Metabolic Tumor Volume as a Prognostic Factor for Oral Cavity Cancer Treated with Primary Surgery
Bibliographic record
Abstract
Objectives: Metabolic tumor volume (MTV) obtained from pretreatment 18F‐fluorodeoxydeglucose positron emission tomography with computed tomography (PET‐CT) has been validated as an independent predictive factor of outcomes in head and neck cancer patients (HNC) treated with primary chemoradiotherapy (CRT). However, its role in patients treated with primary surgery has not yet been studied. The aim of the study was to evaluate the prognostic value of MTV in patients treated with primary surgery for oral cavity squamous cell carcinoma (OCSCC). Methods: Demographic and survival data were obtained from patients diagnosed with OCSCC from 2008 to 2012 in Alberta, Canada. All patients included in the study had positron emission tomography–computed tomography (PET‐CT) scan before curative surgical resection. MTV and maximum standardized uptake value (SUVmax) was delineated from pretreatment PET‐CT scans using Segami Oasis software (Columbus, OH). Results: A total of 80 patients were analyzed using SPSS (SPSS Inc, Chicago, IL). Five‐year overall, disease‐specific, and disease‐free survival using Kaplan‐Meier curves were 72%, 79%, and 78% respectively. An increase in MTV of 17.5 mL (difference between the 75th and 25th percentile) was associated with a 1.9‐fold increase in risk of disease recurrence ( P <. 001) and a 2.0‐fold increase in the risk of death ( P <. 05). SUVmax was not associated with either outcome. Cox‐Regression analysis showed MTV predicted overall (hazard ratio [HR] = 1.22; P <. 0001), disease‐specific (HR = 1.62; P <. 0001), and disease‐free (HR = 1.97; P <. 0001) survival. Conclusions: This study shows that MTV is an adverse prognostic factor for death and disease recurrence in OCSCC treated with primary surgery.
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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) | 0.001 | 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".