Clinical outcome of salvage surgery in patients with recurrent oral cavity cancer: A systematic review and meta‐analysis
Bibliographic record
Abstract
This systematic review and meta-analysis investigated the impact of salvage surgery on 5-year overall survival (OS) and prognostic factors in recurrent oral cavity cancer (rOCC) patients. Relevant literature before May 2022 was reviewed, including retrospective cohort studies and observational studies comparing salvage surgery to other treatments. Risk-of-bias assessments were conducted using the Newcastle-Ottawa scale. Statistical and subgroup analyses assessed the impact of salvage surgery on 5-year OS and prognostic factors. 3036 documents were initially retrieved, with 14 retrospective cohort studies (2069 participants) included. Meta-analysis of 5-year OS in salvage surgery patients yielded a rate of 43.0%. Subgroup analysis showed higher OS in Asians (49.9% vs. 36.9%, p = 0.003) and late-relapse (63.8% vs. 30.0%, p = 0.004) groups. Prognostic factors revealed hazards associated with nodal recurrence, extranodal extension, and perineural invasion. Salvage surgery is a viable option for rOCC patients, showing favorable 5-year OS outcomes. Low publication bias enhances study reliability, but its single-arm design limits conclusions on salvage surgery superiority over other treatments.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".