Association Between Abatacept Exposure Levels and Infection Occurrence in Patients With Rheumatoid Arthritis: Post Hoc Analysis of the AVERT-2 Study
Bibliographic record
Abstract
OBJECTIVE: To determine whether higher serum exposure during subcutaneous (SC) abatacept (ABA) treatment was associated with an increased infection risk in adult patients with early rheumatoid arthritis (RA). METHODS: Data from Assessing Very Early Rheumatoid Arthritis Treatment-2 (AVERT2; ClinicalTrials.gov: NCT02504268), a randomized, placebo-controlled study in anticitrullinated protein antibody-positive patients with early RA, were analyzed. A post hoc population pharmacokinetic (PPK) analysis was performed. The association between steady-state ABA concentration exposures (ie, steady-state time-averaged serum concentration, steady-state trough serum concentration, steady-state maximum serum concentration) and first infection was evaluated using Kaplan-Meier plots of probability vs time receiving treatment and Cox proportional hazards models. RESULTS: The PK model of SC ABA was defined as a linear 2-compartment model with first-order absorption and elimination, and higher body weight was the only covariate with a clinically relevant effect in the final PPK model. Infections occurred in 330/693 patients treated with ABA + methotrexate (MTX; 47.6%; 11/693 [1.6%] with serious infections) and 134/301 of those treated with ABA placebo + MTX (44.5%; 4/301 [1.3%] with serious infections). Exposure-response analysis demonstrated no exposure relationship for an increased risk of first infection for patients with concomitant use of MTX and glucocorticoids (GCs) during the induction period, baseline GC use, or higher-than-median body weight (> 70 kg) at baseline. CONCLUSION: This exposure-response analysis of AVERT-2 showed no increase in the risk of first infection, regardless of ABA exposure level, in patients with RA treated with SC ABA. Similarly, no effect on the risk of first infection was found for concomitant MTX and GC use in patients with RA treated with SC ABA + MTX.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".