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

• Published in: Drugs - Real World Outcomes 2022-06, Vol.9 (2), p.275-285
• Main Authors: Holleman, Marscha S., Huygens, Simone A., Al, Maiwenn J., Kuppen, Malou C. P., Westgeest, Hans M., van den Bergh, Alfonsus C. M., Bergman, Andries M., van den Eertwegh, Alfonsus J. M., Hendriks, Mathijs P., Lampe, Menuhin I., Mehra, Niven, van Moorselaar, Reindert J. A., van Oort, Inge M., Somford, Diederik M., de Wit, Ronald, van de Wouw, Agnes J., Gerritsen, Winald R., Groot, Carin A. Uyl-de
• Format: Article
• Language: English
• Subjects: Androgens; Cancer therapies; Care and treatment; Castration; Clinical medicine; Cost analysis; Data mining; Effectiveness; Hemoglobin; Internal Medicine; Medical research; Medicine; Medicine & Public Health; Metastasis; Methods; Narcotics; Original; Original Research Article; Patients; Pharmacology/Toxicology; Pharmacotherapy; Prognosis; Prostate cancer; Regression analysis; Research methodology; Simulation; Simulation methods; Statistical models; Statistics; Testosterone
• ISSN: 2199-1154; 2198-9788
• DOI: 10.1007/s40801-022-00294-7

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.