Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders

Mario Cesare Nurchis (), Francesca Clementina Radio, Luca Salmasi, Aurora Heidar Alizadeh, Gian Marco Raspolini, Gerardo Altamura, Marco Tartaglia, Bruno Dallapiccola and Gianfranco Damiani
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Mario Cesare Nurchis: Università Cattolica del Sacro Cuore
Francesca Clementina Radio: Ospedale Pediatrico Bambino Gesù IRCCS
Aurora Heidar Alizadeh: Università Cattolica del Sacro Cuore
Gian Marco Raspolini: Università Cattolica del Sacro Cuore
Gerardo Altamura: Università Cattolica del Sacro Cuore
Marco Tartaglia: Ospedale Pediatrico Bambino Gesù IRCCS
Bruno Dallapiccola: Ospedale Pediatrico Bambino Gesù IRCCS
Gianfranco Damiani: Fondazione Policlinico Universitario A. Gemelli IRCCS

The European Journal of Health Economics, 2024, vol. 25, issue 6, No 7, 999-1011

Abstract: 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.

Keywords: Pediatric population; Genomic sequencing; Exome sequencing; Bayesian cost-effectiveness analysis; Public Health (search for similar items in EconPapers)
JEL-codes: C11 C80 I18 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10198-023-01644-0

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