Emanuel Krebs , Deirdre Weymann , Cheryl Ho , Ian Bosdet , Janessa Laskin , Howard J. Lim , Stephen Yip , Aly Karsan , Timothy P. Hanna , Samantha Pollard , Dean A. Regier
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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 recipients receiving multi-gene panel sequencing to controls receiving single-gene testing, maximising balance on observed demographic and clinical 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 and nonparametric bootstrapping.</div></div><div><h3>Findings</h3><div>We matched 858 panel-eligible advanced NSCLC patients to controls, achieving balance for the 16 included covariates. Average test 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 $3529 (95% CI: −$4268, $10,942) and mean incremental LYG were 0.08 (95% CI: −0.04, 0.18). Among the 1000 bootstrap samples, 14.5% had lower costs and increased survival and 78.6% had higher costs and increased survival. The INMB was $523 (95% CI: −$6256, $7023) at $50,000/LYG, with a 57.5% probability of being cost-effective, and $4575 (95% CI: −$5468, $14,064) at $100,000/LYG, with an 84.0% probability of being cost-effective.</div></div><div><h3>Interpretation</h3><div>Using population-based real-world data, we found a moderate to high probability that panel-based testing to inform targeted treatment for NSCLC would be cost-effective at higher thresholds.</div></div><div><h3>Funding</h3><div>This research was supported by <span>Genome British Columbia</span>/<span>Genome Canada</span> (G05CHS) and the <span>Terry Fox Research Institute</span>.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"40 ","pages":"Article 100936"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-world cost-effectiveness of multi-gene panel sequencing to inform therapeutic decisions for advanced non-small cell lung cancer: a population-based study\",\"authors\":\"Emanuel Krebs , Deirdre Weymann , Cheryl Ho , Ian Bosdet , Janessa Laskin , Howard J. 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Using a machine learning approach, we conducted 1:1 genetic algorithm matching of recipients receiving multi-gene panel sequencing to controls receiving single-gene testing, maximising balance on observed demographic and clinical 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 and nonparametric bootstrapping.</div></div><div><h3>Findings</h3><div>We matched 858 panel-eligible advanced NSCLC patients to controls, achieving balance for the 16 included covariates. Average test turnaround times were 18.6 days for multi-gene panel sequencing and 7.0 days for single-gene testing. 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Real-world cost-effectiveness of multi-gene panel sequencing to inform therapeutic decisions for advanced non-small cell lung cancer: a population-based study
Background
Multi-gene panel sequencing streamlines treatment selection for advanced non-small cell lung cancer (NSCLC). Implementation continues to be uneven across jurisdictions, partly due to uncertain clinical and economic impacts. 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 recipients receiving multi-gene panel sequencing to controls receiving single-gene testing, maximising balance on observed demographic and clinical 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 and nonparametric bootstrapping.
Findings
We matched 858 panel-eligible advanced NSCLC patients to controls, achieving balance for the 16 included covariates. Average test 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 $3529 (95% CI: −$4268, $10,942) and mean incremental LYG were 0.08 (95% CI: −0.04, 0.18). Among the 1000 bootstrap samples, 14.5% had lower costs and increased survival and 78.6% had higher costs and increased survival. The INMB was $523 (95% CI: −$6256, $7023) at $50,000/LYG, with a 57.5% probability of being cost-effective, and $4575 (95% CI: −$5468, $14,064) at $100,000/LYG, with an 84.0% probability of being cost-effective.
Interpretation
Using population-based real-world data, we found a moderate to high probability that panel-based testing to inform targeted treatment for NSCLC would be cost-effective at higher thresholds.
Funding
This research was supported by Genome British Columbia/Genome Canada (G05CHS) and the Terry Fox Research Institute.
期刊介绍:
The Lancet Regional Health – Americas, an open-access journal, contributes to The Lancet's global initiative by focusing on health-care quality and access in the Americas. It aims to advance clinical practice and health policy in the region, promoting better health outcomes. The journal publishes high-quality original research advocating change or shedding light on clinical practice and health policy. It welcomes submissions on various regional health topics, including infectious diseases, non-communicable diseases, child and adolescent health, maternal and reproductive health, emergency care, health policy, and health equity.