Being Transparent About Brilliant Failures: An Attempt to Use Real-World Data in a Disease Model for Patients with Castration-Resistant Prostate Cancer

Marscha S. Holleman*, Simone A. Huygens, Maiwenn J. Al, Malou C. P. Kuppen, Hans M. Westgeest, Alfonsus C. M. van den Bergh, Andries M. Bergman, Alfonsus J. M. van den Eertwegh, Mathijs P. Hendriks, Menuhin Lampe, Niven Mehra, Reindert J. A. van Moorselaar, Inge M. van Oort, Diederik M. Somford, Ronald de Wit, Agnes J. van de Wouw, Winald R. Gerritsen, Carin A. Uyl-de Groot

*Bijbehorende auteur voor dit werk

    OnderzoeksoutputAcademicpeer review

    6 Downloads (Pure)

    Samenvatting

    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.

    Originele taal-2English
    Pagina's (van-tot)275–285
    Aantal pagina's11
    TijdschriftDrugs – Real World Outcomes
    Volume9
    Vroegere onlinedatum21-mrt-2022
    DOI's
    StatusPublished - jun-2022

    Citeer dit