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Marieke Pape, Steven C. Kuijper, Pauline A.J. Vissers, Laurens V. Beerepoot, Geert-Jan Creemers, Hanneke W.M. van Laarhoven, and Rob H.A. Verhoeven

Background: In recent years, clinical trials have shown improved survival of patients with metastatic esophageal or gastric cancer. The number of patients participating in clinical trials is limited, and survival improvements observed from clinical trials are unrepresentative for the full population. The aim of our study was to assess trends in survival for the best-case, typical, and worst-case scenarios in patients with metastatic esophageal or gastric cancer. Methods: We selected patients with metastatic esophageal or gastric cancer diagnosed between 2006 and 2020 from the nationwide Netherlands Cancer Registry. Survival was calculated for different percentiles of the survival curve for each incidence year (eg, the 10th percentile [p10] represents the top 10% of patients with the best survival): p10 (best-case), p25 (upper-typical), p50 (median), p75 (lower-typical), and p90 (worst-case). Weighted linear regression analyses were performed to test whether changes in survival were significant. Results: The overall median survival between 2006 and 2020 remained unchanged for patients with esophageal cancer (n=10,448; from 5.2 to 5.2 months, respectively; P=.06) and improved for patients with gastric cancer (n=10,512; from 3.5 to 4.3 months, respectively; P=.001). For patients with esophageal cancer, survival for the best-case scenario (p10; best 10% of patients) significantly improved from 17.2 to 21.0 months (P=.006). For patients with gastric cancer, survival significantly improved for the best-case scenario (p10) from 15.9 to 23.5 months (P<.001) and the upper-typical scenario (p25) scenario improved from 7.9 to 9.9 months (P<.001). Conclusions: Despite significant survival improvements in clinical trials, survival improvements were not observed for the majority of patients treated in daily clinical practice. An increase in survival was only observed for patients with the best prognosis.

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Héctor G. van den Boorn, Ameen Abu-Hanna, Nadia Haj Mohammad, Maarten C.C.M. Hulshof, Suzanne S. Gisbertz, Bastiaan R. Klarenbeek, Marije Slingerland, Laurens V. Beerepoot, Tom Rozema, Mirjam A.G. Sprangers, Rob H.A. Verhoeven, Martijn G.H. van Oijen, Koos H. Zwinderman, and Hanneke W.M. van Laarhoven

Background: Personalized prediction of treatment outcomes can aid patients with cancer when deciding on treatment options. Existing prediction models for esophageal and gastric cancer, however, have mostly been developed for survival prediction after surgery (ie, when treatment has already been completed). Furthermore, prediction models for patients with metastatic cancer are scarce. The aim of this study was to develop prediction models of overall survival at diagnosis for patients with potentially curable and metastatic esophageal and gastric cancer (the SOURCE study). Methods: Data from 13,080 patients with esophageal or gastric cancer diagnosed in 2015 through 2018 were retrieved from the prospective Netherlands Cancer Registry. Four Cox proportional hazards regression models were created for patients with potentially curable and metastatic esophageal or gastric cancer. Predictors, including treatment type, were selected using the Akaike information criterion. The models were validated with temporal cross-validation on their C-index and calibration. Results: The validated model’s C-index was 0.78 for potentially curable gastric cancer and 0.80 for potentially curable esophageal cancer. For the metastatic models, the c-indices were 0.72 and 0.73 for esophageal and gastric cancer, respectively. The 95% confidence interval of the calibration intercepts and slopes contain the values 0 and 1, respectively. Conclusions: The SOURCE prediction models show fair to good c-indices and an overall good calibration. The models are the first in esophageal and gastric cancer to predict survival at diagnosis for a variety of treatments. Future research is needed to demonstrate their value for shared decision-making in clinical practice.