MODELING TREATMENTS AND OUTCOMES IN METASTATIC CASTRATION-RESISTANT PROSTATE CANCER- A CASE STUDY OF DISCRETE EVENT SIMULATION AND THE CHALLENGES FOR A UK NICE EVALUATION
Author(s)
Sorensen S1, Hall F2, Reifsniderf O1, Proskorovsky I3, Dearden L4, Girod I2, Lee J2
1Evidera, Bethesda, MD, USA, 2Janssen UK, High Wycombe, UK, 3Evidera, Montreal, QC, Canada, 4Janssen EMEA HEMAR, High Wycombe, UK
OBJECTIVES: A model evaluating abiraterone acetate plus prednisone (AAP) in chemotherapy-naïve metastatic castration-resistant prostate cancer (mCRPC) was submitted to the UK’s National Institute for Health and Care Excellence (NICE). Given the changing treatment landscape and clinical heterogeneity in mCRPC, a modeling approach that captures experiences of individual patients was chosen to simulate differing clinical trajectories and the impact of new treatments. This study employed a discrete-event simulation (DES) model to capture data from the AAP pivotal Phase 3 trial (COU-AA-302), which led to challenges during the NICE appraisal process. METHODS: An Excel-based DES model was developed using COU-AA-302 data from 1,088 patients with asymptomatic/mildly symptomatic mcRPC. Treatment pathways were defined by treatment guidelines, clinical practice, and clinical trial treatment regimens. Prediction equations were developed from an interim data cut (55% mortality) and validated based on the final data cut (96% mortality) of the trial. Outcomes included time on treatment, delay to chemotherapy, and overall survival (OS). RESULTS: The model predicted longer pre-chemotherapy survival (1.97 vs 1.10 years) and mean OS (3.71 vs. 2.94 years) for patients on AAP versus prednisone. Important predictors of time on treatment included time to diagnosis, baseline characteristics, previous treatment durations, age, and biomarkers (e.g., PSA progression). The mean OS HR predicted by the model (0.74, 95%CI 0.65-0.84) matched the final observed HR adjusted for crossover. In contrast, using Evidence Review Group (ERG)-preferred equations without predictors led to clinical predictions that did not match clinical trial results and led to higher ICERs. CONCLUSIONS: The OS benefit of AAP observed in the COU-AA-302 trial was accurately replicated using individual-patient predictions using DES which is a well-accepted approach within health economics, but it is not common in advanced oncology submissions reviewed by NICE which contributed to a delay in the final appraisal recommendation.
Conference/Value in Health Info
2016-10, ISPOR Europe 2016, Vienna, Austria
Value in Health, Vol. 19, No. 7 (November 2016)
Code
PCN137
Topic
Economic Evaluation
Topic Subcategory
Cost-comparison, Effectiveness, Utility, Benefit Analysis
Disease
Oncology