Modeling Disease Trajectories for Castration-resistant Prostate Cancer Using Nationwide Population-based Data

BACKGROUND: Little is known about disease trajectories for men with castration-resistant prostate cancer (CRPC). OBJECTIVE: To create a state transition model that estimates time spent in the CRPC state and its outcomes. DESIGN, SETTING, AND PARTICIPANTS: The model was generated using population-based prostate-specific antigen data from 40% of the Swedish male population, which were linked to nationwide population-based databases. We compared the observed and predicted cumulative incidence of transitions to and from the CRPC state. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We measured time spent in the CRPC state and the proportion of men who died of prostate cancer during follow-up by CRPC risk category. RESULTS AND LIMITATIONS: Time spent in the CRPC state varied from 1.1 yr for the highest risk category to 3.9 yr for the lowest risk category. The proportion of men who died from prostate cancer within 10 yr ranged from 93% for the highest risk category to 54% for the lowest. There was good agreement between the model estimates and observed data. CONCLUSIONS: There is large variation in the time spent in the CRPC state, varying from 1 yr to 4 yr according to risk category. PATIENT SUMMARY: It is possible to accurately estimate the disease trajectory and duration for men with castration-resistant prostate cancer.