711). To date, no simulation study exists that systematically compares different approaches with respect to their performance in various scenarios when the truth is known. In this article, we aim to fill this gap and present the results of a simulation study that compares three frequentist approaches for the meta-analysis of ROC curves. We performed a systematic simulation study, motivated by an example from medical research. In the simulations, all three approaches worked partially well. The approach by Hoyer and colleagues was slightly superior in most scenarios and is recommended in practice.

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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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