Transoral laser microsurgery for the treatment of oropharyngeal cancer: The Dalhousie University experience
Bibliographic record
Abstract
OBJECTIVE: The optimal treatment strategy for oropharyngeal squamous cell carcinoma is highly debated. However, growing evidence supports the use of minimally invasive techniques, such as transoral laser microsurgery (TLM), as a first-line treatment modality for these carcinomas. The purpose of our study was to assess the efficacy and safety of TLM for the treatment of primary and recurrent oropharyngeal carcinomas. METHODS: All patients with oropharyngeal carcinoma undergoing TLM at the QEII Health Sciences Centre in Halifax, Nova Scotia were identified within a prospective database monitoring TLM outcomes. Kaplan-Meier survival analysis was used to evaluate the following end points at 36 months: local control (LC), disease-specific survival (DSS), and disease-free survival (DFS). Safety endpoints included complications following surgery and long term morbidity related to TLM. RESULTS: Between 2003 and 2014, 39 patients with oropharyngeal carcinoma underwent TLM resection. Twenty-eight (72%) patients had primary carcinoma, nine (23%) were radiation/chemoradiation (RT/CRT) failures, and two (5%) had second primaries following previous RT/CRT. Three patients had stage I disease, 8 stage II, 5 stage III, and 23 stage IV disease. HPV status was available for 26 patients, of which 23 (88%) had HPV positive disease. Kaplan-Meier estimates of 36-month LC, DSS, and DFS for primary oropharyngeal carcinomas were 85.5% (SE 10.6%), 85.7% (SE 13.2%) and 77.7% (SE 12.5%) respectively. Thirty-six-month outcomes for RT/CRT failures were 66.76% (SE 15.7%) for LC and 55.6% (SE 16.6%) for DSS and DFS. Three patients developed complications following surgery. CONCLUSIONS: Observed 36-month efficacy and safety outcomes support the use of TLM for the treatment of primary and recurrent oropharyngeal carcinoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".