OBJECTIVES: In the absence of mature, statistically, and clinically significant overall survival (OS) gains, novel oncology drugs face considerable challenges during health technology assessments (HTAs). This study investigated exceptions where therapies under these circumstances are reimbursed by HTA agencies by analyzing the evidence package underlying positive HTA outcomes.

METHODS: Approved oncology drugs from the European Medicines Agency (EMA) website were identified from 2019, selecting those with comparative studies where statistically significant OS gains were not demonstrated. HTA reports from agencies in Germany (G-BA), France (HAS), England (NICE), and Sweden (TLV) were retrieved and decision-making drivers and critiques were analyzed, conducting a thematic analysis.

RESULTS: 18 drugs were selected and 51 associated HTA reports were reviewed, of which 43 led to full or restricted reimbursement and 8 led to negative reimbursement. The demonstration of concurrent benefits in the primary surrogate endpoint (e.g., PFS) and either morbidity or HRQoL was a key driver leading to reimbursement by HAS (n=6) and G-BA (n=4). In contrast, evidence around budget neutrality or cost-effectiveness were a common focal point for TLV (n=5) and NICE (n=3). In the remaining reimbursed cases, HTA bodies cited multiple factors contributing to their decisions (e.g., improved safety profile, high unmet need, benefits in specific subpopulations or cancer stages, and bridging to a potential cure).

CONCLUSIONS: HTA agencies evaluated novel oncology drugs with limited OS data on a case-by-case basis, but appeared willing to accept uncertainty in conditions that were rare, dire, or with few treatment options. As expected, G-BA and HAS focused on clinical-effectiveness outcomes, while NICE and TLV also considered economic arguments. Based on these findings, a modelling approach can enable manufacturers to proactively identify data gaps and optimize investment returns either in clinical or economic outcomes to strengthen the evidence package and reduce reimbursement uncertainty, especially in anticipation of JCA implementation.