Secukinumab Immunogenicity over 52 Weeks in Patients with Psoriatic Arthritis and Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: Secukinumab, a fully human antiinterleukin 17A monoclonal antibody, is efficacious for the treatment of psoriatic arthritis (PsA) and ankylosing spondylitis (AS). This study examined the immunogenicity of secukinumab in patients with PsA and AS exposed to secukinumab for up to 52 weeks. METHODS: Antibody bridging assays were used to assess the immunogenicity of secukinumab in patients with PsA [FUTURE 1-3 studies, and AS (MEASURE 1-4 studies)]. Evaluations were at baseline and at weeks 16 (AS only), 24, and 52. Treatment-emergent antidrug antibodies (TE-ADA) were defined as a positive ADA signal in ≥ 1 posttreatment sample in patients negative at baseline. Positive samples were analyzed for drug-neutralizing potential, and effect of TE-ADA on secukinumab pharmacokinetics, immunogenicity-related adverse events (AE), and efficacy through Week 52 were assessed. RESULTS: Of 1414 treated PsA and 1164 treated AS patients with samples available for immunogenicity evaluation, 5 (0.35%) and 8 (0.69%), respectively, developed TE-ADA. All but 1 PsA patient were biologic-naive; two of the 5 PsA and one of the 8 AS patients received concomitant methotrexate, and two of the 8 AS patients received concomitant sulfasalazine. Associations between TE-ADA and secukinumab dose, frequency, or administration mode were not observed. Other than one PsA patient, all TE-ADA were non-neutralizing. No TE-ADA were associated with any AE. All TE-ADA were associated with normal secukinumab pharmacokinetics and none were associated with loss of secukinumab efficacy. CONCLUSION: Secukinumab treatment was associated with a low (< 1%) incidence of immunogenicity in patients with PsA or AS. (clinicaltrials.gov: NCT01392326; NCT01752634; NCT01989468; NCT01358175; NCT01649375; NCT02008916; NCT02159053).
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".