Lowering Expectations: Glucocorticoid Tapering Among Veterans With Rheumatoid Arthritis Achieving Low Disease Activity on Stable Biologic Therapy

ACR Open Rheumatol. 2023 Sep;5(9):437-442. doi: 10.1002/acr2.11584. Epub 2023 Jul 25.

Abstract

Objective: In the Steroid EliMination In Rheumatoid Arthritis (SEMIRA) trial, 65% of patients with rheumatoid arthritis (RA) in low disease activity (LDA) on stable biologic therapy successfully tapered glucocorticoids. We aimed to evaluate real-world rates of glucocorticoid tapering among similar patients in the Veterans Affairs Rheumatoid Arthritis registry.

Methods: Within a multicenter, prospective RA cohort, we used registry data and linked pharmacy claims from 2003 to 2021 to identify chronic prednisone users achieving LDA after initiating a new biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD). We defined the index date as first LDA occurring 60 to 180 days after b/tsDMARD initiation. The primary outcome of successful tapering, assessed at day 180 after LDA, required a 30-day averaged prednisone dose both less than or equal to 5mg/day and at least 50% lower than at the index date. The secondary outcome was discontinuation, defined as a prednisone dose of 0 mg/day at days 180 through 210. We used univariate statistics to compare patient characteristics by fulfillment of the primary outcome.

Results: We evaluated 100 b/tsDMARD courses among 95 patients. Fifty-four courses resulted in successful tapering; 33 resulted in discontinuation. Positive rheumatoid factor, higher erythrocyte sedimentation rate, more background DMARDs, shorter time from b/tsDMARD initiation to LDA, and higher glucocorticoid dose 30 days before LDA were associated with greater likelihood of successful tapering.

Conclusion: In a real-world RA cohort of chronic glucocorticoid users in LDA, half successfully tapered and a third discontinued prednisone within 6 months of initiating a new b/tsDMARD. Claims-based algorithms of glucocorticoid tapering and discontinuation may be useful to evaluate predictors of tapering in administrative data sets.