Determinants of Acquisition and Clearance of Human Papillomavirus Infection in Previously Unexposed Young Women
Bibliographic record
Abstract
BACKGROUND: Global variation in human papillomavirus (HPV) prevalence and persistence may be explained by differences in risk factors, such as sexual activity, oral contraceptive use, and behavioral factors. We evaluated determinants of acquisition and clearance of HPV infection among young women previously unexposed to HPV. METHODS: Five hundred thirty-four women aged 15 to 25 years who were cytology and HPV DNA negative, and seronegative for anti-HPV-16/18 antibodies, were recruited (July 2000-September 2001) from study centers in Brazil, the United States, and Canada (NCT00689741/NCT00120848). They were followed up for 76 months. Cervical samples were HPV genotyped via polymerase chain reaction. We used multivariable (forward stepwise, P = 0.15) Cox proportional hazards regression to estimate rate ratios (RR) and 95% confidence intervals (CI), separately according to length of follow-up time. RESULTS: On short-term follow-up (0-27 months), 257 (48%; 8535.80 person-months; incidence rate = 30.11; 95% CI, 26.64-34.02) incident HPV infections were detected. Marital status, lifetime number of sex partners, history of any sexually transmitted disease, and occasional use of oral contraceptives were strongly associated with acquisition of any HPV. Having 2 or more lifetime sex partners (RR, 2.03; 95% CI, 1.37-3.02) and a history of any sexually transmitted disease (RR, 1.98; 95% CI, 1.19-3.29) were the most important determinants of high-risk HPV (hrHPV) incidence. During the entire follow-up (0-76 months), an increased hrHPV clearance was found among women in North America (RR, 1.38; 95% CI, 1.08-1.78) and black women (RR, 1.64; 95% CI, 1.04-2.60). Greater number of lifetime partners was associated with reduced clearance rates for any HPV (RR, 0.65; 95% CI, 0.43-0.98). CONCLUSIONS: We identified variation in risk of HPV acquisition and clearance among women unexposed to HPV at baseline.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".