The Platform Trial In COVID-19 priming and BOOsting (PICOBOO): The immunogenicity, reactogenicity, and safety of licensed COVID-19 vaccinations administered as a second booster in BNT162b2 primed individuals aged 18-<50 and 50-<70 years old
Bibliographic record
Abstract
OBJECTIVES: PICOBOO is a randomised, adaptive trial evaluating the immunogenicity, reactogenicity, and safety of COVID-19 booster strategies. Here, we present data for second boosters among individuals aged 18-<50 and 50-<70 years old primed with BNT162b2 until Day (D) 84. METHODS: concentration of anti-spike Ig Total was summarised as the geometric mean concentration (GMC). Reactogenicity and safety outcomes were captured. RESULTS: Between Mar 2022 and Aug 2023, 743 participants were recruited to the trial and had D28 samples available. Of these, 120 and 103 belonged to the 18-<50 y and 50-<70 y strata, respectively. The mean adjusted GMCs (95% credible intervals) peaked at D28; these were 41 262 (31 611, 51 105), 45 585 (34 194, 57 441) and 25 281 (20 021, 31 234) U/mL in the 18-<50 y stratum and 30 753 (25 071, 36 704), 35 132 (27 523, 42 239) and 17 322 (13 983, 20 641) U/mL in the 50-<70 y stratum following BNT162b2, mRNA-1273 and NVX-CoV2373, respectively. Limited neutralisation against Omicron subvariants was found following boosting with all vaccines. There were 4 possibly or probably-related adverse events in the 18-<50 y stratum and 5 events in the 50-<70 y stratum, and severe reactogenicity events were <10% and <11% in these strata, respectively. CONCLUSIONS: Vaccines targeting Ancestral virus elicited boosted antibody responses to Ancestral virus but minimal neutralising antibody against Omicron variants.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".