Survival outcomes of marijuana users in p16 positive oropharynx cancer patients
Bibliographic record
Abstract
BACKGROUND: Oropharynx squamous cell carcinoma (OPSCC) has become the predominant subsite for head and neck mucosal cancers (HNC) due to the rise of human papillomavirus (HPV) related disease. Previous studies have suggested an association between marijuana use and HPV-related OPSCC. Despite this, no study has examined the potential relationship between marijuana use and survival in this subset of patients. OBJECTIVE: To examine the survival outcomes of HPV-related OPSCC patients in marijuana users. METHODS: Patients who were marijuana users were identified from a prospectively collected database of HNC patients from January 2011 to 2015. A physical review of clinic records was undertaken to extract relevant patient, tumor, treatment, follow-up, as well as survival data. Patients greater than 17 years of age with pathologically proven p16 positive OPSCC were included. They were then case-matched in a 1-to-1 basis to patients who were non-marijuana users based on age, gender, and cTNM staging. RESULTS: Forty-Seven patients met inclusion criteria within each group. Univariate logistic regression analysis showed that age, gender, and cT-Stage were predictive of disease recurrence within both groups (p < 0.05). However, cN-stage, treatment modality, tumor subsite, tobacco use, and tobacco dose were not (p > 0.05). There was no statistically significant difference between marijuana and non-marijuana user groups in 5-year (p = 0.400) overall survival, disease-specific (p = 0.993), disease-free (p = 0.404), and metastasis-free survival (p = 0.384). CONCLUSIONS: No survival difference is found between HPV-related OPSCC marijuana users and non-users. This finding has implications for both de-escalation regimes and the use of cannabis as a therapeutic agent.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".