ANIFROLUMAB EFFECTS ON RESPONSE TO INFLUENZA VACCINE IN SLE
Bibliographic record
Abstract
PV244 / #178 Poster Topic: AS24 - SLE-Treatment Background/Purpose Risk for infections in systemic lupus may arise from immunosuppressant treatments or intrinsic immune defects. Disordered interferon signals are a hallmark of SLE. Anifrolumab, which targets the Type I Interferon Receptor (IFNAR), has been found to be safe and effective but, not surprisingly, inhibition of interferon signals is associated with some viral infections and herpes zoster reactivation. We previously reported a relationship between interferon activation and suppressed response to influenza vaccine.[1] The current study examined hemagglutinin inhibition and anti-influenza vaccine antibodies after the administration of flu vaccine in SLE patients on anifrolumab. Methods Between 2020 and 2023, 18 patients with active, moderate to severe SLE received 3 monthly doses of open-label anifrolumab 300 mg IV. Two weeks after dose 1, an FDA-approved quadrivalent, season-specific influenza vaccination was given, In the third season (2022-23), 6 additional SLE patients participated in the protocol without receiving anifrolumab. All patients continued standard-of-care treatment (SOC) (Figure 1). Vaccine response was quantified with a hemagglutinin inhibition assay (HAI) using predominate antigen of active strains each year, and results of an enzyme-linked immunosorbent assay (ELISA) measuring IgG to the relevant seasonal vaccine antigens. Comparison of responses before and after vaccination and in patients who did or did not receive anifrolumab was performed by non-parametric testing. The proportion in each group developing a 2-fold increase in values for each test at week 8 compared to baseline, utilized Fisher’s Exact Test. Confidence intervals were derived with the Exact Clopper-Pearson Method. Figure 1. Study Design Results In a combined analysis merging data from all 3 years, anifrolumab treated patients had no observable deficits in vaccine response by either HAI (Figure 2A) or by antibody levels to the vaccine (Figure 2B). At week 8, geometric mean titers (GMTs) and geometric standard deviations (GSDs) for HAI were anifrolumab: 123.0 (5.39) and control: 69.6 (1.79). GMTs (GSDs) for anti-vaccine antibody concentrations were anifrolumab: 171.8 (3.59) μg/mL and control: 151.7 (2.62). Geometric mean fold rises (GMFRs) (GSDs) of HAI titers from baseline to week 8 were anifrolumab 1.6 (4.52), control: 3.0 (1.46) and GMFRs of anti-influenza IgG were anifrolumab: 1.5 (2.91) and control: 2.8 (3.61). No differences were noted when vaccine responses were evaluated separately for each influenza season. All 6 patients in the control group and 15 (78.9%) of patients in the anifrolumab group developed at least 1 adverse event (AE) during the study. All AEs were mild or moderate in intensity. There were no serious adverse events, deaths, adverse events of special interest, or adverse events leading to discontinuation of treatment. As an additional analysis, the SLEDAI Flare Index (SFI) was evaluated. There were 8 (42%) individual patients in the anifrolumab group and 6 (100%) of patients in the control group who were noted to have a flare, (p=0.0196). All flares were mild/moderate and either mucocutaneous or musculoskeletal. There were 8 total flares in the treatment group (n=19) and 11 (n=6) in the control group. Figure 2. A) Anifrolumab Impact on Hemagglutination Inhibition (HAI) after Influenza Vaccine B) Anifrolumab Impact on Anti-Influenza Virus IgG Concentrations after Influenza Vaccine Conclusions Humoral antibody responses induced by seasonal influenza virus vaccination in adult SLE patients were comparable between patients receiving anifrolumab and those only receiving standard of care, with no evidence to suggest inhibition of vaccine response by anifrolumab. Anifrolumab was well tolerated with no unexpected safety findings in the context of influenza vaccination. References: [1.] Crowe SR. Arthritis Rheum 2011;63(8):2396-406.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".