A Systematic Review of the Methodological Quality of Economic Evaluations in Genetic Screening and Testing for Monogenic Disorders

PurposeUnderstanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examine opportunities for improvement. MethodsWe searched Pubmed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the BMJ checklist. ResultsAcross 47 identified studies, there was substantial variation in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulation, comparing between two and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis. ConclusionWe describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection, (2) use of uncertainty/sensitivity analyses, and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.