SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer

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

doi:10.3390/cancers11020187

SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer

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

GI Medical Oncology

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

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.

Original language	English (US)
Article number	187
Journal	Cancers
Volume	11
Issue number	2
DOIs	https://doi.org/10.3390/cancers11020187
State	Published - Feb 2019

Keywords

Cox regression
Delphi consensus
Gastric cancer
Metastasis
Oesophageal cancer
Prediction model

ASJC Scopus subject areas

Oncology
Cancer Research

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van den Boorn, H. G., Abu-Hanna, A., Ter Veer, E., van Kleef, J. J., Lordick, F., Stahl, M., Ajani, J. A., Guimbaud, R., Park, S. H., Dutton, S. J., Bang, Y. J., Boku, N., Mohammad, N. H., Sprangers, M. A. G., Verhoeven, R. H. A., Zwinderman, A. H., van Oijen, M. G. H., & van Laarhoven, H. W. M. (2019). SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer. Cancers, 11(2), Article 187. https://doi.org/10.3390/cancers11020187

van den Boorn, HG, Abu-Hanna, A, Ter Veer, E, van Kleef, JJ, Lordick, F, Stahl, M, Ajani, JA, Guimbaud, R, Park, SH, Dutton, SJ, Bang, YJ, Boku, N, Mohammad, NH, Sprangers, MAG, Verhoeven, RHA, Zwinderman, AH, van Oijen, MGH & van Laarhoven, HWM 2019, 'SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer', Cancers, vol. 11, no. 2, 187. https://doi.org/10.3390/cancers11020187

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title = "SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer",

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.",

keywords = "Cox regression, Delphi consensus, Gastric cancer, Metastasis, Oesophageal cancer, Prediction model",

author = "{van den Boorn}, {H{\'e}ctor G.} and Ameen Abu-Hanna and {Ter Veer}, Emil and {van Kleef}, {Jessy Joy} and Florian Lordick and Michael Stahl and Ajani, {Jaffer A.} and Rosine Guimbaud and Park, {Se Hoon} and Dutton, {Susan J.} and Bang, {Yung Jue} and Narikazu Boku and Mohammad, {Nadia Haj} and Sprangers, {Mirjam A.G.} and Verhoeven, {Rob H.A.} and Zwinderman, {Aeilko H.} and {van Oijen}, {Martijn G.H.} and {van Laarhoven}, {Hanneke W.M.}",

note = "Publisher Copyright: {\textcopyright} 2019 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2019",

month = feb,

doi = "10.3390/cancers11020187",

language = "English (US)",

volume = "11",

journal = "Cancers",

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AU - van den Boorn, Héctor G.

AU - Abu-Hanna, Ameen

AU - Ter Veer, Emil

AU - van Kleef, Jessy Joy

AU - Lordick, Florian

AU - Stahl, Michael

AU - Ajani, Jaffer A.

AU - Guimbaud, Rosine

AU - Park, Se Hoon

AU - Dutton, Susan J.

AU - Bang, Yung Jue

AU - Boku, Narikazu

AU - Mohammad, Nadia Haj

AU - Sprangers, Mirjam A.G.

AU - Verhoeven, Rob H.A.

AU - Zwinderman, Aeilko H.

AU - van Oijen, Martijn G.H.

AU - van Laarhoven, Hanneke W.M.

PY - 2019/2

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N2 - �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.

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KW - Delphi consensus

KW - Gastric cancer

KW - Metastasis

KW - Oesophageal cancer

KW - Prediction model

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SOURCE: A registry-based prediction model for overall survival in patients with metastatic oesophageal or gastric cancer

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