Positive Endocervical Margins at Conization: Repeat Conization or Colposcopic Follow-Up? A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: The presence of residual cervical lesions was evaluated in patients submitted to repeat conization due to a finding of positive endocervical margins in a previous loop electrosurgical excision procedure (LEEP) specimen. In addition, the correlation between the presence of a residual lesion and risk factors for cervical cancer, and the use of repeat conization as first-choice treatment were analyzed. METHODS: This retrospective study included 44 patients submitted to repeat cervical conization or total hysterectomy following a finding of affected endocervical margins in LEEP specimens. The risk factors analyzed in relation to the presence of residual lesions were age, smoking, cone depth, glandular involvement and the histopathology findings of cervical intraepithelial neoplasia (CIN) 1, CIN 2 or CIN 3/carcinoma in situ. The Chi-square test and the Mann-Whitney t-test were used, with significance defined at P < 0.05. RESULTS: Residual lesions were found in 23/44 patients (52.3%), with 3/23 cases (13.0%) being compatible with invasive squamous cell carcinoma. Of the 23 patients, six (26.1%) were submitted to total hysterectomy, with one case being compatible with a moderately differentiated invasive squamous cell carcinoma. Two patients with a histopathology finding of CIN 3/carcinoma in situ in the previous LEEP specimen were diagnosed with invasive squamous cell carcinoma in the repeat conization specimen. Residual lesions were not significantly associated with the risk factors evaluated. CONCLUSIONS: In view of the high frequency of residual disease found when positive endocervical margins were found in LEEP specimens, the indication for repeat cervical conization rather than colposcopic follow-up is viable and justified. Indeed, since the presence of a residual lesion and its progression in the cervical canal are more difficult to screen and control, patients unable to comply with regular colposcopic follow-up could benefit from repeat conization when trying to avoid a potentially negative outcome.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".