Treatment benefit or survival of the fittest: what drives the time-dependent decrease in serious infection rates under TNF inhibition and what does this imply for the individual patient?. Issue 11 (25th July 2011) - Strangfeld, A; Eveslage, M; Schneider, M; Bergerhausen, H J; Klopsch, T; Zink, A; Listing, J
Abstract : Objective: To examine the risk of serious infection conveyed by tumour necrosis factor α (TNFα) inhibitors in the treatment of rheumatoid arthritis (RA). Methods: Data from patients with RA enrolled in the German biologics register RABBIT were used for analysis. Baseline patient characteristics, time-varying risk factors (treatment changes, functional capacity) and selection processes caused by dropout, death or switching to non-anti-TNF treatment were taken into account to estimate the adjusted incidence rate ratios (IRRadj ) of serious infection during treatment with TNF inhibitors compared with non-biological disease-modifying antirheumatic drug treatment. Results: Data were available on 5044 patients, in whom 392 serious infections occurred. The crude rates of serious infections in patients treated with TNF inhibitors declined over the first 3 years of observation (from 4.8 to 2.2/100 patient-years). This decline was driven by (1) treatment termination or loss to follow-up in patients at increased risk and (2) a risk reduction through decreasing glucocorticoid doses and improvement in function. Adjusted for selection processes and time-varying risk factors, the following parameters assessed at baseline (age, chronic diseases) or at follow-up prior to the infection were significantly associated with an increased risk: age >60 years, chronic lung or renal disease, low functional capacity, history of serious infections, treatment with glucocorticoids (7.5–14 mg/day, IRRadj 2.1 (95% CI 1.4 to 3.2); ≥15 mg/day, IRRadj 4.7 (95% CI 2.4 to 9.4)) and treatment with TNFα inhibitors (IRRadj 1.8 (95% CI 1.2 to 2.7)). Conclusion: Reasons for the decline in infection rates observed at the group level were identified. The results enable expected infection rates to be calculated in individual patients based on their risk profiles.