Background: Ovarian cancer is the fifth leading cause of cancer death in women in the US. With poly(ADP-ribose) polymerase (PARP) inhibitors having shown promising results in ongoing trials, there is interest in better understanding their economic value.
Objective: This study aimed to review and evaluate the quality of published cost-effectiveness analyses (CEAs), and provide recommendations for CEAs in this setting.
Methods: A systematic literature review of the MEDLINE and EMBASE databases was conducted in June 2019 to identify CEAs of PARP inhibitors in treating advanced ovarian cancer from peer-reviewed journals and conferences. Key information from the identified publications were extracted and reviewed. The quality of full-text studies was assessed using the Quality of Health Economic Studies instrument. Recommendations for future CEAs were developed based on the findings from the literature review.
Results: Eighteen CEAs (five in full texts) met the inclusion criteria. Most adopted a US healthcare or societal perspective. The majority of the studies did not clearly display the economic model structure. No studies reported the validation of model projections based on internal or external data. Surrogate outcomes such as incremental costs per progression-free life-year gained were the most common outcomes reported. The majority of studies drew their conclusions based on surrogate outcomes, even with no theoretical or empirical threshold for cost effectiveness. All five full-text studies included some type of sensitivity or scenario analyses. The key drivers of the incremental cost-effectiveness ratio were treatment duration, effects, and costs, health utility, and prevalence of BRCA mutations.
Conclusion: In the existing CEAs for PARP inhibitors, there were uncertainties and challenges leading to variation in quality. We provided recommendations to improve consistency and quality of CEAs in this setting, which will help to better understand the value of PARP inhibitors, improve decision making, and reduce potential misallocation of resources.