Outcomes of Conservative Management of High Grade Squamous Intraepithelial Lesions in Young Women
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to determine regression rates of cervical intraepithelial neoplasia (CIN) 2 and 3 in women younger than 24 years, followed conservatively for up to 24 months. MATERIALS AND METHODS: This is a retrospective chart review of colposcopy patients in clinic database based on the following: (1) younger than 24 years at first visit; (2) first visit January 1, 2010, to May 31, 2013, and at least 1 follow-up visit after diagnosis; (3) histologic diagnosis of CIN2+; and (4) optimal conservative management (observation for up to 24 months or to 24 years, whichever occurred first). Patient information and clinical/pathologic data were extracted from charts to examine patient characteristics and treatment outcomes, CIN2+ regression rates, median times to regression for CIN2 versus CIN3 (Kaplan-Meier survival analysis), and predictors of regression (multivariate logistic regression analysis). RESULTS: A total of 154 women met criteria. The most severe histological diagnoses were CIN2 in 99 (64.3%), CIN3 in 51 (33.1%), and adenocarcinoma in situ in 4 (2.6%). Adenocarcinoma in situ was immediately treated. In follow-up, CIN2 regressed to CIN1 or negative in 74 women (74.7%)-median time to regression, 10.8 months. Cervical intraepithelial neoplasia 3 regressed in 11 women (21.6%)-median time to regression not reached (last follow-up censored at 52.7 months). Cervical intraepithelial neoplasia 2 on biopsy, low grade referral Pap, and younger age predicted regression. Overall, 49 women (31.8%) were treated. CONCLUSIONS: Conservative management should continue to be recommended to young women with CIN2. Rigorous retention mechanisms are required to ensure that these women return for follow-up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".