International Validation of a Nomogram to Predict Recurrence after Resection of Grade 1 and 2 Nonfunctioning Pancreatic Neuroendocrine Tumors.

Humans Neuroectodermal Tumors, Primitive Neuroendocrine Tumors / diagnosis Nomograms Pancreatic Neoplasms / pathology Prognosis Retrospective Studies
Nonfunctional pancreatic neuroendocrine tumors Prediction model Recurrence Risk factors

Journal

Neuroendocrinology
ISSN: 1423-0194
Titre abrégé: Neuroendocrinology
Pays: Switzerland
ID NLM: 0035665

Informations de publication

Date de publication:
2022
Historique:
received: 19 08 2020
accepted: 29 06 2021
pubmed: 4 8 2021
medline: 26 5 2022
entrez: 3 8 2021
Statut: ppublish

Résumé

Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors. Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1-2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel's C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs >2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence. Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78-88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70-0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors >2 cm (C-statistic 0.80). External validity of this prediction model for recurrence after curative surgery for grade 1-2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com.

Sections du résumé

BACKGROUND
Despite the low recurrence rate of resected nonfunctional pancreatic neuroendocrine tumors (NF-pNETs), nearly all patients undergo long-term surveillance. A prediction model for recurrence may help select patients for less intensive surveillance or identify patients for adjuvant therapy. The objective of this study was to assess the external validity of a recently published model predicting recurrence within 5 years after surgery for NF-pNET in an international cohort. This prediction model includes tumor grade, lymph node status and perineural invasion as predictors.
METHODS
Retrospectively, data were collected from 7 international referral centers on patients who underwent resection for a grade 1-2 NF-pNET between 1992 and 2018. Model performance was evaluated by calibration statistics, Harrel's C-statistic, and area under the curve (AUC) of the receiver operating characteristic curve for 5-year recurrence-free survival (RFS). A sub-analysis was performed in pNETs >2 cm. The model was improved to stratify patients into 3 risk groups (low, medium, high) for recurrence.
RESULTS
Overall, 342 patients were included in the validation cohort with a 5-year RFS of 83% (95% confidence interval [CI]: 78-88%). Fifty-eight patients (17%) developed a recurrence. Calibration showed an intercept of 0 and a slope of 0.74. The C-statistic was 0.77 (95% CI: 0.70-0.83), and the AUC for the prediction of 5-year RFS was 0.74. The prediction model had a better performance in tumors >2 cm (C-statistic 0.80).
CONCLUSIONS
External validity of this prediction model for recurrence after curative surgery for grade 1-2 NF-pNET showed accurate overall performance using 3 easily accessible parameters. This model is available via www.pancreascalculator.com.

Identifiants

DOI: 10.1159/000518757 PMID: 34343138
pubmed: 34343138
pii: 000518757
doi: 10.1159/000518757
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

571-579

Informations de copyright

© 2021 The Author(s) Published by S. Karger AG, Basel.

Auteurs

Charlotte M Heidsma (CM)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Stijn van Roessel (S)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Susan van Dieren (S)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Anton F Engelsman (AF)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Oliver Strobel (O)

Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, University of Heidelberg, Heidelberg, Germany.

Markus W Buechler (MW)

Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, University of Heidelberg, Heidelberg, Germany.

Simon Schimmack (S)

Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, University of Heidelberg, Heidelberg, Germany.

Julie Perinel (J)

Department of Surgery, Centre Hospitalier Universitaire de Lyon, University of Lyon, Lyon, France.

Mustapha Adham (M)

Department of Surgery, Centre Hospitalier Universitaire de Lyon, University of Lyon, Lyon, France.

Vikram Deshpande (V)

Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Josefine Kjaer (J)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Olov Norlen (O)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Anthony J Gill (AJ)

Cancer Diagnosis and Pathology Group Kolling Institute of Medical Research and University of Sydney, Sydney, New South Wales, Australia.

Jaswinder S Samra (JS)

Department of Surgery, Royal North Shore Hospital, St Leonards, University of Sydney, Sydney, New South Wales, Australia.

Anubhav Mittal (A)

Department of Surgery, Royal North Shore Hospital, St Leonards, University of Sydney, Sydney, New South Wales, Australia.

Frederik J H Hoogwater (FJH)

Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.

Florian Primavesi (F)

Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria.

Stefan Stättner (S)

Department of Visceral, Transplant and Thoracic Surgery, Medical University of Innsbruck, Innsbruck, Austria.
Department of Surgery, Salzkammergut Klinikum, Standort Vocklabruck, Vocklabruck, Austria.

Marc G Besselink (MG)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

Casper H J van Eijck (CHJ)

Department of Surgery, Erasmus Medical Center, Erasmus University Rotterdam, Rotterdam, The Netherlands.

E J M Nieveen van Dijkum (EJM)

Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › International Validation of a Nomogram to...
questionsmedicales.fr › Tumeurs › Tumeurs par type histologique › Tumeurs du tissu nerveux › Tumeurs neuroectodermiques › Tumeurs neuroépitheliales › Tumeurs neuroectodermiques primitives › International Validation of a Nomogram to...
questionsmedicales.fr › Tumeurs › Tumeurs par type histologique › Tumeurs du tissu nerveux › Tumeurs neuroectodermiques › Tumeurs neuroendocrines › International Validation of a Nomogram to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Modèles statistiques › Nomogrammes › International Validation of a Nomogram to...
questionsmedicales.fr › Maladies endocriniennes › Tumeurs des glandes endocrines › Tumeurs du pancréas › International Validation of a Nomogram to...
questionsmedicales.fr › Diagnostic › Pronostic › International Validation of a Nomogram to...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études rétrospectives › International Validation of a Nomogram to...