SOURCE-PANC: A Prediction Model for Patients With Metastatic Pancreatic Ductal Adenocarcinoma Based on Nationwide Population-Based Data

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  • 1 Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam;
  • | 2 Department of Research and Development, Netherlands Comprehensive Cancer Organisation, Utrecht;
  • | 3 Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam; and
  • | 4 Division of Medical Oncology, Department of Internal Medicine, GROW–School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, the Netherlands.

Background: A prediction model for overall survival (OS) in metastatic pancreatic ductal adenocarcinoma (PDAC) including patient and treatment characteristics is currently not available, but it could be valuable for supporting clinicians in patient communication about expectations and prognosis. We aimed to develop a prediction model for OS in metastatic PDAC, called SOURCE-PANC, based on nationwide population-based data. Materials and Methods: Data on patients diagnosed with synchronous metastatic PDAC in 2015 through 2018 were retrieved from the Netherlands Cancer Registry. A multivariate Cox regression model was created to predict OS for various treatment strategies. Available patient, tumor, and treatment characteristics were used to compose the model. Treatment strategies were categorized as systemic treatment (subdivided into FOLFIRINOX, gemcitabine/nab-paclitaxel, and gemcitabine monotherapy), biliary drainage, and best supportive care only. Validation was performed according to a temporal internal–external cross-validation scheme. The predictive quality was assessed with the C-index and calibration. Results: Data for 4,739 patients were included in the model. Sixteen predictors were included: age, sex, performance status, laboratory values (albumin, bilirubin, CA19-9, lactate dehydrogenase), clinical tumor and nodal stage, tumor sublocation, presence of distant lymph node metastases, liver or peritoneal metastases, number of metastatic sites, and treatment strategy. The model demonstrated a C-index of 0.72 in the internal–external cross-validation and showed good calibration, with the intercept and slope 95% confidence intervals including the ideal values of 0 and 1, respectively. Conclusions: A population-based prediction model for OS was developed for patients with metastatic PDAC and showed good performance. The predictors that were included in the model comprised both baseline patient and tumor characteristics and type of treatment. SOURCE-PANC will be incorporated in an electronic decision support tool to support shared decision-making in clinical practice.

Submitted August 5, 2020; final revision received October 10, 2020; accepted for publication October 12, 2020.

Published online July 21, 2021.

Author contributions: Study design: van den Boorn, Dijksterhuis, van Oijen, van Laarhoven. Data collection: van den Boorn, Dijksterhuis, van der Geest. Data analysis: van den Boorn, Dijksterhuis. Manuscript preparation: van den Boorn, Dijksterhuis, van Oijen, van Laarhoven.

Disclosures: Dr. de Vos-Geelen has reported receiving nonfinancial support from BTG Specialty Pharmaceuticals and Servier; serving as a consultant for Amgen, AstraZeneca, Merck Sharp & Dohme, Pierre Fabre, Servier, and Shire; and receiving grant/research support from Servier. Dr. Wilmink has reported serving as a consultant for Celgene, Merck, and Servier; and receiving unrestricted research funding from Bayer, Celgene, Merck Serono, Nordic Bioscience, and Servier. Dr. van Oijen has reported receiving grant/research support from Bayer, Bristol Myers Squibb, Lilly, Merck Serono, Nordic Pharma, and Roche. Dr. van Laarhoven has reported serving as a consultant for Bristol Myers Squibb, Celgene, Lilly/ImClone, Merck Sharp & Dohme, Nordic Pharma, and Servier; and receiving grant/research support from Bayer Schering Pharma, Bristol Myers Squibb, Celgene, Lilly, Merck Serono, Merck Sharp & Dohme, Nordic Pharma, Philips Healthcare, Roche, and Servier. The remaining authors have reported that they have not received any financial consideration from any person or organization to support the preparation, analysis, results, or discussion of this article.

Correspondence: Hanneke W.M. van Laarhoven, MD, PhD, PhD, Department of Medical Oncology, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands. Email: h.vanlaarhoven@amsterdamumc.nl

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