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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Univ Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, PakistanUniv Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, Pakistan
Sajjad, Saba
Farman, Sumaira
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Univ Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, PakistanUniv Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, Pakistan
Farman, Sumaira
Saeed, Muhammad Ahmed
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Univ Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, PakistanUniv Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, Pakistan
Saeed, Muhammad Ahmed
Ahmad, Nighat Mir
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Univ Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, PakistanUniv Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, Pakistan
Ahmad, Nighat Mir
Butt, Bilal Azeem
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Univ Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, PakistanUniv Hlth Sci, Fatima Mem Coll Med & Dent, Div Rheumatol, Lahore, Pakistan