Human Papillomavirus Intermittence and Risk Factors Associated With First Detections and Redetections in the Ludwig-McGill Cohort Study of Adult Women
Bibliographic record
Abstract
BACKGROUND: We assessed the incidence and risk factors for first detection and redetection with the same human papillomavirus (HPV) genotype, and prevalence of cytological lesions during HPV redetections. METHODS: The Ludwig-McGill cohort study followed women aged 18-60 years from São Paulo, Brazil in 1993-1997 for up to 10 years. Women provided cervical samples for cytology testing and HPV DNA testing at each visit. A redetection was defined as a recurring genotype-specific HPV positive result after 1 or more intervening negative visits. Predictors of genotype-specific redetection were assessed using adjusted hazard ratios (aHR) with Cox regression modeling. RESULTS: In total, 2184 women contributed 2368 incident HPV genotype-specific first detections and 308 genotype-specific redetections over a median follow-up of 6.5 years. The cumulative incidence of redetection with the same genotype was 6.6% at 1 year and 14.8% at 5 years after the loss of positivity of the first detection. Neither age (aHR 0.90; 95% confidence interval [CI], .54-1.47 for ≥45 years vs < 25 years) nor new sexual partner acquisition (aHR 0.98; 95% CI, .70-1.35) were statistically associated with genotype-specific redetection. High-grade squamous intraepithelial lesion prevalence was similar during first HPV detections (2.9%) and redetection (3.2%). CONCLUSIONS: Our findings suggest many HPV redetections were likely reactivations of latent recurring infections.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".