Olfactory Neuroblastoma: A Multicenter Survival Analysis and Application of a Staging Modification Incorporating Hyam's Grade
Bibliographic record
Abstract
Background: Olfactory neuroblastoma (ONB) is a rare sinonasal malignancy with favorable survival and frequent delayed recurrence. Current staging systems including the Kadish, modified Kadish (mKadish), and Dulguerov systems poorly delineate locally advanced tumors and do not incorporate histologic grade. The two primary aims of this multi-institutional study were to 1) examine the clinical covariates associated with survival and recurrence of ONB in the modern era and 2) incorporate Hyam's tumor grade into existing staging systems and to assess its ability to predict survival and recurrence. Methods: Data from nine North American academic centers were retrospectively reviewed between 2005 and 2021. Patient demographics, tumor staging (original Kadish, modified Kadish [mKadish], Dulguerov, and AJCC staging systems), Hyam's grade, treatment factor, recurrence and survival were included. Univariate and multivariate analyses were completed to assess recurrence and survival. The ability of traditional staging systems and novel modifications of these were assessed for their capacity to predict recurrence and survival with concordance-statistics analysis. Results: A total of 256 ONB patients were included. 27 patients (10.9%) were Kadish A, 53 (21.4%) were Kadish B and 168 (67.7%) were Kadish C. 41 patients (16.3%) underwent surgery alone, 137 (54.4%) surgery + radiation therapy (RT), 51 (20.2%) surgery + chemotherapy + RT and 17 other (6.6%). The 5-year and 10-year overall survival (OS) were 83.5% and 66.7%, respectively. The 5-year and 10-year progression-free survival (PFS) were 70.8% and 53.1%, respectively. On univariate analysis, age, mKadish, Dulguerov stage, nodal status, positive margins, and surgery were associated with survival. On univariate analysis, T-stage, M-stage, AJCC stage, Kadish stage, Dulguerov stage, orbital involvement, skull base bone involvement, Hyam's grade and positive margins were associated with recurrence. On multivariable analysis, age, AJCC stage, involvement of bilateral maxillary sinuses and positive margins were associated with mortality, while only AJCC staging was associated with recurrence. When assessing the ability of staging systems to predict mortality, the original Kadish staging system had the worst predictive value (c-statistic = 0.5676), while a novel modification of the Dulguerov system incorporating Hyam's grade had the highest predictive value (c-statistic = 0.659), When assessing the ability to predict recurrence, the original mKadish had the worst ability to predict recurrence (c-statistic = 0.5513), while a novel modification of the AJCC staging incorporating Hyam's grade had the highest predictive value for recurrence (c-statistic = 0.702). Conclusions: Traditional ONB staging systems poorly predict survival and recurrence. Incorporation of Hyam's grade into traditional ONB staging systems improves the ability to predict mortality and disease recurrence. Publication History Article published online: 01 February 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".