Cost-effectiveness analyses of genetic and genomic diagnostic tests

Abstract

Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests compete with traditional approaches to diagnosis, including the genetic testing of single genes and other clinical strategies, for finite health-care budgets. In this context, decision analytic model-based cost-effectiveness analysis is a useful method to help evaluate the costs versus consequences of introducing new health-care interventions. This Perspective presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of health-care resources to obtain robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.

Orthodontics in the era of big data analytics

“…We are living in an exciting time of major technological advancements in genetics. The next‐generation sequencing (NGS) technology has rapidly evolved since the time of human genome project in 2003 with a declining cost of ~US$10 million in 2007 to $1500 in 2015 . NGS commonly refers to a technology of massively parallel sequencing of small fragments of DNA or RNA in a relatively short time .…”

The economic case for precision medicine

“…For example, clinical decisions may be challenging if the cut point for a continuous test result is disputed or if multiple treatment strategies are possible following a particular test result. In practice, therefore, the imperfect implementation [61] of a testing strategy, through clinicians’ prescribing behavior, may contribute to overestimating the net health gain obtained from a precision medicine [20]. …”

“…An extensive literature of published economic evaluations of health technologies for precision medicine is developing [11–19] and, in 2016, some 45 systematic reviews on this topic were identified [20]. The specific challenges in designing and conducting economic evaluations of precision medicine have also been described [21–27].…”

Predicting the occurrence of variants in RAG1 and RAG2

“…We may view each gene as a vector with one component corresponding to each residue mutation in the gene, together with a weight for each component that is given by (1). Therefore, we can find the overlap score measure with the rf − igf weight of each term in g, for a query q;…”

“…Costs associated with genomic investigations continue to reduce [1] while the richness of data generated increases. Globally, the adoption of wide scale genome sequencing implies that all new-born infants may receive screening for pathogenic genetic variants in an asymptomatic stage, pre-emptively [2].…”