Cost-effectiveness of precision medicine in the fourth-line treatment of metastatic lung adenocarcinoma: An early decision analytic model of multiplex targeted sequencing.
To identify parameters that drive the cost-effectiveness of precision medicine by comparing the use of multiplex targeted sequencing (MTS) to select targeted therapy based on tumour genomic profiles to either no further testing with chemotherapy or no further testing with best supportive care in the fourth-line treatment of metastatic lung adenocarcinoma.



A combined decision tree and Markov model to compare costs, life-years, and quality-adjusted life-years over a ten-year time horizon from an Australian healthcare payer perspective. Data sources included the published literature and a population-based molecular cohort study (Cancer 2015). Uncertainty was assessed using deterministic sensitivity analyses and quantified by estimating expected value of perfect/partial perfect information. Uncertainty due to technological/scientific advancement was assessed through a number of plausible future scenario analyses.



Point estimate incremental cost-effective ratios indicate that MTS is not cost-effective for selecting fourth-line treatment of metastatic lung adenocarcinoma. Lower mortality rates during testing and for true positive patients, lower health state utility values for progressive disease, and targeted therapy resulting in reductions in inpatient visits, however, all resulted in more favourable cost-effectiveness estimates for MTS. The expected value to decision makers of removing all current decision uncertainty was estimated to be between AUD 5,962,843 and AUD 13,196,451, indicating that additional research to reduce uncertainty may be a worthwhile investment. Plausible future scenarios analyses revealed limited improvements in cost-effectiveness under scenarios of improved test performance, decreased costs of testing/interpretation, and no biopsy costs/adverse events. Reductions in off-label targeted therapy costs, when considered together with the other scenarios did, however, indicate more favourable cost-effectiveness of MTS.



As more clinical evidence is generated for MTS, the model developed should be revisited and cost-effectiveness re-estimated under different testing scenarios to further understand the value of precision medicine and its potential impact on the overall health budget.
Centre for Health Economics, Monash Business School, Monash University, Victoria 3800, Australia; Cambridge Centre for Health Service Research, University of Cambridge, Cambridge CB2 0SR, United Kingdom. Electronic address: brett.doble@medschl.cam.ac.uk.
Brett
B
Doble
Olivia Newton-John Cancer Research Institute, Olivia Newton-John Cancer and Wellness Centre, Austin Health, Victoria 3084, Australia.
Thomas
T
John
Garvan Institute of Medical Research, The Kinghorn Cancer Centre, Darlinghurst, New South Wales 2010, Australia; St. Vincent's Clinical School, UNSW Australia, New South Wales 2052, Australia.
David
D
Thomas
Molecular Pathology Research and Development Laboratory, Department of Pathology, Peter MacCallum Cancer Centre, Victoria 3002, Australia.
Andrew
A
Fellowes
Molecular Pathology Research and Development Laboratory, Department of Pathology, Peter MacCallum Cancer Centre, Victoria 3002, Australia.
Stephen
S
Fox
Centre for Health Economics, Monash Business School, Monash University, Victoria 3800, Australia; Office of Health Economics, London, SW1E 6QT, United Kingdom.
Paula
P
Lorgelly
D000230:Adenocarcinoma / Q000188:drug therapy / Q000191:economics / Q000556:secondary*; D000077192:Adenocarcinoma of Lung; D001315:Australia; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D018450:Disease Progression; D023281:Genomics; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy* / Q000191:economics / Q000556:secondary*; D058990:Molecular Targeted Therapy / Q000379:methods; D057285:Precision Medicine / Q000191:economics*; D019057:Quality-Adjusted Life Years; D017422:Sequence Analysis, DNA
Cost-effectiveness analysis; Economic evaluation; Genomic testing; Next-generation sequencing; Non-small cell lung cancer; Oncology