Margin Sampling and Survival Outcomes in Oral Cavity and p16‐Positive Oropharyngeal Squamous Cell Carcinoma
Bibliographic record
Abstract
Objective To compare the association of margin sampling technique on survival outcomes in surgically treated cT1‐2 oral cavity and oropharyngeal squamous cell carcinoma. Study Design A prospective longitudinal cohort study. Setting Tertiary care academic teaching hospital in Halifax, Nova Scotia. Methods All cases of surgically treated cT1‐2 oral cavity and oropharyngeal cancer undergoing specimen‐oriented margin analysis between January 1, 2017, and December 31, 2018 were analyzed. The specimen‐oriented cohort was compared with a cohort of patients from January 1, 2009, to December 31, 2014, where a defect‐oriented margin sampling protocol was used. Kaplan‐Meier survival curves were used to estimate 2‐year overall survival, disease‐specific survival, local control, and recurrence‐free survival rates in oral cavity and p16‐positive oropharyngeal squamous cell carcinoma. Cox proportional hazards models were used to assess the effect of margin sampling method on disease‐specific survival and local control. Results There was no significant association between margin sampling technique and 2‐year survival outcomes for surgically treated cT1‐2 oral cavity and oropharyngeal squamous cell carcinoma. In the multivariate Cox proportional hazard model, the hazard ratio (HR) of specimen‐oriented sampling was not significantly different for disease‐specific survival (HR, 1.32; 95% CI, 0.3032‐5.727; P =. 713) or local control (HR, 0.4087; 95% CI, 0.0795‐2.099; P =. 284). Conclusion Intraoperative margin sampling method was not associated with a significant change in 2‐year survival outcomes. Despite no effect on survival outcomes, implementation of a specimen‐oriented sampling method has potential for cost avoidance by decreasing the number of re‐resections for positive or close 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".