Regional Recurrences and Hyams Grade in Esthesioneuroblastoma
Bibliographic record
Abstract
Abstract Objective The aim of this study is to determine if Hyams grade may help predict which patients with esthesioneuroblastoma (ENB) tumors are likely to develop regional recurrences, and to determine the impact of tumor extent on regional failure in ENB patients without evidence of nodal disease at presentation. Design The study was designed as a retrospective review for ENB patients. Settings The study was prepared at tertiary care academic center for ENB patients. Participants Patients with ENB were included in the study. Main Outcome Measures Oncologic outcomes (5-year regional and locoregional control (LRC) and overall survival) in patients with Hyams low grade versus high grade. Oncologic outcomes based on radiographic disease extent. Results A total of 43 patients were included. Total 25 patients (58%) had Hyams low-grade tumor, and 18 (42%) had high-grade tumor. Of the 34 patients without regional disease at presentation, 8 (24%) were treated with elective nodal radiation. There were no statistically significant differences in 5-year regional control in the Hyams low-grade versus high-grade groups (78 vs. 89%; p = 0.4). The 5-year LRC rates in patients with low grade versus high grade were 73 versus 89% (p = 0.6). The 5-year overall survival rates in patients with low-grade versus high-grade tumors were 86 versus 63% (p = 0.1). Radiographic extension of disease into the olfactory groove, olfactory nerve, dura, and periorbita were statistically associated with decreased 5-year overall survival (5-year OS 49 vs. 91% [p = 0.04], 49 vs. 91% [p = 0.04], 44 vs. 92% [p = 0.02], and 44 vs. 80% [p = 0.04], respectively). Conclusion ENBs are associated with a risk of regional failure. The current analysis suggests that Hyams low-grade and high-grade malignancies have comparable rates of early and delayed regional recurrences, although small sample size may limit our conclusions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".