Postcolposcopy Management of Women With Histologically Proven CIN 1
Bibliographic record
Abstract
OBJECTIVES: This study aimed to determine during 36 months of follow-up the (1) clinical outcomes and (2) influence of high-risk human papillomavirus (HPV) status on the risk of progression to cervical intraepithelial neoplasia 2+ (CIN 2+), among women with histologically proven CIN 1. MATERIALS AND METHODS: This is an ad hoc analysis of women with CIN 1 within TOMBOLA, a randomized trial of the management of women with low-grade cervical cytology. Women from the colposcopy arm with CIN 1 confirmed on punch biopsies and managed conservatively by cytology every 6 months in primary care were included. Sociodemographic data and a sample for HPV testing were collected at recruitment. Data on the sample women were extracted to calculate the cumulative incidence of CIN 2+ and the performance characteristics of the baseline HPV test. Detection of CIN 2 or worse (CIN 2+) during follow-up or at exit colposcopy was analyzed. RESULTS: A total of 171 women were included. Their median age was 29 years. Fifty-two percent were high-risk HPV positive, 17% were HPV-16 positive, and 11% were HPV-18 positive. Overall, 21 women (12%) developed CIN 2+, with a median time to detection of 25 months. Factors associated with progression to CIN 2+ were presence of HPV-18 (relative risk = 3.04; 95% CI = 1.09-8.44) and HPV-16 and/or HPV-18 at recruitment (relative risk = 3.98; 95% CI = 1.60-9.90). The sensitivity and specificity of a combined HPV-16/HPV-18 test for the detection of CIN 2+ during 3 years were 58% and 78%, respectively. CONCLUSIONS: Our results suggest that women with confirmed CIN 1 have low rates of progression to high-grade CIN within 3 years. Because the median time to progression was 25 months, conservative management could recommend the next repeat cytology at 2 years.
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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 | 0.004 |
| 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 | 0.001 | 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".