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Original article
Incremental cost-effectiveness of algorithm-driven genetic testing versus no testing for Maturity Onset Diabetes of the Young (MODY) in Singapore
  1. Hai Van Nguyen1,
  2. Eric Andrew Finkelstein2,
  3. Shweta Mital2,
  4. Daphne Su-Lyn Gardner3
  1. 1 School of Pharmacy, Memorial University of Newfoundland, St. John’s, Canada
  2. 2 Health Services and Systems Research, Duke NUS Medical School, Singapore
  3. 3 Department of Endocrinology, Singapore General Hospital, Singapore
  1. Correspondence to Dr Hai Van Nguyen, School of Pharmacy, Memorial University of Newfoundland, St. John’s, A1B 3V6, Canada; hvnguyen{at}mun.ca

Abstract

Background Offering genetic testing for Maturity Onset Diabetes of the Young (MODY) to all young patients with type 2 diabetes has been shown to be not cost-effective. This study tests whether a novel algorithm-driven genetic testing strategy for MODY is incrementally cost-effective relative to the setting of no testing.

Methods A decision tree was constructed to estimate the costs and effectiveness of the algorithm-driven MODY testing strategy and a strategy of no genetic testing over a 30-year time horizon from a payer’s perspective. The algorithm uses glutamic acid decarboxylase (GAD) antibody testing (negative antibodies), age of onset of diabetes (<45 years) and body mass index (<25 kg/m2 if diagnosed >30 years) to stratify the population of patients with diabetes into three subgroups, and testing for MODY only among the subgroup most likely to have the mutation. Singapore-specific costs and prevalence of MODY obtained from local studies and utility values sourced from the literature are used to populate the model.

Results The algorithm-driven MODY testing strategy has an incremental cost-effectiveness ratio of US$93 663 per quality-adjusted life year relative to the no testing strategy. If the price of genetic testing falls from US$1050 to US$530 (a 50% decrease), it will become cost-effective.

Conclusion Our proposed algorithm-driven testing strategy for MODY is not yet cost-effective based on established benchmarks. However, as genetic testing prices continue to fall, this strategy is likely to become cost-effective in the near future.

  • algorithm-driven genetic testing
  • maturity onset diabetes of the young
  • gene panel testing
  • cost-effectiveness
  • Singapore

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Footnotes

  • Contributors HVN led the model development and contributed to data analysis; SM contributed to data analysis; EF and DS-LG conceptualised the initial idea; DS-LG conducted clinical investigations that provided model inputs. All authors contributed to manuscript writing and manuscript revisions. HN and DS-LG are the overall guarantors of the manuscript.

  • Funding DS-LG and EF received funding from the Stratified Medicine Programme Office, a joint initiative by the Biomedical Research Council and the National Medical Research Council, Singapore.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.