Correlation of PET-CT nodal SUVmax with p16 positivity in oropharyngeal squamous cell carcinoma
Bibliographic record
Abstract
BACKGROUND: The incidence of human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC) has been rising in recent years. Given the clinical impact of HPV/p16 positivity in OPSCC, identifying surrogate markers of this disease early in the diagnostic work-up of these patients could improve patient care. METHODS: Demographic, pathologic, staging and PET-CT data from patients diagnosed with OPSCC from 2009-2014 were obtained from a prospectively collected provincial cancer registry. Tumor HPV/p16 status was correlated to the maximum standard uptake value (SUVmax) of the primary tumor and cervical nodes. Comparisons of means and multinomial regression models were used to determine associations between p16 status and SUVmax. A diagnostic odds ratio was calculated using a cut off value for predicting HPV/p16 positivity based on nodal SUVmax. RESULTS: PET-CT and HPV/p16 data was obtained for 65 patients treated surgically for OPSCC. Significantly higher nodal SUVmax was associated with HPV/p16 positive nodes (SUVmax 10.8 vs 7.9). No significant differences were seen between HPV/p16 positive vs negative primary tumor SUVmax (10.3 vs 13.7). In combination with other clinical parameters, higher nodal SUVmax was highly correlated with HPV/p16 positivity. CONCLUSION: Elevated nodal SUVmax is a significant predictor of HPV/p16 positive disease.
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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 | 0.001 | 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".