Characteristics of small pancreatic neuroendocrine tumors and risk factors for invasion and metastasis
Notice bibliographique
Résumé
Background: The number of people with small pancreatic neuroendocrine tumors (pNETs) (tumors with a diameter less than or equal to 2 cm) is gradually increasing, but the selection of treatment strategy is still controversial. Our aim was to characterize small pNETs with a poor prognosis and to define the impact of aggressive small pNETs on survival and the risk factors for the development of invasive disease. Methods: Patients with pNETs diagnosed between 2004 and 2019 and a tumor diameter of 2 cm or less were selected from the SEER Registry. Kaplan-Meier survival analysis was used to identify the factors affecting patient survival, and binary logistic regression was used to identify the associated risk factors. Results: A total of 3261 patients with pNETs were enrolled in the study. Both older and younger patients benefited from surgery. Regional invasion occurred in 10% of the patients, and distant metastases occurred in 9% of the patients, but in both categories, those who underwent surgery had better survival outcomes than those who did not. There was no difference in survival between patients with a tumor diameter of 1-2 cm and those with a tumor diameter of less than 1 cm, and there was no difference in survival between patients with functional and nonfunctional small pNETs. However, the survival of patients with pNETs in the head of the pancreas was worse than that of patients with tumors in other parts of the pancreas. Survival was worse in elderly patients and in those with poorly differentiated and undifferentiated tumors. Lymphatic metastasis, regional invasion, and distant metastasis all worsened the prognosis of patients. The presence or absence of neuroendocrine function, the degree of tumor differentiation, and the location of the tumor were associated with the risk of lymphatic metastasis and regional invasion; the risk factors for distant metastasis were associated with the degree of differentiation and tumor location. Conclusion: The pNETs ≤ 2 cm in diameter could be still aggressive, and patient prognosis worsens after invasive disease develops. Attention to the characteristics of aggressive tumors can improve patient survival.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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) | 0,000 | 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 tête enseignante, 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 ».