Genomic testing for suspected monogenic kidney disease in children and adults: A health economic evaluation

You Wu; Kushani Jayasinghe; Zornitza Stark; Catherine Quinlan; Chirag Patel; Hugh McCarthy; Amali C Mallawaarachchi; Peter G Kerr; Stephen Alexander; Andrew J Mallett; Ilias Goranitis; KidGen Collaborative investigators

doi:10.1016/j.gim.2023.100942

Genomic testing for suspected monogenic kidney disease in children and adults: A health economic evaluation

Genet Med. 2023 Nov;25(11):100942. doi: 10.1016/j.gim.2023.100942. Epub 2023 Jul 22.

Affiliations

¹ Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Australian Genomics Health Alliance, Melbourne, VIC, Australia; Murdoch Children's Research Institute, Melbourne, VIC, Australia.
² Murdoch Children's Research Institute, Melbourne, VIC, Australia; Department of Nephrology, Monash Medical Centre, Melbourne, Australia; Monash University, Melbourne, Australia; The KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia.
³ Australian Genomics Health Alliance, Melbourne, VIC, Australia; Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia.
⁴ Murdoch Children's Research Institute, Melbourne, VIC, Australia; The KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia; Department of Pediatric Nephrology, Royal Children's Hospital, Melbourne, Australia.
⁵ The KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia; Genetic Health Queensland, Royal Brisbane and Women's Hospital, Brisbane, Australia.
⁶ Centre for Kidney Research, Children's Hospital at Westmead, Sydney, Australia; Sydney Children's Hospitals Network, Sydney, Australia; Faculty of Medicine, The University of Sydney, Sydney, Australia.
⁷ Department of Medical Genetics, Royal Prince Alfred Hospital, Sydney, Australia; Garvan Institute of Medical Research, Sydney, Australia.
⁸ Department of Nephrology, Monash Medical Centre, Melbourne, Australia; Monash University, Melbourne, Australia.
⁹ The KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia; Institute for Molecular Bioscience and Faculty of Medicine, The University of Queensland, Brisbane, Australia; Department of Renal Medicine, Townsville University Hospital, Townsville, Australia; College of Medicine & Dentistry, James Cook University, Townsville, Australia. Electronic address: andrew.mallett@health.qld.gov.au.
¹⁰ Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; Australian Genomics Health Alliance, Melbourne, VIC, Australia; Murdoch Children's Research Institute, Melbourne, VIC, Australia; The KidGen Collaborative, Australian Genomics Health Alliance, Melbourne, Australia. Electronic address: ilias.goranitis@unimelb.edu.au.

PMID: 37489581
DOI: 10.1016/j.gim.2023.100942

Abstract

Purpose: To assess the relative cost-effectiveness of genomic testing compared with standard non-genomic diagnostic investigations in patients with suspected monogenic kidney disease from an Australian health care system perspective.

Methods: Diagnostic and clinical information was used from a national cohort of 349 participants. Simulation modelling captured diagnostic, health, and economic outcomes during a time horizon from clinical presentation until 3 months post-test results based on the outcome of cost per additional diagnosis and lifetime horizon based on cost per quality-adjusted life-year (QALY) gained.

Results: Genomic testing was Australian dollars (AU$) 1600 more costly per patient and led to an additional 27 diagnoses out of a 100 individuals tested, resulting in an incremental cost-effectiveness ratio of AU$5991 per additional diagnosis. Using a lifetime horizon, genomic testing resulted in an additional cost of AU$438 and 0.04 QALYs gained per individual compared with standard diagnostic investigations, corresponding to an incremental cost-effectiveness ratio of AU$10,823 per QALY gained. Sub-group analyses identified that the results were largely driven by the cost-effectiveness in glomerular diseases.

Conclusion: Based on established or expected thresholds of cost-effectiveness, our evidence suggests that genomic testing is very likely to be cost saving for individuals with suspected glomerular diseases, whereas no evidence of cost-effectiveness was found for non-glomerular diseases.

Keywords: Cost-effectiveness; Economic evaluation; Exome sequencing; Genetic kidney disease; Genomic sequencing.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Australia
Child
Computer Simulation
Cost-Benefit Analysis
Genetic Testing*
Humans
Quality-Adjusted Life Years