Lan Gao1,2,3, Shu-Chuen Li4. 1. Deakin Health Economics, Centre for Population Health Research, Faculty of Health, Deakin University, Level 3, Building BC, 221 Burwood Hwy, Burwood, VIC, 3125, Australia. lan.gao@deakin.edu.au. 2. Global Obesity Centre, Centre for Population Health Research, Faculty of Health, Deakin University, Geelong, VIC, Australia. lan.gao@deakin.edu.au. 3. Discipline of Pharmacy and Experimental Pharmacology, School of Biomedical Sciences and Pharmacy, Faculty of Medicine and Health, The University of Newcastle, MS108, Medical Sciences Building, University Drive, Callaghan, 2308, NSW, Australia. lan.gao@deakin.edu.au. 4. Discipline of Pharmacy and Experimental Pharmacology, School of Biomedical Sciences and Pharmacy, Faculty of Medicine and Health, The University of Newcastle, MS108, Medical Sciences Building, University Drive, Callaghan, 2308, NSW, Australia.
Abstract
OBJECTIVES: To assess the cost-effectiveness of nivolumab for patients with advanced or metastatic squamous non-small-cell lung cancer (NSCLC) progressed on or after platinum-based chemotherapy using a modelled economic evaluation. METHODS: Both partition survival (PS) and Markov models, comprised of three health states, were adopted to evaluate the cost-effectiveness of nivolumab compared to docetaxel from an Australian healthcare system perspective with a 6-year time horizon. Reconstructed individual patient data (IPD) were derived from published Kaplan-Meier curves from the pivotal trial for overall survival (OS) and progression-free survival (PFS) using a validated algorithm. Best-fitting survival curves were selected to extrapolate the OS, PFS and post-progression survival (PPS) beyond trial duration. Expected costs and health outcomes [i.e. quality-adjusted life year (QALY), and life year (LY)] associated with each of the health states (i.e. PF, PD and dead) were accrued over the time horizon. Both deterministic and probabilistic sensitivity analyses were undertaken. RESULTS: Nivolumab was associated with both higher costs and benefits in both PS and Markov models. In particular, from the PS model, nivolumab cost an additional A$198,862/QALY and A$181,623/LY gained. The Markov model showed that nivolumab had an incremental cost-effectiveness ratio (ICER) of A$220,029/QALY and A$193,459/LY, respectively. The sensitivity analyses showed base-case results were sensitive to the extrapolation approach, duration of treatment, cost of nivolumab and time horizon modelled. CONCLUSIONS: Using an often-quoted willingness-to-pay per QALY threshold in Australia (i.e. A$50,000), the treatment with nivolumab cannot be considered cost-effective. It might be funded publicly by special arrangements given unmet clinical needs for patients.
OBJECTIVES: To assess the cost-effectiveness of nivolumab for patients with advanced or metastatic squamous non-small-cell lung cancer (NSCLC) progressed on or after platinum-based chemotherapy using a modelled economic evaluation. METHODS: Both partition survival (PS) and Markov models, comprised of three health states, were adopted to evaluate the cost-effectiveness of nivolumab compared to docetaxel from an Australian healthcare system perspective with a 6-year time horizon. Reconstructed individual patient data (IPD) were derived from published Kaplan-Meier curves from the pivotal trial for overall survival (OS) and progression-free survival (PFS) using a validated algorithm. Best-fitting survival curves were selected to extrapolate the OS, PFS and post-progression survival (PPS) beyond trial duration. Expected costs and health outcomes [i.e. quality-adjusted life year (QALY), and life year (LY)] associated with each of the health states (i.e. PF, PD and dead) were accrued over the time horizon. Both deterministic and probabilistic sensitivity analyses were undertaken. RESULTS:Nivolumab was associated with both higher costs and benefits in both PS and Markov models. In particular, from the PS model, nivolumab cost an additional A$198,862/QALY and A$181,623/LY gained. The Markov model showed that nivolumab had an incremental cost-effectiveness ratio (ICER) of A$220,029/QALY and A$193,459/LY, respectively. The sensitivity analyses showed base-case results were sensitive to the extrapolation approach, duration of treatment, cost of nivolumab and time horizon modelled. CONCLUSIONS: Using an often-quoted willingness-to-pay per QALY threshold in Australia (i.e. A$50,000), the treatment with nivolumab cannot be considered cost-effective. It might be funded publicly by special arrangements given unmet clinical needs for patients.