Pennello Gene A
Diagnostic Devices Branch, Division of Biostatistics, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD, USA.
Clin Trials. 2013 Oct;10(5):666-76. doi: 10.1177/1740774513497541. Epub 2013 Aug 27.
Biomarker assays can be evaluated for analytical performance (ability of assay to measure the biomarker quantity) and clinical performance (ability of assay result to inform of the clinical condition of interest). Additionally, a biomarker assay is said to have clinical utility if it ultimately improves patient outcomes when used as intended.
This article reviews analytical and clinical performance studies of biomarker assay tests and also some designs of clinical utility studies.
Appropriate design and statistical analysis of analytical and clinical evaluation studies depend on the intended clinical use of the test. Some key aspects to valid performance studies include using subjects who are independent of those used to develop the test, masking users of the test to any other available test or reference results, and including in the primary statistical analysis subjects with unavailable results in an intention-to-diagnose analysis. Ingenuity in study design and analysis may be required for efficient and unbiased estimation of performance.
Performance studies need to be carefully planned as they can be prone to many sources of bias. Analytical inaccuracy can hamper the clinical performance of biomarkers.
As biomedical research and technology advance, challenges in study design and statistical analysis will continue to emerge for analytical and clinical performance studies of biomarker assays. Although not emphasized in some circles, the analytical performance of a biomarker assay is important to characterize. Analytical performance studies have many study design and statistical analysis challenges that deserve further attention.
生物标志物检测可针对分析性能（检测测量生物标志物数量的能力）和临床性能（检测结果告知感兴趣临床状况的能力）进行评估。此外，如果生物标志物检测按预期使用时最终能改善患者预后，则称其具有临床效用。
本文综述生物标志物检测的分析和临床性能研究以及一些临床效用研究设计。
分析和临床评估研究的恰当设计与统计分析取决于检测的预期临床用途。有效性能研究的一些关键方面包括使用与用于开发检测的受试者无关的受试者、对检测使用者隐瞒任何其他可用检测或参考结果，以及在意向性诊断分析的主要统计分析中纳入结果不可用的受试者。可能需要在研究设计和分析方面发挥独创性，以高效且无偏地估计性能。
性能研究需要精心规划，因为它们可能容易出现多种偏倚来源。分析不准确会妨碍生物标志物的临床性能。
随着生物医学研究和技术的进步，生物标志物检测的分析和临床性能研究在研究设计和统计分析方面的挑战将持续出现。尽管在某些领域未得到强调，但生物标志物检测的分析性能对于特征描述很重要。分析性能研究存在许多值得进一步关注的研究设计和统计分析挑战。
