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SOURCE: A Registry-Based Prediction Model for Overall Survival in Patients with Metastatic Oesophageal or Gastric Cancer

Cited 18 time in Web of Science Cited 18 time in Scopus
Authors

van den Boom, Hector G.; Abu-Hanna, Ameen; ter Veer, Emil; van Kleef, Jessy Joy; Lordick, Florian; Stahl, Michael; Ajani, Jaffer A.; Guimbaud, Rosine; Park, Se Hoon; Dutton, Susan J.; Bang, Yung-Jue; Boku, Narikazu; Mohammad, Nadia Haj; Sprangers, Mirjam A. G.; Verhoeven, Rob H. A.; Zwinderman, Aeilko H.; van Oijen, Martijn G. H.; van Laarhoven, Hanneke W. M.

Issue Date
2019-02
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Citation
Cancers, Vol.11 No.2, p. 187
Abstract
Prediction models are only sparsely available for metastatic oesophagogastric cancer. Because treatment in this setting is often preference-based, decision-making with the aid of a prediction model is wanted. The aim of this study is to construct a prediction model, called SOURCE, for the overall survival in patients with metastatic oesophagogastric cancer. Data from patients with metastatic oesophageal (n = 8010) or gastric (n = 4763) cancer diagnosed during 2005-2015 were retrieved from the nationwide Netherlands cancer registry. A multivariate Cox regression model was created to predict overall survival for various treatments. Predictor selection was performed via the Akaike Information Criterion and a Delphi consensus among experts in palliative oesophagogastric cancer. Validation was performed according to a temporal internal-external scheme. The predictive quality was assessed with the concordance-index (c-index) and calibration. The model c-indices showed consistent discriminative ability during validation: 0.71 for oesophageal cancer and 0.68 for gastric cancer. The calibration showed an average slope of 1.0 and intercept of 0.0 for both tumour locations, indicating a close agreement between predicted and observed survival. With a fair c-index and good calibration, SOURCE provides a solid foundation for further investigation in clinical practice to determine its added value in shared decision making.
ISSN
2072-6694
URI
https://hdl.handle.net/10371/173036
DOI
https://doi.org/10.3390/cancers11020187
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  • College of Medicine
  • Department of Medicine
Research Area Clinical Medicine

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