TY - JOUR
T1 - Being Transparent About Brilliant Failures
T2 - An Attempt to Use Real-World Data in a Disease Model for Patients with Castration-Resistant Prostate Cancer
AU - Holleman, Marscha S.
AU - Huygens, Simone A.
AU - Al, Maiwenn J.
AU - Kuppen, Malou C. P.
AU - Westgeest, Hans M.
AU - van den Bergh, Alfonsus C. M.
AU - Bergman, Andries M.
AU - van den Eertwegh, Alfonsus J. M.
AU - Hendriks, Mathijs P.
AU - Lampe, Menuhin I.
AU - Mehra, Niven
AU - van Moorselaar, Reindert J. A.
AU - van Oort, Inge M.
AU - Somford, Diederik M.
AU - de Wit, Ronald
AU - van de Wouw, Agnes J.
AU - Gerritsen, Winald R.
AU - Groot, Carin A. Uyl-de
N1 - Funding Information: This research was funded by Sanofi-Aventis Netherlands B.V., Janssen-Cilag B.V., Astellas Pharma B.V., and Bayer B.V. The funding organisations had no role in the design and conduct of the study; collection, management, analysis, interpretation of the data; or preparation, review, or approval of the manuscript. Publisher Copyright: © 2022, The Author(s).
PY - 2022/6
Y1 - 2022/6
N2 - Background: Real-world disease models spanning multiple treatment lines can provide insight into the (cost) effectiveness of treatment sequences in clinical practice. Objective: Our objective was to explore whether a disease model based solely on real-world data (RWD) could be used to estimate the effectiveness of treatments for patients with castration-resistant prostate cancer (CRPC) that could then be suitably used in a cost-effectiveness analysis. Methods: We developed a patient-level simulation model using patient-level data from the Dutch CAPRI registry as input parameters. Time to event (TTE) and overall survival (OS) were estimated with multivariate regression models, and type of event (i.e., next treatment or death) was estimated with multivariate logistic regression models. To test internal validity, TTE and OS from the simulation model were compared with the observed outcomes in the registry. Results: Although patient characteristics and survival outcomes of the simulated data were comparable to those in the observed data (median OS 20.6 vs. 19.8 months, respectively), the disease model was less accurate in estimating differences between treatments (median OS simulated vs. observed population: 18.6 vs. 17.9 [abiraterone acetate plus prednisone], 24.0 vs. 25.0 [enzalutamide], 20.2 vs. 18.7 [docetaxel], and 20.0 vs. 23.8 months [radium-223]). Conclusions: Overall, the disease model accurately approximated the observed data in the total CRPC population. However, the disease model was unable to predict differences in survival between treatments due to unobserved differences. Therefore, the model is not suitable for cost-effectiveness analysis of CRPC treatment. Using a combination of RWD and data from randomised controlled trials to estimate treatment effectiveness may improve the model.
AB - Background: Real-world disease models spanning multiple treatment lines can provide insight into the (cost) effectiveness of treatment sequences in clinical practice. Objective: Our objective was to explore whether a disease model based solely on real-world data (RWD) could be used to estimate the effectiveness of treatments for patients with castration-resistant prostate cancer (CRPC) that could then be suitably used in a cost-effectiveness analysis. Methods: We developed a patient-level simulation model using patient-level data from the Dutch CAPRI registry as input parameters. Time to event (TTE) and overall survival (OS) were estimated with multivariate regression models, and type of event (i.e., next treatment or death) was estimated with multivariate logistic regression models. To test internal validity, TTE and OS from the simulation model were compared with the observed outcomes in the registry. Results: Although patient characteristics and survival outcomes of the simulated data were comparable to those in the observed data (median OS 20.6 vs. 19.8 months, respectively), the disease model was less accurate in estimating differences between treatments (median OS simulated vs. observed population: 18.6 vs. 17.9 [abiraterone acetate plus prednisone], 24.0 vs. 25.0 [enzalutamide], 20.2 vs. 18.7 [docetaxel], and 20.0 vs. 23.8 months [radium-223]). Conclusions: Overall, the disease model accurately approximated the observed data in the total CRPC population. However, the disease model was unable to predict differences in survival between treatments due to unobserved differences. Therefore, the model is not suitable for cost-effectiveness analysis of CRPC treatment. Using a combination of RWD and data from randomised controlled trials to estimate treatment effectiveness may improve the model.
UR - http://www.scopus.com/inward/record.url?scp=85126813497&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s40801-022-00294-7
DO - https://doi.org/10.1007/s40801-022-00294-7
M3 - Article
C2 - 35314962
SN - 2199-1154
VL - 9
SP - 275
EP - 285
JO - Drugs - real world outcomes
JF - Drugs - real world outcomes
IS - 2
ER -