Impact of Structural Differences on the Modeled Cost-Effectiveness of Noninvasive Prenatal Testing

Amber Salisbury, Alison Pearce, Kirsten Howard and Sarah Norris
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Amber Salisbury: Menzies Centre for Health Policy and Economics, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
Alison Pearce: The Daffodil Centre, University of Sydney, a joint venture with Cancer Council NSW, Sydney, Australia
Kirsten Howard: Menzies Centre for Health Policy and Economics, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia
Sarah Norris: Menzies Centre for Health Policy and Economics, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia

Medical Decision Making, 2024, vol. 44, issue 7, 811-827

Abstract: Background Noninvasive prenatal testing (NIPT) was developed to improve the accuracy of prenatal screening to detect chromosomal abnormalities. Published economic analyses have yielded different incremental cost-effective ratios (ICERs), leading to conclusions of NIPT being dominant, cost-effective, and cost-ineffective. These analyses have used different model structures, and the extent to which these structural variations have contributed to differences in ICERs is unclear. Aim To assess the impact of different model structures on the cost-effectiveness of NIPT for the detection of trisomy 21 (T21; Down syndrome). Methods A systematic review identified economic models comparing NIPT to conventional screening. The key variations in identified model structures were the number of health states and modeling approach. New models with different structures were developed in TreeAge and populated with consistent parameters to enable a comparison of the impact of selected structural variations on results. Results The review identified 34 economic models. Based on these findings, demonstration models were developed: 1) a decision tree with 3 health states, 2) a decision tree with 5 health states, 3) a microsimulation with 3 health states, and 4) a microsimulation with 5 health states. The base-case ICER from each model was 1) USD$34,474 (2023)/quality-adjusted life-year (QALY), 2) USD$14,990 (2023)/QALY, (3) USD$54,983 (2023)/QALY, and (4) NIPT was dominated. Conclusion Model-structuring choices can have a large impact on the ICER and conclusions regarding cost-effectiveness, which may inadvertently affect policy decisions to support or not support funding for NIPT. The use of reference models could improve international consistency in health policy decision making for prenatal screening. Highlights NIPT is a clinical area in which a variety of modeling approaches have been published, with wide variation in reported cost-effectiveness. This study shows that when broader contextual factors are held constant, varying the model structure yields results that range from NIPT being less effective and more expensive than conventional screening (i.e., NIPT was dominated) through to NIPT being more effective and more expensive than conventional screening with an ICER of USD$54,983 (2023)/QALY. Model-structuring choices may inadvertently affect policy decisions to support or not support funding of NIPT. Reference models could improve international consistency in health policy decision making for prenatal screening.

Keywords: noninvasive prenatal testing, NIPT; prenatal screening; health economic modeling; economic evaluation; structural uncertainties; decision tree; microsimulation; cost-effectiveness analyses; cost-utility analyses (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:44:y:2024:i:7:p:811-827

DOI: 10.1177/0272989X241263368

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