A Nomogram to Accurately Identify Pancreatic Neuroendocrine Tumors Metastasizing to Distant Organs: A Study Based on Two National Population-Based Cohorts From the United States and China.
Clin Med Insights Oncol
; 16: 11795549221099853, 2022.
Article
em En
| MEDLINE
| ID: mdl-35620244
Background: Distant organ metastasis is the leading cause of death in pancreatic neuroendocrine tumor (pNET) patients. In the present study, we aimed to develop and validate a nomogram that could accurately identify pNET metastasizing to distant organs. Methods: The cases extracted from the Surveillance, Epidemiology, and End Results (SEER) program were assigned to the training cohort and validation cohort. The cases from the Chinese Gastrointestinal Neuroendocrine Tumors program were assigned to the external validation cohort. The strategy was developed with the support of a nomogram, and the predictive value of this strategy was evaluated by the receiver operating characteristic (ROC) curve analysis. Results: In total, 2024 American cases were involved in the present study. Besides, 1450 and 574 patients were allocated into training and internal validation cohorts, respectively. In addition, 122 Chinese patients were assigned to the external validation cohort. The results of the univariate logistic regression analysis suggested that tumor grade, tumor size, and the number of metastatic lymph nodes were the risk of metastasis to distant organs, and these 3 clinicopathological characteristics were used to develop the nomogram. We observed that the accuracy of the nomogram for predicting metastasis to distant organs was 0.797, 0.819, and 0.837 in the training cohort, internal validation cohort, and external validation cohort, respectively. Conclusions: A predictive nomogram was developed and validated, and it showed an acceptable performance in predicting metastasis to distant organs. The results will enable clinicians to identify pNETs, metastasizing to distant organs, and develop an effective individualized therapeutic strategy for these patients.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Clin Med Insights Oncol
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
China