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诊断研究中的缺失值和不确定结果——方法的范围综述。

Missing values and inconclusive results in diagnostic studies - A scoping review of methods.

机构信息

Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Germany.

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands.

出版信息

Stat Methods Med Res. 2023 Sep;32(9):1842-1855. doi: 10.1177/09622802231192954. Epub 2023 Aug 9.

Abstract

Most diagnostic studies exclude missing values and inconclusive results from the analysis or apply simple methods resulting in biased accuracy estimates. This may be due to the lack of availability or awareness of appropriate methods. This scoping review aimed to provide an overview of strategies to handle missing values and inconclusive results in the reference standard or index test in diagnostic accuracy studies. Conducting a systematic literature search in MEDLINE, Cochrane Library, and Web of Science, we could identify many articles proposing methods for addressing missing values in the reference standard. There are also several articles describing methods regarding missing values or inconclusive results in the index test. The latter encompass imputation, frequentist and Bayesian likelihood, model-based, and latent class methods. While methods for missing values in the reference standard are regularly applied in practice, this is not true for methods addressing missing values and inconclusive results in the index test. Our comprehensive overview and description of available methods may raise further awareness of these methods and will enhance their application. Future research is needed to compare the performance of these methods under different conditions to give valid and robust recommendations for their usage in various diagnostic accuracy research scenarios.

摘要

大多数诊断研究将缺失值和不确定结果排除在分析之外,或者应用简单的方法,导致准确性估计存在偏差。这可能是由于缺乏适当方法的可用性或意识。本范围综述旨在提供处理诊断准确性研究中参考标准或指标检验中缺失值和不确定结果的策略概述。通过在 MEDLINE、Cochrane 图书馆和 Web of Science 中进行系统文献检索,我们可以确定许多提出方法来处理参考标准中缺失值的文章。还有几篇文章描述了针对指标检验中缺失值或不确定结果的方法。后者包括插补、频率论和贝叶斯似然、基于模型和潜在类别方法。虽然参考标准中缺失值的方法在实践中经常应用,但在处理指标检验中缺失值和不确定结果的方法方面并非如此。我们对现有方法的全面概述和描述可能会进一步提高对这些方法的认识,并增强它们的应用。需要进一步的研究来比较这些方法在不同条件下的性能,以便为它们在各种诊断准确性研究场景中的使用提供有效和可靠的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44e9/10540494/bebec078e0ad/10.1177_09622802231192954-fig1.jpg

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