Recurrence morbidity of olfactory neuroblastoma
Bibliographic record
Abstract
BACKGROUND: With modern treatment paradigms, olfactory neuroblastoma (ONB) has favorable overall survival (OS); however, the incidence of recurrence remains high. The primary aims of this study were to delineate the prognosis of recurrence of ONB and explore how recurrence subsites are associated with OS, disease-specific survival (DSS), and further recurrence. METHODS: A retrospective chart review of ONB cases from nine academic centers between 2005 and 2021 was completed. Tumor characteristics, recurrence subsites, timelines to recurrence, additional recurrences, and survival estimates were determined using descriptive and time-to-event analyses. RESULTS: A final cohort of 233 patients was identified, with 70 (30.0%) patients recurring within 50.4 (standard deviation ±40.9) months of diagnosis on average, consisting of local (50%), neck (36%), intracranial (9%), and distant (6%) recurrence. Compared with subjects without recurrence, patients with recurrence had significantly different primary American Joint Committee on Cancer T stage (p < 0.001), overall stage (p < 0.001), and modified Kadish scores (p < 0.001). Histopathology identified that dural involvement and positive margins were significantly greater in recurrent cases. First recurrence was significantly associated with worse 5-year DSS (hazard ratio = 5.62; p = 0.003), and subjects with neck or local recurrence had a significantly better DSS compared to intracranial or distant recurrence. CONCLUSIONS: Recurrent cases of ONB have significantly different stages and preoperative imaging factors. Patients with local or neck recurrence, however, have better DSS than those with intracranial or distant recurrence, independent of initial tumor stage or Hyams grade. Identifying specific factors that confer an increased risk of recurrence and DSS is important for patient counseling in addition to surveillance planning.
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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 | 0.003 |
| 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) | 0.001 | 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".