SOURCE: Prediction models for overall survival in patients with metastatic and potentially curable esophageal and gastric cancer.

Abstract

301 Background: Prediction models in cancer care can provide personalized prediction outcomes and can aid in shared decision making. Existing prediction models for esophageal and gastric cancer (EGC), however, are mostly aimed at predicting survival after a curative treatment has already been completed. The aim of this study is to develop prediction models, called SOURCE, to predict overall survival at diagnosis in potentially curable and metastatic EGC patients. Methods: The data from 12,756 EGC patients diagnosed between 2014-2017 were retrieved from the prospective Netherlands Cancer Registry. Four Cox regression models were created for potentially curable and metastatic cancers of the esophagus and stomach. Predictors, including treatment type, were selected using the Akaike Information Criterion. The models were validated with temporal cross-validation on their concordance-index (c-index) and calibration. Results: The validated model’s c-index is 0.76 for potentially curable cancer. For the metastatic models, the c-indices are 0.71 and 0.70 for esophageal and gastric cancer, respectively. The calibration intercepts and slopes lie in the 95% confidence interval of 0 and 1, respectively. The included model variables are given in Table. Conclusions: The SOURCE prediction models show fair c-indices and an overall good calibration. The models are the first in EGC to include treatment as a predictor. The models predict survival at diagnosis for a variety of treatments and therefore could have a high clinical applicability. Future research is needed to demonstrate the effect on shared decision making in clinical practice. [Table: see text]