• Medicine · Mar 2020

    Observational Study

    Nomograms predict survival outcomes for distant metastatic pancreatic neuroendocrine tumor: A population based STROBE compliant study.

    • Gang Li, Mao-Lin Tian, Yun-Tao Bing, Hang-Yan Wang, Chun-Hui Yuan, and Dian-Rong Xiu.
    • Department of General Surgery, Peking University Third Hospital, Haidian District, Beijing, People's Republic of China.
    • Medicine (Baltimore). 2020 Mar 1; 99 (13): e19593.

    AbstractAs a rare malignant tumor, pancreatic neuroendocrine tumor (pNET) has very low incidence. However, most of the pNET patients would develop the distant metastasis, which significantly reduces patients' survival rate. Therefore, it is very important to construct a prognostic model of pNET patients with distant metastasis based on a large database to guide clinical application and treatment. The aim of this study is to establish nomograms for cancer-specific survival (CSS) and overall survival (OS) of patients with distant metastatic pNET based on the Surveillance, Epidemiology, and End Results (SEER) database.SEER were reviewed and the patients with pNET diagnosed between 1973 and 2015 were selected. After screening, a total of 624 cases were included in the study. Patients were randomly divided into a training cohort (n = 416) and a validation cohort (n = 208). Cox proportional hazard analysis revealed that age at diagnosis of ≥80 years, year of diagnosis, histological grade, and primary site surgery were independent factors both for CSS and OS. The nomograms indicated good accuracy in predicting 1-, 3-, and 5-year survival, with a C-index of 0.777 (95% confidence interval [CI], 0.743-0.811) for CSS and 0.772 (95% CI 0.738-0.806) for OS in training cohort. In the validation cohort, the C-index was 0.798 (95% CI 0.755-0.841) for CSS and 0.797 (95% CI 0.753-0.841) for OS. The calibration curves showed satisfactory consistency between predicted and actual survival.The study establishes excellent prognostic nomograms for CSS and OS for pNET patients with distant metastasis. They can be used to accurately predict survival rate, and provide useful information to physicians and patients.

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