DRUG LEVELS AND ANTI-DRUG ANTIBODIES OVER 2 YEARS OF BELIMUMAB THERAPY IN SYSTEMIC LUPUS ERYTHEMATOSUS
Bibliographic record
Abstract
PV270 / #457 Poster Topic: AS24 - SLE-Treatment Background/Purpose Although methods to measure belimumab concentrations and anti-drug antibodies (ADA) are available, the clinical significance of drug monitoring and how immunogenic belimumab is in patients with systemic lupus erythematosus (SLE) remain unclear. This study aimed to assess ADA incidence in patients with SLE and to investigate associations between belimumab concentrations and clinical response, serological outcomes, and adverse events. Methods We included 100 patients treated with intravenous belimumab. Clinical data and biological samples were collected at baseline and months 3, 6, 12, and 24. Belimumab levels were determined by quantitative sandwich ELISA, and ADA by an acid-dissociation radioimmunoassay. Clinical activity was evaluated with the SLE disease activity index 2000 (SLEDAI-2K), revised SLE activity measure (SLAM-R), and physician’s global assessment (PhGA). Serological markers included complement C3, C4, and anti-dsDNA antibodies. Adverse events were retrieved from case-report forms and medical charts. We performed cross-sectional analyses using Spearman’s correlation coefficients, and longitudinal analyses using generalized estimating equations. Results Belimumab concentrations varied widely (median: 25.8; IQR: 20.9–43.5 μg/mL), but were stable over time at the group level. Preexisting ADA were detected in 2 patients, but no patient developed ADA during follow-up. Belimumab levels moderately correlated with SLEDAI-2K (ρ: -0.37; p=0.003) and PhGA (ρ: -0.41; p=0.005) at month 6, while longitudinal analyses revealed associations with SLEDAI-2K (β: -0.10; SE: 0.05; p=0.031) and SLAM-R (β: -0.32; SE: 0.13; p=0.014). Despite moderate correlations between belimumab levels and serological markers at month 6, there were no associations in longitudinal analyses. There was no relationship between belimumab levels and adverse events. Conclusions Belimumab yielded no immunogenicity. Belimumab levels were associated with clinical activity but not with serological activity or adverse events.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".