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Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders.
- Source :
-
The European journal of health economics : HEPAC : health economics in prevention and care [Eur J Health Econ] 2024 Aug; Vol. 25 (6), pp. 999-1011. Date of Electronic Publication: 2023 Nov 17. - Publication Year :
- 2024
-
Abstract
- Genetic diseases are medical conditions caused by sequence or structural changes in an individual's genome. Whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly used for diagnosing suspected genetic conditions in children to reduce the diagnostic delay and accelerating the implementation of appropriate treatments. While more information is becoming available on clinical efficacy and economic sustainability of WES, the broad implementation of WGS is still hindered by higher complexity and economic issues. The aim of this study is to estimate the cost-effectiveness of WGS versus WES and standard testing for pediatric patients with suspected genetic disorders. A Bayesian decision tree model was set up. Model parameters were retrieved both from hospital administrative datasets and scientific literature. The analysis considered a lifetime time frame and adopted the perspective of the Italian National Health Service (NHS). Bayesian inference was performed using the Markov Chain Monte Carlo simulation method. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI). The present analysis showed that implementing first-line WGS would be a cost-effective strategy, against the majority of the other tested alternatives at a threshold of €30,000-50,000, for diagnosing outpatient pediatric patients with suspected genetic disorders. According to the sensitivity analyses, the findings were robust to most assumption and parameter uncertainty. Lessons learnt from this modeling study reinforces the adoption of first-line WGS, as a cost-effective strategy, depending on actual difficulties for the NHS to properly allocate limited resources.<br /> (© 2023. The Author(s).)
- Subjects :
- Humans
Child
Markov Chains
Decision Trees
Italy
Genetic Testing economics
Genetic Testing methods
Female
Male
Child, Preschool
Cost-Effectiveness Analysis
Cost-Benefit Analysis
Bayes Theorem
Genetic Diseases, Inborn diagnosis
Genetic Diseases, Inborn genetics
Genetic Diseases, Inborn economics
Exome Sequencing economics
Exome Sequencing methods
Whole Genome Sequencing economics
Whole Genome Sequencing methods
Subjects
Details
- Language :
- English
- ISSN :
- 1618-7601
- Volume :
- 25
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- The European journal of health economics : HEPAC : health economics in prevention and care
- Publication Type :
- Academic Journal
- Accession number :
- 37975990
- Full Text :
- https://doi.org/10.1007/s10198-023-01644-0