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

Hanneke Wilma Marlies van LaarhovenAmeen Abu-HannaEmil Ter VeerJessy Joy van KleefFlorian LordickMichael StahlJaffer A AjaniRosine GuimbaudSe Hoon ParkSusan J DuttonYung-Jue BangNarikazu BokuNadia Haj MohammadMirjam A G SprangersRob H A VerhoevenAeilko H ZwindermanMartijn G H van Oijen
Published in: Cancers (2019)
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.
Keyphrases
  • papillary thyroid
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  • clinical practice
  • squamous cell carcinoma
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  • healthcare
  • decision making
  • machine learning
  • electronic health record
  • artificial intelligence
  • social media
  • big data