The association of tumor diameter with lymph node metastasis and recurrence in patients with endometrial cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Tumor diameter (TD)/original lesion area has been reported to have a certain predictive effect on lymph node metastasis (LNM) and recurrence of endometrial cancer (EC) patients, but there is still controversy about their relationship. Therefore, we conducted a meta-analysis to provide reference for clinical management and follow-up studies of patients with EC. Methods: The databases of PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP, and Wanfang were searched, from inception to 27 October 2022, for studies regarding the association of TD with LNM risk and recurrence rate in EC. The search strategy was developed using a combination of free terms and medical subject headings (MeSH). Stata 15.0 was used to conduct the statistical analysis. Odds ratio (OR) with the 95% confidence interval (CI) were calculated to evaluate the association of TD and the risk of LNM and recurrence in EC patients. The OR value obtained from the multivariate analysis is first extracted; the results of univariate analysis were extracted for articles without the results of multivariate analysis. Newcastle-Ottawa Scale (NOS) assessed the quality of the included articles, publication bias was evaluated by Egger's test with funnel plots. Results: There was a total of 69 studies 123,383 EC patients included. Meta-analysis showed higher LNM risk in EC patients with the TD >2 cm, which was 2.88 times higher than that in those with ≤2 cm, and the difference was statistically significant (OR =2.88; 95% CI: 2.12-3.89; P<0.001), publication bias had no effect on the results. The risk of recurrence in EC patients with a TD >2 cm was 2.45 times higher than that in those with ≤2 cm (OR =2.45; 95% CI: 1.73-3.48; P<0.001), publication bias exerted influence over the results. Conclusions: TD is associated with LNM and recurrence in patients with EC. Therefore, TD should be considered in the scope of surgery and adjuvant therapy.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.007 | 0.008 |
| 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".