Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders.

Importance: The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary. Objective: To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders. Design, Setting, and Participants: In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis. Main Outcomes and Measures: Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS. Results: The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty. Conclusions and Relevance: The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

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

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.

Organizational Aspects of the Implementation and Use of Whole Genome Sequencing and Whole Exome Sequencing in the Pediatric Population in Italy: Results of a Survey.

This study explores the organizational aspects of whole genome sequencing (WGS) implementation for pediatric patients with suspected genetic disorders in Italy, comparing it with whole exome sequencing (WES). Health professionals' opinions were collected through an internet-based survey and analyzed using a qualitative summative content analysis methodology. Among the 16 respondents, most were clinical geneticists performing only WES, while 5 also used WGS. The key differences identified include higher needs for analyzing genome rearrangements following WES, greater data storage and security requirements for WGS, and WGS only being performed in specific research studies. No difference was detected in centralization and decentralization issues. The main cost factors included genetic consultations, library preparation and sequencing, bioinformatic analysis, interpretation and confirmation, data storage, and complementary diagnostic investigations. Both WES and WGS decreased the need for additional diagnostic analyses when not used as last-resort tests. Organizational aspects were similar for WGS and WES, but economic evidence gaps may exist for WGS in clinical settings. As sequencing costs decline, WGS will likely replace WES and traditional genetic testing. Tailored genomic policies and cost-effectiveness analyses are needed for WGS implementation in health systems. WGS shows promise for enhancing genetics knowledge and expediting diagnoses for pediatric patients with genetic disorders.