Immediate and delayed impact of oral glucocorticoid therapy on risk of serious infection in older patients with rheumatoid arthritis: a nested case-control analysis

Abstract

Objectives: To explore the relationship of serious infection risk with current and prior oral glucocorticoid (GC) therapy in elderly patients with rheumatoid arthritis (RA).

Methods: A case-control analysis matched 1947 serious infection cases to five controls, selected from 16207 RA patients aged ≥ 65 between 1985-2003 in Quebec, Canada. Adjusted odds ratios for infection associated with different GC patterns were estimated using conventional models and a weighted cumulative dose (WCD) model.

Results: The WCD model predicted risks better than conventional models. Current and recent GC doses had highest impact on current risk. Doses taken up to 2.5 years ago were also associated with increased risk, albeit to a lesser extent. A current user of 5mg prednisolone had a 30%, 46% or 100% increased risk of serious infection when used continuously for the last 3 months, 6 months or 3 years, respectively, compared to a non-user. The risk associated with 5mg prednisolone taken for the last 3 years was similar to that associated with 30 mg taken for the last month. Discontinuing a two-year course of 10mg prednisolone six months ago halved the risk compared to ongoing use.

Conclusions: GC therapy is associated with infection risk in older patients with RA. The WCD model provided more accurate risk estimates than conventional models. Current and recent doses have greatest impact on infection risk, but the cumulative impact of doses taken in the last 2-3 years still affects risk. Knowing how risk depends on pattern of GC use will contribute to an improved benefit/harm assessment.

Figure 1

Estimated weight function (solid curve) and pointwise 95% bootstrap CI (dotted curves) for the final weighted cumulative dose model of the association between previous oral glucocorticoid exposure and serious infection. The final WCD model used 3 degrees of freedom to model the weight function (see Supplementary Online Materials). Relative risks associated with specific exposure patterns are derived from the weighted sum of past doses, with weights shown on the y-axis. Accordingly, the total impact of continuing exposure (in terms of log OR) during a given time period corresponds to the area under the weight curve (over the corresponding time interval).