Relationship between positive margin and residual/recurrence after excision of cervical intraepithelial neoplasia: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: The relationship between endocervical and ectocervical margin status and residual or recurrence after cervical intraepithelial neoplasia (CIN) resection has been controversial. We investigated the relationship between the excision margins and residual/recurrence to assess indicators for the scope of resection and the risk of treatment failure by using meta-analysis. Methods: Literature searches were performed in PubMed, Medline, Embase, Central, Wangfang and CNKI databases. Patients after CIN resection were grouped according to whether there was residual or recurrence, and the differences in exposure factors between the two groups were compared. Or they were grouped by exposure factor, and compare the differences in residual and recurrence rates under different grouping conditions. The observed outcome was postoperative residual or recurrence. The risk of bias in the literature was assessed using the Newcastle-Ottawa Scale (NOS). The chi-square test were used for heterogeneity. Subgroup explored the sources of heterogeneity. Publication bias was assessed using funnel plots and Egger's test. Results: A total of 11 studies were included in this study, 8 studies were at low risk of bias and 3 studies were at high risk of bias. The 11 studies included 3065 patients, 774 patients with positive margins and 2,291 patients with negative margins. The rate of residual/recurrence after excision of CIN in patients with positive margins was significantly higher than in patients with negative margins [odds ratio (OR) =3.99, P<0.00001]. There was no heterogeneity among the studies (P=0.16), with publication bias (P<0.05). The residual/recurrence rate was significantly higher in patients with positive endocervical margins than in patients with negative endocervical margins (OR =2.59, P<0.00001). There was no heterogeneity among studies (P=0.78) and no publication bias (P<0.05). There was no significant difference in residual/recurrence rate between positive and negative ectocervical margins (OR =1.14, P=0.36). There was no heterogeneity among studies (P=0.32) and no publication bias (P<0.05). Conclusions: Positive endocervical margins, but not external cervical margins, are risk factors for residual/recurrence of CIN after resection. Close attention to the status of the endocervical margins is recommended. More aggressive treatment and frequent follow-up are needed for patients with positive endocervical margins.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.031 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".