Letter to the editor: Testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis

被引:0
|
作者
Leventhal, Emily L. [1 ,2 ]
Daamen, Andrea R. [1 ,2 ]
Lipsky, Peter E. [1 ,2 ]
机构
[1] AMPEL BioSolut LLC, Charlottesville, VA 22902 USA
[2] RILITE Res Inst, Charlottesville, VA 22902 USA
关键词
systemic lupus erythematosus; machine learning; lupus nephritis; precision medicine;
D O I
10.1093/bib/bbad322
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Because of the clinical heterogeneity among patients with systemic lupus erythematosus (SLE), developing molecular profiles that predict clinical features can be useful in creating a personalized approach to treatment. Toro-Dominguez et al. created a web tool to aid in therapeutic decision making for clinicians that predicts clinical features associated with SLE from blood transcriptomic data. Specifically, they present a machine learning model that predicts the presence of proliferative nephritis from blood transcriptomics. Here, we report use of the tool in independent datasets and found that it did not perform sufficiently well to consider replacement of the standard kidney biopsy as a diagnostic procedure.
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页数:3
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