ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Cancer Endocrinology
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1514792
This article is part of the Research TopicFunctional Neuroendocrine TumorsView all 12 articles
The PANEN nomogram: clinical decision support for patients with metastatic pancreatic neuroendocrine neoplasm referred for peptide receptor radionuclide therapy
Provisionally accepted- 1GenesisCare (Australia), Wembley, Western Australia, Australia
- 2GFO Clinics Troisdorf, Troisdorf, Germany
- 3BAMF Health, Michigan, United States
- 4Zentralklinik, Bad Berka, Germany
- 5Maastricht University, Maastricht, Netherlands
- 6CURANOSTICUM, Wiesbaden-Frankfurt, Germany
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Patients with pancreatic neuroendocrine neoplasms (P-NEN) may benefit from peptide receptor radionuclide therapy (PRRT). Prediction of overall survival (OS) using statistical models has the potential to guide treatment decisions. In this study, we have generated a clinicopathological and imaging parameter-based internally validated nomogram of patients who received PRRT for metastatic P-NEN to facilitate treatment decision support for the clinical management of such patients.We reviewed 447 pancreatic NEN patients treated with PRRT. Clinical variables for the prediction of overall survival (OS) included age, gender, Karnofsky performance score (KPS), weight loss, hepatomegaly, time from diagnosis to first PRRT (days), tumor functionality, presence of Hedinger syndrome, presence of liver metastases, presence of bone metastases, presence of lung metastases, alkaline phosphatase, FDG 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) scan positivity, erythrocytes, platelets, creatinine clearance, leucocytes, and histologic grade of tumor differentiation based on KI-67 staining. A random survival forests (RSF) method was used to construct a model with an optimal number of clinical variables. The model was developed on 80% of the data and tested on the remaining 20% of the data. Performance of prediction was calculated using the c-index, a generalization of the area under the ROC curve (AUC) for survival models.Median follow up time was 2045 days (min 136 days, max 10329 days). Time from diagnosis to 1 st PRRT, alkaline phosphatase, KPS Karnofsky performance score, hepatomegaly, weight loss, [18F]FDGFDG-PET scan positivity, Ki-67% derived histologic grade, lung metastases, age, presence of bone metastases, platelet count, erythrocyte count, creatinine clearance, hemoglobin, presence of functioning tumor, creatinine, and gender, were in order of importance, all independent predictors for overall survival. The development set c-index was 0.86, while the test set c-index was 0.82. A nomogram was constructed based on the optimal number of clinical parameters selected in the RSF model.This study proposes an internally validated nomogram (PANEN-N) to accurately predict overall survival for pancreatic neuroendocrine neoplasm (P-NEN) patients following PRRT, which could be used for patient counseling to facilitate informed and shared decision support in daily clinical practice as well as for generating new hypotheses.
Keywords: Pancreatic neuroendocrine neoplasm, clinical decision support nomogram, peptide receptor radionuclide therapy, Survival, machine learning
Received: 22 Oct 2024; Accepted: 28 May 2025.
Copyright: © 2025 Singh, Sanduleanu, Kulkarni, Langbein, Lambin and Baum. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Aviral Singh, GenesisCare (Australia), Wembley, Western Australia, Australia
Sebastian Sanduleanu, GFO Clinics Troisdorf, Troisdorf, 57462, Germany
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