High-Level Immunogenicity Is Achieved Vaccine With Adjuvanted Pandemic H1N1<sub>2009</sub> and Improved With Booster Dosing in a Randomized Trial of HIV-Infected Adults
Bibliographic record
Abstract
Background: More severe influenza disease and poor vaccine immunogenicity in HIV-infected patients necessitate improved immunization strategies to maximize vaccine efficacy. Methods: A phase III, randomized trial was conducted at 4 Cana-dian sites. Two dosing strategies (standard dose vs standard dose plus booster on day 21) were assessed in HIV patients aged 20 to 59 years during the H1N12009 pandemic. A single antigen, inactivated split adjuvanted (AS03A) influenza vaccine (Arepanrix) was utilized. Serum hemagglutination inhibition (HAI) titres were assessed at days 21 and 42 and at month 6. Results: 150 participants received at least one injection. Baseline parameters were similar between groups: 83% male, 85% on HAART, median CD4 = 519 cells/mm3, 84% with HIV RNA < 50 copies/mL. At day 21, seroprotection (HAI ≥1:40) was achieved in 80% (95% CI, 70-89) of participants. Seroconversion occurred in 74% (63–85). Seroprotection and seroconversion were further improved in those randomized to booster dosing: day 42, 94% (85–98) versus 73% (60-83) (P < .01) and 86% (75–93) versus 66% (5–77) (P = .01). Seroprotec-tion was retained in 40% (28–54) of recipients at month 6 with trends toward greater retention of immunity in booster recipients. Conclusion: High-level immunogenicity was achieved with a single dose of this adjuvanted vaccine. Immunogenicity was further improved with booster dosing. Use of this adjuvanted vaccine and booster represent an important approach to increasing immunogenicity in this vaccine hypo-responsive population.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".