Clinicopathological and prognostic implications of genetic alterations in oral cancers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study evaluated the clinicopathological and prognostic implications of genetic alterations characterizing oral squamous cell carcinoma(OSCC). Comparative genomic hybridization(CGH) was used to identify chromosomal alterations present in primary OSCCs obtained from 97 pateints. In this population, tobacco use was a significant risk factor for OSCC. By contrast, all 97 of our samples are negative for human papillomavirus (HPV) DNA integration, which is another known risk factor for OSCC in certain populations. Results of the Fisher's exact test followed by Benjamini-Hochberg correction for multiple testing, showed a correlation of 7p gain and 8p loss with node-positive OSCC (p≤0.04 for both genetic alterations) and association of 11q13 gain with high-grade OSCC (p≤0.05). Univariate Cox-proportional hazard models, also corrected for multiple testing, showed significant association of 11q13 gain and 18q loss with decreased survival (p≤0.05). These findings were supported by multivariate analysis which revealed that 11q13 gain and 18q loss together serve as a strong bivariate predictor of poor prognosis. In conclusion, our study has identified genetic alterations that correlate significantly with nodal status, grade, and poor survival status of OSCC. These potential biomarkers may aid the current TNM system for better prediction of clinical outcome.
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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 it