Abstract
319 Background: The use of patient reported outcome measures (PROMs) is a popular method to obtain real-world patient data in oncological research. However, PROMs rely on voluntary and active participation of patients and are therefore prone to selection bias. To investigate the suitability of PROMs as real-world data, we investigated the real-world representativeness of the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) registry with respect to the Dutch population of patients with esophagogastric cancer. Methods: We identified 2,575 patients in the POCOP registry and 13,702 in the nationwide population-based Netherlands Cancer Registry (NCR) from 2016-2021. We used Representativeness-indicators (R-indicators) to investigate the degree to which the POCOP registry and clinically relevant subgroups thereof, were a representative sample with respect to the population. R-indicators express the representativeness between 0 (not representative) and 1 (perfect representativeness). Calibration methods using inverse propensity weighting were used to correct potential differences between POCOP and the population estimates. Subsequently, median and 5-year overall survival were calculated and compared between patients in the POCOP registry and in the population, to investigate the representativeness in terms of survival. Results: Representativeness of the entire POCOP registry was 0.73 (95% CI: 0.71-0.74). The overall representativeness of palliative patients was higher than that of potentially curable patients (0.89 (0.87-0.90) and 0.70 (0.68-0.71), respectively). Representativeness of most clinical subgroups stratified to treatment was good; R-indicators ranged between 0.8 to 1.0. Median survival of the NCR, POCOP and calibrated POCOP was 19, 32, and 23 months, respectively. The 5-year overall survival of patients in the NCR, POCOP and calibrated POCOP was 26%, 36%, and 27%, respectively. Conclusions: The real-world representativeness of patients who participated in PROMs was good when we accounted for treatment. This shows that in the analysis of PROMs stratification to treatment groups can lead to generalizable results to the population. Using complete non-stratified PROMs, real-world representativeness was lower and calibration methods could be used to correct differences between patients in the PROMs and the population.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.