Anifrolumab Response Biomarkers in Systemic Lupus Erythematosus Patients

Koichi Kimura's research dataset contains flow cytometry and clinical data from 31 SLE patients treated with anifrolumab. It identifies baseline CD317 expression on T cells as a predictive biomarker for 6-month clinical response, with an AUC of 0.89. The data supports biomarker discovery for personalized treatment strategies in lupus.

Use Cases

• Analyze baseline CD317 expression on T cells to predict anifrolumab clinical response using BICLA criteria.
• Compare discriminative power of CD317 expression on T cells against the four-gene IFN gene signature (IFNGS) for response prediction.
• Evaluate the relationship between baseline CD169 expression on monocytes and successful glucocorticoid tapering outcomes.
• Investigate T-peripheral-helper–cell frequency as a potential biomarker separating responders from non-responders.

Strengths

• Data from a prospective study of 31 SLE patients with defined responder (n=15) and non-responder (n=16) groups.
• Identifies a biomarker (CD317 on T cells) with high predictive power (AUC 0.89) for clinical response.
• Includes ten biomarkers showing significant changes, with four identified as higher at baseline in responders.

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.
• The 26.8 KB file size indicates a very limited dataset, likely containing summary or key results only.

Provenance

Source

figshare, authored by Koichi Kimura.

Collection Method

Prospective enrollment of SLE patients initiating anifrolumab; immune cell subsets and IFN-associated markers evaluated by flow cytometry.

Time Range

Clinical response assessed at 6 months post-treatment initiation.

Freshness

Last updated March 2026.

Geography

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