From trial to registry data Survival and health-related quality of life outcomes in oesophagogastric cancer

Open Access
Authors
  • J.J. van Kleef
Supervisors
  • H.W.M. van Laarhoven
  • L.V. van de Poll-Franse
Cosupervisors
  • M.A.G. Sprangers
  • M.G.H. van Oijen
Award date 28-11-2025
ISBN
  • 9789465224053
Number of pages 375
Organisations
  • Faculty of Medicine (AMC-UvA)
Abstract

This thesis aimed to identify prognostic and predictive factors for overall survival and to explore the health-related quality of life (HRQoL) in patients with oesophagogastric cancer.
Several clinically relevant prognostic and predictive factors associated with systemic therapy in advanced oesophagogastric cancer were identified, supporting personalized treatment and future trial design.
Our review of palliative systemic therapy showed that, although baseline HRQoL is generally impaired, most therapies help maintain HRQoL, with some therapies offering better outcomes than others. However, HRQoL reporting in randomized trials remains limited and variable, with minimal improvement over time.
This thesis also presents the POCOP project (Prospective Observational Cohort study of Oesophagogastric cancer Patients) and its collaboration with other Dutch cancer cohorts, providing a foundation for large-scale research and innovative study designs.
Furthermore, external validation of the Dutch SOURCE survival prediction models using Belgian cancer registry data showed good calibration in gastric cancer but poor calibration in oesophageal cancer, emphasizing the need for validation before clinical application.
The last study of this thesis confirmed that HRQoL is an independent prognostic factor in both curative and palliative settings, indicating that HRQoL scales could be used to develop or update prognostic models.
The thesis concludes by highlighting the value of combining clinical trial and real-world data to improve outcomes of oesophagogastric cancer patients. It stresses the need for better HRQoL reporting and the use of patient-reported outcomes to support informed, personalized treatment decision making.

Document type PhD thesis
Language English
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