Implementing performance-based risk-sharing agreements in non-small cell lung cancer immunotherapy: a real-world data case study.

backgroundPerformance-based risk-sharing agreements (PBRSA) represent an innovative tool for managing uncertainty and balanced distribution of the financial risk of high-cost drugs. By linking reimbursement to real-world treatment performance, these agreements help mitigate budgetary impacts. This study poses an illustrative patient-level PBRSA reimbursement model for non-small cell lung cancer (NSCLC) immunotherapy based on collected real-world data (RWD).

methodsA retrospective analysis of 266 patients with NSCLC treated with immunotherapy was performed. Progression-free survival (PFS) served as the primary outcome measure of therapeutic effectiveness. An illustrative patient-level PBRSA model was developed to quantify the manufacturer’s financial participation based on deviations from established PFS thresholds reported in randomised controlled trials (RCT). The manufacturer’s financial responsibility increased proportionally to greater deviations in patient outcomes from the RCT benchmark. Cost calculations were limited exclusively to the acquisition price of immunotherapies, excluding administration, toxicity management, and other indirect costs. The potential PBRSA scenario was compared with the current reimbursement situation.

resultsUsing this reimbursement method, cost savings per checkpoint inhibitor for healthcare payers could represent between 27.3% and 66.2% of the total cost, depending on the individual PFS reached. For the RWD cohort of NSCLC patients unsuccessfully treated with pembrolizumab monotherapy was 57.5% (a reduction in cost to payers from $27 996 to $11 893 per patient); pembrolizumab in combination 51.7% ($33 595 to $16 237); nivolumab 37.1% ($5 608 to $3 531); atezolizumab 27.3% ($11 799 to $8 583); and durvalumab 66.2% ($44 005 to $14 882).

conclusionsThis study proposes an illustrative patient-level PBRSA reimbursement model leveraging real-world clinical data to enhance risk-sharing for high-cost therapies. Unlike conventional cost-effectiveness analyses, this method directly links clinical performance and manufacturer financial responsibility. Future research should integrate comprehensive cost considerations and validate model performance in broader clinical settings.