Longitudinal model-based meta-analysis for survival probabilities in patients with castration-resistant prostate cancer

Purpose The aims of this longitudinal model-based meta-analysis (MBMA) were to indirectly compare the time courses of survival probabilities and to identify corresponding potential significant covariates across approved drugs in patients with castration-resistant prostate cancer (CRPC). Methods A systematic literature review for monotherapy studies in patients with CRPC was conducted up to August 8, 2018. The time courses of progression-free survival (PFS) and overall survival (OS) were fitted with parametric survival models. Covariate analyses were performed to determine the impact of treatment drugs, dosing regimens, and patient characteristics on the survival probabilities. Simulations were carried out to quantify the magnitude of covariate effects. Results A total of 146 studies including clinical trials and real-world data on longitudinal survival probabilities in 20,712 patients with CRPC were included in our meta-database. The time courses of PFS and OS probabilities were best described by the log-logistic model. There was no significant difference in median OS and PFS between docetaxel, cabazitaxel, abiraterone acetate, and enzalutamide. There was no significant dose-response relationship in PFS or OS for docetaxel at 50 to 120 mg/m(2) every 3 weeks (Q3W) and cabazitaxel at 20 to 25 mg/m(2) Q3W. Model-based simulations indicated that PFS probability was associated with chemotherapy, Gleason score, and baseline prostate-specific antigen (BLPSA), while OS probability was associated with chemotherapy, Gleason score, visceral metastasis, Eastern Cooperative Oncology Group performance status, and BLPSA. Conclusion Our modeling and simulation framework can be applied to support indirect comparison, dose selection, and go/no-go decision-making for new agents targeting CRPC.