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Abstract
Objective To compare the cost-effectiveness of genetic testing strategies in patients with epilepsy of unknown etiology.
Methods This meta-analysis and cost-effectiveness study compared strategies involving 3 genetic tests: chromosomal microarray (CMA), epilepsy panel (EP) with deletion/duplication testing, and whole-exome sequencing (WES) in a cost-effectiveness model, using “no genetic testing” as a point of comparison.
Results Twenty studies provided information on the diagnostic yield of CMA (8 studies), EP (9 studies), and WES (6 studies). The diagnostic yield was highest for WES: 0.45 (95% confidence interval [CI]: 0.33–0.57) (0.32 [95% CI: 0.22–0.44] adjusting for potential publication bias), followed by EP: 0.23 (95% CI: 0.18–0.29), and CMA: 0.08 (95% CI: 0.06–0.12). The most cost-effective test was WES with an incremental cost-effectiveness ratio (ICER) of $15,000/diagnosis. However, after adjusting for potential publication bias, the most cost-effective test was EP (ICER: $15,848/diagnosis) followed by WES (ICER: $34,500/diagnosis). Among combination strategies, the most cost-effective strategy was WES, then if nondiagnostic, EP, then if nondiagnostic, CMA (ICER: $15,336/diagnosis), although adjusting for potential publication bias, the most cost-effective strategy was EP ± CMA ± WES (ICER: $18,385/diagnosis). While the cost-effectiveness of individual tests and testing strategies overlapped, CMA was consistently less cost-effective than WES and EP.
Conclusion WES and EP are the most cost-effective genetic tests for epilepsy. Our analyses support, for a broad population of patients with unexplained epilepsy, starting with these tests. Although less expensive, CMA has lower yield, and its use as the first-tier test is thus not supported from a cost-effectiveness perspective.
Glossary
- CI=
- confidence interval;
- CMA=
- chromosomal microarray;
- CNV=
- copy number variation;
- EP=
- epilepsy panel;
- ICER=
- incremental cost-effectiveness ratio;
- WES=
- whole-exome sequencing
Footnotes
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
Supplementary data: GitHub: github.com/IvanSanchezFernandez/CostEffectivenessGeneticTests and at Zenodo: zenodo.org/badge/latestdoi/138793909.
Patient Page page e523
- Received April 8, 2018.
- Accepted in final form August 30, 2018.
- © 2019 American Academy of Neurology
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