Presentation (CTI)

OBJECTIVES: CLL has evolved into a multi-line, long-duration disease with rapid evidence generation, frequent treatment switching and immature overall survival (OS) data. While Bruton tyrosine kinase inhibitors (BTKis) are increasingly viewed as clinically comparable, they differ meaningfully in tolerability, persistence, pricing dynamics, and downstream economic impact. Conventional static CEAs, typically focused on single lines of therapy, fail to capture evolving factors, particularly in the context of Medicare price negotiations and emerging real-world-evidence (RWE). We present a methodological framework for a living, sequence-CEA designed to support payer decision making in dynamic CLL treatment landscapes.
METHODS: We constructed a living sequence-CEA framework informed by a Real-time AI-assisted Living Systematic Literature Review (REAL-SLR) able to explicitly represent treatment pathways across multiple lines of therapy. The framework integrates randomized controlled trial data, matched-adjusted indirect comparisons (MAICs), regulatory updates, and continuously updated RWE on safety, discontinuation, and persistence. Early treatment attributes are modelled as determinants of downstream sequencing options and cost trajectories. Pricing inputs are structured to accommodate evolving policy/contracting environments, including negotiated prices/rebates. The framework supports iterative updating as new clinical, real-world, and pricing data emerge, without model redevelopment.
RESULTS: The proposed framework shifts evaluative focus from isolated treatment comparisons to sequence-level decisions. By modelling treatment persistence/discontinuation, the approach captures how early-line choices propagate economic and clinical consequences across the disease course, even with immature OS. The living structure enables timely reassessment of value as evidence and policy contexts evolve supporting stratified analyses for clinically-relevant subpopulations where safety/tolerability differences are consequential.
CONCLUSIONS: Living sequence-CEAs offer a methodologically coherent alternative for evaluating CLL treatments than static, single-line CEAs. By aligning modelling structure with living RWE dynamics, this approach provides a decision-relevant basis for strategic formulary evaluation under conditions of uncertainty. Living CEA models enable better-informed formulary placement and subpopulation-specific coverage strategies in changing CLL treatment landscape.