Long-term efficacy of transanal local excision versus total mesorectal excision after neoadjuvant treatment for rectal cancer: A meta-analysis
Bibliographic record
Abstract
AIM: The purpose of this meta-analysis is to compare the long-term efficacy of transanal local excision (TLE) versus total mesorectal excision (TME) following neoadjuvant therapy for rectal cancer. METHOD: The Web of Science, Pubmed, Medline, Embase, and the Cochrane Library were systematically searched for correlational research. The Newcastle-Ottawa Scale and the Cochrane risk of bias tool were used to assess the quality of cohort studies (CSs) and randomized controlled trials (RCTs), respectively. Statistically analyzed using RevMan5.4. RESULT: A total of 13 studies, including 3 randomized controlled trials (RCTs) and 10 cohort studies (CSs), involving 1402 patients, were included in the analysis. Of these, 570 patients (40.66%) underwent TLE, while 832 patients (59.34%) underwent TME. In the meta-analysis of CSs, no significant difference was observed between the TLE group and TME group regarding 5-year overall survival (OS) and 5-year disease-free survival (DFS) (P > 0.05). However, the TLE group had a higher rates of local recurrence (LR) [risk ratio (RR) = 1.93, 95%CI (1.18, 3.14), P = 0.008] and a lower rates of 5-years local recurrence-free survival (LRFS) [hazard ratio (HR) = 2.79, 95%CI (1.04, 7.50), P = 0.04] compared to the TME group. In the meta-analysis of RCTs, there was no significant difference observed between the TLE group and TME group in terms of LR, 5-year OS, 5-year DFS, and 5-year disease-specific survival (P > 0.05). CONCLUSION: After undergoing neoadjuvant therapy, TLE may provide comparable 5-year OS and DFS to TME for rectal cancer. However, neoadjuvant therapy followed by TLE may has a higher LR and lower 5-year LRFS compared to neoadjuvant therapy followed by TME, so patients should be carefully selected. Neoadjuvant therapy followed by TLE may be a suitable option for patients who prioritize postoperative quality of life. However, the effectiveness of this approach requires further research to draw a definitive conclusion.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.065 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".