Extra-Nodal Lymphomas of the Head and Neck and Oral Cavity: A Retrospective Study
Bibliographic record
Abstract
Disease Overview: Lymphomas, both Hodgkin’s and non-Hodgkin’s lymphomas, are one of the most common cancers in the head and neck area. The extra-nodal variant of lymphoma is rare, but it is the most common non-Hodgkin’s lymphoma (ENHL). Furthermore, it is difficult to diagnose due to its non-specific clinical and radiological features, which can mimic other benign or malignant clinical manifestations. The study: This retrospective study involved 72 patients affected by head and neck ENHL in the period between 2003 and 2017. All patients underwent a diagnostic-therapeutic procedure according to the guidelines, and a 5-year follow-up. Based on the location of the swelling at the time of diagnosis, patients were divided into two groups: oral and non-oral ENHLs. Statistical analysis was performed using Kaplan–Meier analysis with the log-rank test. In addition, Fisher’s exact test was applied to the two groups to evaluate and compare variances (the acceptable significance level was set at p < 0.05). Conclusion: ENHL with oral localization is much more aggressive than ENHL with non-oral localization, with a death rate of 40% (versus 4.76 for the non-oral one). In fact, between the two groups, there is a statistically significant difference in mortality, with a p-value of 0.0001 and 0.0002, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".