The Biomarkers of Lupus Disease Study: A Bold Approach May Mitigate Interference of Background Immunosuppressants in Clinical Trials

狼疮疾病生物标志物研究:一种大胆的方法或可减轻临床试验中背景免疫抑制剂的干扰

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Abstract

OBJECTIVE: Molecular medicine raised expectations for strategically targeted biologic agents in systemic lupus erythematosus (SLE), but clinical trial results have been disappointing and difficult to interpret. Most studies add investigational agents to various, often effective, standard therapy immunosuppressants used at baseline, with unknown treatment interactions. Eliminating polypharmacy in trials of active lupus remains controversial. We undertook the Biomarkers of Lupus Disease study to test withdrawal of immunosuppressants as a novel approach to rendering SLE trials interpretable. METHODS: In 41 patients with active, non-organ-threatening SLE flare (group A), temporary steroids were given while background immunosuppressants were withdrawn. Time to loss of disease suppression (time to disease flare) and safety were evaluated; standard therapy was immediately resumed when symptoms recurred. Immunologic impacts of standard therapy were studied at baseline by multiplex assay, enzyme-linked immunosorbent assay, and messenger RNA array in group A patients plus 62 additional patients donating a single sample (group B). RESULTS: Patients with lower or higher baseline disease activity had median times to flare of 71 or 45 days, respectively; 40 of 41 patients (98%) had disease flares by 6 months. All flares were treated and resolved within 6 weeks. No serious adverse events occurred from flare or infection. Type I interferon (IFN), Th17, and B lymphocyte stimulator pathways tracked together. Baseline immunosuppressants had distinct impacts on Th17 and B lymphocyte stimulator, depending on IFN signature. CONCLUSION: Trials in active, non-organ-threatening SLE can safely withdraw background treatments if patients who have disease flares are designated nonresponders and returned to standard therapy. Immunologic effects of standard therapy vary between IFN-defined subsets. These findings provide a strategy for minimizing or optimizing treatment combinations in lupus trials and clinical care.

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