Sublingual Gland Resection in Squamous Cell Carcinoma of the Floor of Mouth: is it Necessary?
Bibliographic record
Abstract
OBJECTIVES: Little evidence exists to guide surgeons in the management of the sublingual glands (SLG) not macroscopically involved by squamous cell carcinoma of the floor of mouth and oral tongue. This study aims to determine the frequency with which the SLG is invaded, to identify variables predicting for SLG invasion and the morbidity associated with it's resection in entirety. STUDY DESIGN: Retrospective cohort study. METHODS: A review of 164 patients treated for oral cavity cancer at a tertiary institution with a large volume of head and neck malignancy was performed. Demographic data, rates of surgical complications and follow up information was recorded. Pathologic review of resected material in this group yielded 134 specimens in the region of the SLG. A detailed analysis of 63 specimens in which the SLG was included was carried out. RESULTS: The median age was 58 years, mean follow up was 2.2 years, and there were 44 males and 19 females. Seventeen cases (27%) demonstrated histopathological SLG invasion. In patients with SLG involvement, this was evident at the time of surgery in 15 patients (88%). Microscopic SLG invasion, without macroscopic evidence at surgery, was present in only 4.2% of patients undergoing SLG resection. Clinical and pathological T stage (p = 0.023 and 0.005) and tumor thickness (p = 0.015) predicted for SLG invasion. Total SLG resection significantly increased the post-operative wound complication rate from 14% in patients without SLG resection to 25% (p = 0.05). CONCLUSION: Total SLG resection in early stage and thin squamous cell carcinoma of the floor of mouth and oral tongue provides minimal oncologic benefit and is associated with increased perioperative morbidity due to neck wound complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".