Robust statistical methods for analysis of biomarkers measured with batch/experiment-specific errors.
Robust statistical methods for analysis of biomarkers measured with batch/experiment-specific errors.
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DOI：
10.1002/sim.3796
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发表时间：
2010-02-10
影响因子：
2
通讯作者：
Bostick, Roberd M.
中科院分区：
文献类型：
--
作者：
Long, Qi;Flanders, W. Dana;Fedirko, Veronika;Bostick, Roberd M.
在许多生物学研究中，生物标志物的测量存在误差。此外，研究样品通常分为不同批次进行测量，从不同实验中收集的数据用于单一分析。一般来说，测量误差的结构是未知的，不容易确定。虽然进行测量的条件从一个批次/实验到另一个批次/实验是不同的，但它们通常在每个批次/实验中保持稳定。因此，测量误差可以被认为是批次/实验特异性的，即，在每个批次/实验内是固定的，这导致每个批次/实验内的等级保持特性。在这种情况下，我们研究了稳健的统计方法，用于分析结果变量与测量误差的预测因子之间的关联，并评估这些生物标志物的诊断或预测准确性。我们的方法不需要假设的结构和分布的测量误差，这往往是不现实的。与现有的基于测量误差的正态性和加性结构的方法相比，我们的方法在偏离这些假设的情况下仍然可以得到有效的推论。所提出的方法很容易实现使用现成的软件。仿真研究表明，在各种测量误差结构下，所提出的方法的性能是令人满意的，即使是一个相当小的样本量，而现有的方法下错误指定的结构和天真的方法表现出显着的偏见。我们的方法说明使用生物标志物验证结直肠肿瘤的病例对照研究。
In many biological studies, biomarkers are measured with errors. In addition, study samples are often divided and measured in separate batches, and data collected from different experiments are used in a single analysis. Generally speaking, the structure of the measurement error is unknown and is not easy to ascertain. While the conditions under which the measurements are taken vary from one batch/experiment to another, they are often held steady within each batch/experiment. Thus, the measurement error can be considered batch/experiment specific, that is, fixed within each batch/experiment, which result into a rank preserving property within each batch/experiment. Under this condition, we study robust statistical methods for analyzing the association between an outcome variable and predictors measured with error, and evaluating the diagnostic or predictive accuracy of these biomarkers. Our methods require no assumptions on the structure and distribution of the measurement error, which are often unrealistic. Compared to existing methods that are predicated on normality and additive structure of measurement errors, our methods still yield valid inferences under departure from these assumptions. The proposed methods are easy to implement using off-shelf software. Simulation studies show that under various measurement error structures, the performance of the proposed methods is satisfactory even for a fairly small sample size, whereas existing methods under misspecified structures and a naive approach exhibited substantial bias. Our methods are illustrated using a biomarker validation case-control study for colorectal neoplasms.
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DOI：
10.1158/1940-6207.capr-08-0157
发表时间：
2009-03
期刊：
Cancer prevention research (Philadelphia, Pa.)
影响因子：
--
作者：
Fedirko V;Bostick RM;Flanders WD;Long Q;Shaukat A;Rutherford RE;Daniel CR;Cohen V;Dash C
通讯作者：
Dash C
影响因子：
4.4
作者：
Ye H;Yu T;Temam S;Ziober BL;Wang J;Schwartz JL;Mao L;Wong DT;Zhou X
通讯作者：
Zhou X
影响因子：
3.7
作者：
STEFANSKI, LA;BUZAS, JS
通讯作者：
BUZAS, JS
DOI：
10.1158/1055-9965.epi-08-0732
发表时间：
2009-01
期刊：
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
影响因子：
--
作者：
Daniel CR;Bostick RM;Flanders WD;Long Q;Fedirko V;Sidelnikov E;Seabrook ME
通讯作者：
Seabrook ME
影响因子：
4.2
作者：
Blanck, HM;Bowman, BA;Miller, DT
通讯作者：
Miller, DT