Baseline CD317 Expression Predicting Anifrolumab Response in SLE

A clinical biomarker dataset from a prospective study of 31 SLE patients initiating anifrolumab treatment. It contains flow cytometry measurements of immune cell subsets and type I IFN-associated markers used to predict 6-month clinical response. The data identifies baseline CD317 expression on T cells as the top predictor, with an AUC of 0.89.

Use Cases

• Train a classifier to predict clinical response using baseline CD317 expression on T cells and B cells.
• Analyze the correlation between T-peripheral-helper–cell frequency and successful glucocorticoid tapering outcomes.
• Compare the predictive performance of CD169 expression on monocytes against a four-gene IFN gene signature.
• Build a model to separate responders from non-responders using the ten biomarkers that showed significant changes.

Strengths

• Data is from a prospective clinical study specifically designed to identify biomarkers for anifrolumab response.
• Identifies a top-performing biomarker (CD317 on T cells) with a reported AUC of 0.89 for predicting response.
• Includes results for 31 analyzed patients, with 15 responders and 16 non-responders.

Limitations

• Small sample size of 31 patients limits statistical power and generalizability of findings.
• Biomarker measurements are specific to the study's flow cytometry protocol and may not be directly comparable to other assays.
• Clinical response was defined at a single 6-month time point, lacking longitudinal outcome data.

Provenance

Source

figshare, authored by Koichi Kimura.

Collection Method

Prospective enrollment of SLE patients, with immune cell subsets and markers evaluated by flow cytometry.

Time Range

Study period not specified in input; data reflects baseline and 6-month response assessment.

Freshness

Last updated in March 2026.

Geography

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