A resample-replace lasso procedure for combining high-dimensional markers with limit of detection

© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Bibliographische Detailangaben
Veröffentlicht in:Journal of applied statistics. - 1991. - 49(2022), 16 vom: 01., Seite 4278-4293
1. Verfasser: Wang, Jinjuan (VerfasserIn)
Weitere Verfasser: Zhao, Yunpeng, Tang, Larry L, Mueller, Claudius, Li, Qizhai
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Journal of applied statistics
Schlagworte:Journal Article 97K80 Limit of detection (LOD) area under the receiver operating characteristic curve (AUC) graphical lasso high-dimensional data imputation precision matrix
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520 |a In disease screening, a biomarker combination developed by combining multiple markers tends to have a higher sensitivity than an individual marker. Parametric methods for marker combination rely on the inverse of covariance matrices, which is often a non-trivial problem for high-dimensional data generated by modern high-throughput technologies. Additionally, another common problem in disease diagnosis is the existence of limit of detection (LOD) for an instrument - that is, when a biomarker's value falls below the limit, it cannot be observed and is assigned an NA value. To handle these two challenges in combining high-dimensional biomarkers with the presence of LOD, we propose a resample-replace lasso procedure. We first impute the values below LOD and then use the graphical lasso method to estimate the means and precision matrices for the high-dimensional biomarkers. The simulation results show that our method outperforms alternative methods such as either substitute NA values with LOD values or remove observations that have NA values. A real case analysis on a protein profiling study of glioblastoma patients on their survival status indicates that the biomarker combination obtained through the proposed method is more accurate in distinguishing between two groups 
650 4 |a Journal Article 
650 4 |a 97K80 
650 4 |a Limit of detection (LOD) 
650 4 |a area under the receiver operating characteristic curve (AUC) 
650 4 |a graphical lasso 
650 4 |a high-dimensional data 
650 4 |a imputation 
650 4 |a precision matrix 
700 1 |a Zhao, Yunpeng  |e verfasserin  |4 aut 
700 1 |a Tang, Larry L  |e verfasserin  |4 aut 
700 1 |a Mueller, Claudius  |e verfasserin  |4 aut 
700 1 |a Li, Qizhai  |e verfasserin  |4 aut 
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