Real-World Cost-Effectiveness of Publicly Reimbursed Multi-Gene Panel Sequencing to Inform Therapeutic Decisions for Advanced Non-Small Cell Lung Cancer in British Columbia, Canada
Author(s)
Krebs E1, Weymann D1, Ho C2, Bosdet I3, Laskin J3, Lim H3, Yip S3, Karsan A4, Hanna T5, Pollard S1, Regier D6
1Cancer Control Research, BC Cancer Research Institute, Vancouver, BC, Canada, 2Department of Medical Oncology, BC Cancer, Vancouver, Canada; University of British Columbia, Vancouver, BC, Canada, 3BC Cancer, Vancouver, BC, Canada, 4Michael Smith Genome Sciences Centre, BC Cancer Research Institute, Vancouver, BC, Canada, 5Queen’s University, Kingston, ON, Canada, 6BC Cancer/University of British Columbia, Vancouver, BC, Canada
Presentation Documents
OBJECTIVES: Multi-gene panel sequencing streamlines treatment selection for advanced non-small cell lung cancer (NSCLC). Implementation continues to be uneven across jurisdictions, in part due to uncertain clinical and economic impacts compared to single-gene testing. In British Columbia (BC), Canada, the public healthcare system reimbursed a multi-gene panel in September 2016. This study determined the population-level cost-effectiveness of publicly reimbursed multi-gene panel sequencing compared to single-gene testing for advanced NSCLC.
METHODS: Our population-based retrospective study design used patient-level linked administrative health databases. We considered adult BC residents with a panel-eligible lung cancer diagnosis between September 2016 and December 2018. Using a machine learning approach, we conducted 1:1 genetic algorithm matching of patients receiving multi-gene panel sequencing with contemporaneous controls receiving single-gene testing, maximizing balance on observed characteristics. Following matching, we estimated mean three-year survival time and costs (public healthcare payer perspective; 2021 CAD) and calculated the incremental net monetary benefit (INMB) for life-years gained (LYG) at conventional willingness-to-pay thresholds using inverse probability of censoring weighted linear regression. Our probabilistic analysis used nonparametric bootstrapping with 1000 replications to account for estimation uncertainty.
RESULTS: We matched 858 panel-eligible advanced NSCLC patients to controls, achieving balance for the 16 included covariates. Average turnaround times were 18.6 days for multi-gene panel sequencing and 7.0 days for single-gene testing. After matching, mean incremental costs were $3,529(95%CI:-$4,268,$10,942) and mean incremental LYG were 0.08(95%CI:-0.04,0.18). Among the 1,000 bootstrap samples, 14.5% had lower costs and increased survival and 78.6% had higher costs and increased survival. The probability of multi-gene panel sequencing being cost-effective was 57.5% at $50,000/LYG and 84.0% at $100,000/LYG(INMB:$4,575[95%CI:-$5,468,$14,064]).
CONCLUSIONS: Implementation of panel-based sequencing has been slow compared to the rapid development of new targeted therapies. Using population-based real-world data, we found a relatively high probability that panel-based testing to inform targeted treatment for NSCLC would be cost-effective at conventional thresholds.
Conference/Value in Health Info
Value in Health, Volume 27, Issue 6, S1 (June 2024)
Code
PT30
Topic
Economic Evaluation, Health Policy & Regulatory, Medical Technologies, Study Approaches
Topic Subcategory
Cost-comparison, Effectiveness, Utility, Benefit Analysis, Diagnostics & Imaging, Reimbursement & Access Policy
Disease
Oncology, Personalized & Precision Medicine
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