Abstract A17: Regional failure after surgery of primary oral cancer is highly associated with poor survival
Notice bibliographique
Résumé
Abstract Oral squamous cell carcinoma (OSCC) is notorious for poor prognosis and this has not improved over the last few decades. One main reason is the regional failure, i.e., neck metastasis. Some proposed elective neck dissection; however, only 20–28% positive node identified. Due to small sample sized studies and a lack of uniformity in study design and reporting system, current literatures have shown contradictory results in prediction using clinicopathological parameters. Moreover, the impact of neck dissection on patient's quality of life can be enormous with markedly compromised oral functions. Objective: The overall goal is to identify markers that can better predict tumor behavior at the time of diagnosis so patients can receive appropriate and effective treatment considering risk and benefit. As the first step, the objectives of this study are: 1) to collect the demographics, clinicopathological information of primary OSCC patients surgically treated with intent-to-cure; 2) to categorize these patients according to their nodal status (LN0: negative node; LN+: positive node) at and after surgery; 3) to determine the impact of nodal status to the overall survival. Methods: Between 1995 and 2008, 283 primary OSCC patients received surgery with intent-to-cure and at least 12 months follow-up were identified in a longitudinal study. Data was collected with respect to patient demographics, smoking habit, anatomical site, nodal status at and after surgery, and time from surgery to positive nodal status, death (with disease or not), or the last follow-up visit. Patients were categorized into 4 groups: A. Patients who were LN0 at surgery or during follow-up (N=183); B. Patients who were LN0 at surgery but LN+ during follow-up (N=56); C. Patients who received concurrent neck dissection and were LN+ at the time of surgery (N = 39); and D. Patients who received concurrence neck dissection and were LN0 at the time of surgery (N = 5). Differences among the groups were examined using Fisher's exact test for categorical variables or t-test for continuous variables. Time-to-event curves were estimated by the Kaplan-Meier method, and comparisons were performed using log-rank test. All of the tests were two-sided. P ≤ 0.05 was considered to be statistically significant. Results: There is no statistical difference among groups in age, gender, ethnicity, smoking habit, and anatomical sites. Among the 239 LN0 patients without concurrent neck dissection at the time of surgery (Groups A and B), 23% became LN+ during follow-up. Strikingly, 66% and 80% of Group B had regional failure at the first 12 and 18 months postsurgery, respectively. Nodal status at or after surgery is significant associated with survival (75% in Group A and 100% in Group D vs. 43% in Group B and 46% in Group C, P < 0.0001), time to survival (83.5 ± 44.5 months of Groups A&B vs. 53.4 ± 46.5 months in Groups C&D, P < 0.0001) and 5-year survival rate (84% in Groups A&B vs. 47% in Groups C&D, P < 0.0001). Interestingly, there is no difference in time to death and survival rate between Group B and Group C. Conclusion: The nodal status is highly associated with patients' survival disregarding its timing during the disease progression, i.e., presence at the time of diagnosis, at or after surgery. For those LN0 OSCCs at the time of diagnosis, the data strongly support an aggressive subgroup that will develop LN+ within a short time frame post-surgery. However, the aggressiveness is difficult to predict solely on the conventional clinicopathological parameters. There is an urgent need to develop more effective/ objective molecular markers to predict patients who will develop nodal disease shortly after surgery. Hence, these patients will benefit from the prophylactic neck dissection, and ultimately, a better survival can be achieved. Supported by the Canadian Cancer Society Research Institute (20336), NIH/NIDCR (R01 DE17013) and Terry Fox Research Institute (2009–24). Citation Information: Cancer Prev Res 2011;4(10 Suppl):A17.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».