Clinical Biomarker Data for Anifrolumab Response in SLE Patients

A 31-patient study by Koichi Kimura identifies biomarkers predicting response to anifrolumab in systemic lupus erythematosus. The dataset contains flow cytometry and clinical response data for 15 responders and 16 non-responders, with baseline CD317 expression on T cells showing high predictive power.

Use Cases

• Analyze baseline CD317 expression on T cells to predict 6-month BICLA response and glucocorticoid tapering success.
• Compare predictive performance of CD317 expression on T cells against the four-gene IFN gene signature (IFNGS) using AUC metrics.
• Investigate correlations between baseline CD169 expression on monocytes and T-peripheral-helper–cell frequency with clinical response outcomes.
• Model the discriminative power of ten significant biomarkers, including CD317 on B cells, for separating responders from non-responders.

Strengths

• Data from a 31-patient prospective clinical study with defined responder (15) and non-responder (16) groups.
• Includes biomarker measurements with statistically significant results, such as an AUC of 0.89 for CD317 on T cells.
• Clear clinical response criteria based on BICLA response and successful glucocorticoid tapering at 6 months.

Limitations

• Small sample size of 31 patients limits statistical power and generalizability of findings.
• Dataset scope is limited to a single study's cohort, requiring external validation for broader application.
• The 10.7 KB file size indicates a very limited dataset, likely containing summary or key results rather than raw patient-level data.

Provenance

Source

Koichi Kimura via figshare.

Collection Method

Prospective clinical study using flow cytometry and quantitative PCR (qPCR) on enrolled SLE patients initiating anifrolumab.

Time Range

Clinical response assessed at 6 months post-treatment initiation.

Freshness

Last updated March 2026.

Geography

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