Real-world usage and adverse events of immune checkpoint inhibitors (ICI): a large-scale, automated, GDPR-compliant analysis of hospital records
Authors: Annelies Verbiest1, Philip Debruyne2, Iege Bassez3, Danielle Delombaerde4,5, Laura Tack2, Clara L. Oeste3, Laura Deckx3, Lieselot Croes1,5, Dries Hens3, Vincent Geldhof1, Hans Prenen1,5, Christof Vulsteke4,5
Download our poster, as presented at ESMO 2024, and get more insights into the methodology used and the results obtained in the multi-center study.
Background
• Immune checkpoint inhibitors (ICI) form a backbone of curative and non-curative treatment across cancer types, yielding survival benefits as well as costs and adverse events (AEs).
• The interplay between these is challenging to estimate from trial data and classical real-world data (claims, registries), because of the heterogeneity of patient populations and outcomes.
• The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is designed for analysis of cross-domain observational health data.
Conclusions
• We were able to build granular real-world data warehouses across hospitals on >1500 ICI patients.
• Lung carcinoma constituted 46% of ICI-indications.
• Among AEs that can be ICI-related, diabetes mellitus was the main AE detected before start of ICI (21% patients).
• AEs detected on ICI-treatment varied.
Complete the form above to download the poster and discover the methods used and the results obtained.
1 Department of Oncology, Multidisciplinary Oncological Center Antwerp, Antwerp University Hospital, Antwerp, Belgium
2 Department of Medical Oncology, General Hospital AZ Groeninge, Kortrijk, Belgium
3 LynxCare, Leuven, Belgium
4 Department of Oncology, General Hospital AZ Maria Middelares, Ghent, Belgium
5 Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium
Background
• Immune checkpoint inhibitors (ICI) form a backbone of curative and non-curative treatment across cancer types, yielding survival benefits as well as costs and adverse events (AEs).
• The interplay between these is challenging to estimate from trial data and classical real-world data (claims, registries), because of the heterogeneity of patient populations and outcomes.
• The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is designed for analysis of cross-domain observational health data.
Conclusions
• We were able to build granular real-world data warehouses across hospitals on >1500 ICI patients.
• Lung carcinoma constituted 46% of ICI-indications.
• Among AEs that can be ICI-related, diabetes mellitus was the main AE detected before start of ICI (21% patients).
• AEs detected on ICI-treatment varied.
Complete the form above to download the poster and discover the methods used and the results obtained.
1 Department of Oncology, Multidisciplinary Oncological Center Antwerp, Antwerp University Hospital, Antwerp, Belgium
2 Department of Medical Oncology, General Hospital AZ Groeninge, Kortrijk, Belgium
3 LynxCare, Leuven, Belgium
4 Department of Oncology, General Hospital AZ Maria Middelares, Ghent, Belgium
5 Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, Antwerp, Belgium
