# Construction and validation of a nomogram for patients with pancreatic neuroendocrine tumors: A population study of 5,927 patients

## TL;DR

Researchers built a tool to better predict survival for patients with rare pancreatic tumors using data from 5,927 cases.

## Contribution

A new nomogram was developed and validated for predicting prognosis in pancreatic neuroendocrine tumor patients.

## Key findings

- The nomogram outperformed the AJCC staging system in predicting cancer-specific survival.
- Calibration plots confirmed the nomogram's predictions align well with real-world outcomes.
- Eight independent factors were identified as key for prognosis prediction.

## Abstract

Pancreatic neuroendocrine tumors (pNETs) are a group of uncommon tumors derived from peptide neurons and neuroendocrine cells, and account for roughly 2% to 4% of all pancreatic neoplasms. This study aimed to construct and validate a nomogram for predicting the prognosis of patients with pNETs. Our data came from the SEER database.

A total of 5927 pNETs patients between 2004 and 2018 were included in this study. The nomogram was constructed base on eight prognostic factors and validated by C-index, ROC curve and calibration curves. A nomogram based on eight independent prognostic factors (patient age, sex, race, tumor grade, AJCC T, AJCC N, AJCC M, surgery, radiation, chemotherapy, tumor function and marital status) was developed for the prediction of CSS at 3 and 5 years.

The C-index and AUCs of the nomogram demonstrated that its superiority in discrimination over AJCC staging system. The calibration plots showed the good consistency between predictions and actual observations.

In conclusion, our nomogram could better predict the prognosis of pNETs patients than AJCC staging system. The nomogram could be improved by integrating more important factors other than SEER database.