Olfactory Neuroblastoma: A Multicenter Survival Analysis and Application of a Staging Modification Incorporating Hyam's Grade
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».