Presentation (CTI)

OBJECTIVES: Early health technology assessments are increasingly recommended to inform “go/no-go” decisions during drug development and launch. Conventional approaches using network meta-analysis (NMA) and cost-effectiveness models (CEMs) typically evaluate a single target product profile (TPP), limiting exploration of uncertainty across plausible efficacy scenarios. This constraint can lead to suboptimal decisions when patient-level data (PLD) are unavailable. We introduce Value-Based Decision Boundary Analysis (VB-DBA), a novel framework that integrates NMA and early CEMs for time-to-event outcomes without requiring PLD, enabling health technology developers (HTDs) to identify efficacy thresholds and evaluate value-based pricing (VBP) scenarios.
METHODS: VB-DBA defines clinically relevant decision boundaries across three zones (aspirational, upside, and minimum-go) based on hazard ratio (HR) ranges for TPP comparators. A simulation-based bootstrapping approach estimates standard errors for hypothetical log-HRs using reconstructed Kaplan-Meier data from an anchor study, fitted via Royston-Parmar flexible survival models. These boundaries are integrated into an early CEM to generate VBP scenarios and assess commercial potential. A hypothetical example in renal cell carcinoma (RCC) illustrates the method, modeling overall survival (OS) and progression-free survival (PFS) across thirty-seven HR scenarios. Commercial potential scores were calculated by combining VBP outputs with market share weights for comparators.
RESULTS: VB-DBA identified HR thresholds where relative efficacy shifts across zones, informing pivotal trial design, comparator selection, and pricing strategies. For the example RCC asset, eighty VBP scenarios were modeled across OS and PFS. Commercial potential scores showed limited viability under most scenarios, emphasizing the importance of recalibrating TPP assumptions early and aligning clinical and economic objectives to reduce risk.
CONCLUSIONS: VB-DBA offers a structured, evidence-driven approach to explore uncertainty, optimize trial design, and align pricing strategies before committing additional resources to development or deciding where and when to launch. By integrating efficacy thresholds with economic modeling, VB-DBA provides more informed, economically efficient development decisions and facilitates internal stakeholder alignment.