Natural History of Genital Warts: Analysis of the Placebo Arm of 2 Randomized Phase III Trials of a Quadrivalent Human Papillomavirus (Types 6, 11, 16, and 18) Vaccine
Bibliographic record
Abstract
BACKGROUND: The placebo arm of human papillomavirus (HPV) vaccine trials helps define the natural history of genital warts (GW). METHODS: Women enrolled in the placebo arm (n = 8800) of 2 randomized trials of a quadrivalent vaccine were examined for the presence of GW for up to 9 visits over approximately 4 years. A comprehensive examination of the perianal area, vulva, and vagina prompted biopsy. Biopsy samples were analyzed by a blinded panel of up to 4 histopathologists and tested for 14 HPV genotypes (6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, and 59) by use of a polymerase chain reaction-based assay. Risk factors for the development of GW were assessed. RESULTS: Women were followed up for an average of 3.6 years (range, 0-4.9 years). Overall, 298 (3.4%) of 8800 participants developed GW related to HPV-6 or HPV-11 (incidence rate, 0.87 cases per 100 person-years-at-risk). In total, 520 distinct lesions were diagnosed as GW. HPV DNA was detected in 472 (90.8%) lesions, with HPV-6 and HPV-11 detected in 447 (86.0%) of these lesions (94.7% of 472 HPV DNA-positive lesions). We found high-risk HPV types in 161 (31.0%) of 520 lesions. Risk factors for HPV-6- and HPV-11-related GW included infection at baseline, acquisition of new sex partners, a higher number of sex partners, and DNA positivity at baseline for a high-risk HPV type. CONCLUSIONS: We confirm the major role played by HPV-6 and HPV-11 in GW, as well as associated risk factors. A vaccine that includes these types of HPV could substantially reduce the overall burden of HPV disease.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".