Expectant management versus immediate treatment for low‐grade cervical intraepithelial neoplasia
Bibliographic record
Abstract
BACKGROUND: The optimal management strategy for women with low-grade biopsy-proven cervical intraepithelial neoplasia (CIN) is not clear. Our objective was to compare the effectiveness of regular colposcopic follow-up and treatment of progressive disease only versus immediate treatment. METHODS: Data were accrued between November 2000 and March 2006 for a noninferiority randomized clinical trial of 415 women with biopsy-proven grade 1 CIN from 8 Canadian and 2 Brazilian colposcopy clinics. Subjects were randomly assigned to either undergo immediate treatment with a loop electrical excision procedure (LEEP) or receive regular colposcopic follow-up for 18 months. The primary outcome was progression of disease to CIN 2 to 3 was based on histology obtained during 18 months of follow-up. Treatments were compared using differences of proportion with a 9% noninferiority margin. Analysis was conducted on the basis of intention-to-treat. RESULTS: An initial LEEP was performed on 179 women. Disease progression was found in 32. Easily controlled vaginal bleeding occurred in 16 (8.9%). During follow-up, disease progression was identified in 3 (1.7%) women in the immediate treatment arm and 9 (4.4%) in the colposcopic follow-up arm-a tolerable difference of 2.7% with 1-sided 95% confidence interval (CI) upper limit of 6.0%. Compliance with all 3 follow-up visits was 61% overall, but significantly worse in women ≤30 years of age (P < .05). CONCLUSIONS: The risk of progression to CIN grade 2 or 3 or cancer over 18 months was similar in the 2 treatment groups. In Canada and Brazil, follow-up for 18 months is a reasonable management strategy for women with persistent low-grade cytology who are found to have grade 1 CIN on referral for colposcopy and cervical biopsy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".