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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-Domínguez 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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