Prevalence of Anti-infliximab Antibodies and Their Associated Co-factors in Children with Refractory Arthritis and/or Uveitis: A Retrospective Longitudinal Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Infliximab (IFX) is a monoclonal tumor necrosis factor-α-inhibiting antibody used in children with refractory arthritis and uveitis. Immunogenicity is associated with a lack of clinical response and infusion reactions in adults; data on immunogenicity in children treated with IFX for rheumatic diseases are scarce. We aimed to describe the prevalence of anti-IFX antibodies and determine co-factors associated with anti-IFX antibodies in children with inflammatory rheumatic and ocular diseases. METHODS: Consecutive children treated between August 2009 and August 2012 with IFX at our department were included. Blood samples were collected every 6 months before IFX infusion and tested for anti-IFX antibodies by radioimmunoassay. Patients' charts were retrospectively reviewed for clinical features and analyzed for associations with anti-IFX antibodies. RESULTS: Anti-IFX antibodies occurred in 14/62 children (23%) and 32/253 blood samples (12.6%) after a mean treatment time of 1084 days (range 73-3498). Infusion reactions occurred in 10/62 (16%) children during the treatment period. With continuation of IFX, anti-IFX antibodies disappeared in 7/14 children. In the bivariate analysis, the occurrence of anti-IFX antibodies was associated with younger age at IFX treatment start (mean age 7.01 vs 9.88 yrs, p = 0.003) and infusion reactions (OR 15.0), while uveitis as treatment indication was protective against development of anti-IFX antibodies (OR 0.17), likely because of higher IFX doses. In the multivariate logistic regression, all 3 covariates remained highly significant. CONCLUSION: Anti-IFX antibodies occurred commonly at any time during IFX treatment. Anti-IFX antibodies were associated with younger age at IFX start, infusion reactions, and arthritis as treatment indication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".