Ziegler A, König I R, Schulz-Knappe P
Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
Dtsch Med Wochenschr. 2013 May;138(19):e2-24. doi: 10.1055/s-0032-1327406. Epub 2013 Apr 30.
Biomarkers are of increasing importance for personalized medicine in many areas of application, such as diagnosis, prognosis, or the selection of targeted therapies. In many molecular biomarker studies, intensity values are obtained from large scale ‑omics experiments. These intensity values, such as protein concentrations, are often compared between at least two groups of subjects to determine the diagnostic ability of the molecular biomarker. Various prospective or retrospective study designs are available for molecular biomarker studies, and the biomarker used may be univariate or may even consist in a multimarker rule. In this work, several challenges are discussed for the planning and conduct of biomarker studies. The phases of diagnostic biomarker studies are closely related to levels of evidence in diagnosis, and they are therefore discussed upfront. Different study designs for molecular biomarker studies are discussed, and they primarily differ in the way subjects are selected. Using two systematic reviews from the literature, common sources of bias of molecular diagnostic studies are illustrated. The extreme selection of patients and controls and verification bias are specifically discussed. The pre-analytical and technical variability of biomarker measurements is usually expressed in terms of the coefficient of variation, and is of great importance for subsequent validation studies for molecular biomarkers. It is finally shown that the required sample size for biomarker validation quadratically increases with the coefficient of variation, and the effect is illustrated using real data from different laboratory technologies.
生物标志物在个性化医疗的诸多应用领域，如诊断、预后或靶向治疗的选择中，正变得越来越重要。在许多分子生物标志物研究中，强度值是从大规模组学实验中获得的。这些强度值，如蛋白质浓度，通常在至少两组受试者之间进行比较，以确定分子生物标志物的诊断能力。分子生物标志物研究有各种前瞻性或回顾性研究设计，所使用的生物标志物可能是单变量的，甚至可能由多标志物规则组成。在这项工作中，讨论了生物标志物研究规划和实施中的几个挑战。诊断性生物标志物研究的阶段与诊断证据水平密切相关，因此将提前进行讨论。讨论了分子生物标志物研究的不同研究设计，它们主要在受试者选择方式上有所不同。利用文献中的两项系统评价，阐述了分子诊断研究中常见的偏倚来源。特别讨论了患者和对照的极端选择以及验证偏倚。生物标志物测量的分析前和技术变异性通常用变异系数来表示，这对分子生物标志物的后续验证研究非常重要。最后表明，生物标志物验证所需的样本量随变异系数呈二次方增加，并使用来自不同实验室技术的实际数据说明了这种效应。
