Human Papillomavirus 16 (HPV 16) and HPV 18 Antibody Responses Measured by Pseudovirus Neutralization and Competitive Luminex Assays in a Two- versus Three-Dose HPV Vaccine Trial
Bibliographic record
Abstract
Human papillomavirus 16 (HPV 16) and HPV 18 antibody responses in a 2- versus 3-dose HPV vaccine (Gardasil) trial were measured by a pseudovirus neutralizing antibody (PsV NAb) assay and by the Merck competitive Luminex immunoassay (cLIA). Eight hundred twenty-four female subjects assigned to three dosing regimens (group 1, 9 to 13 years old; 2 doses, months 0 and 6 [n = 259]; group 2, 9 to 13 years old; 3 doses, months 0, 2, and 6 [n = 260]; group 3, 16 to 26 years old; 3 doses, months 0, 2, and 6 [n = 305]) had postvaccine responses assessed 1 month after the last dose. Of 791 subjects with baseline and 7-month sera, 15 (1.9%) and 9 (1.1%) were baseline seropositive for HPV 16 and HPV 18, respectively. All baseline-seronegative vaccinees seroconverted to both HPV 16 and HPV 18. Mean anti-HPV 16 levels were similar for groups 1 and 2 (for PsV NAb, P = 0.675; for cLIA, P = 0.874), and levels for both groups 1 and 2 were approximately 2-fold higher than that for group 3 (for PsV NAb and cLIA, P < 0.001). Mean anti-HPV 18 levels were approximately 1.4-fold lower in group 1 than in group 2 (for PsV, NAb P = 0.013; for cLIA, P = 0.001), and levels for both groups 1 and 2 were approximately 2.0- to 2.5-fold higher than that for group 3 (for PsV NAb and cLIA, P < 0.001). Pearson correlation coefficients for the assays were 0.672 for HPV 16 and 0.905 for HPV 18. Most of the discordant results were observed at lower cLIA signals. These results suggest that the PsV NAb assay could be a suitable alternative to cLIA for the measurement of postvaccine antibody responses.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.001 | 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".