Beauchamp · Genetics in medicine : official journal of the American College of Medical Genetics 2019 · decision-tree cost-effectiveness model · n=>60,000 patients (input cohort)

Clinical impact and cost-effectiveness of a 176-condition expanded carrier screen.

Cited 78 times in the scientific literature.

Level 4 - case-series / case-control

Economic decision-tree model parameterized by retrospective cohort data and literature estimates (graded by analogy)

PubMed 30760891 · doi:10.1038/s41436-019-0455-8 · record verified 2026-08-30

What was done

A decision-tree model evaluated the health-economic impact of preconception screening comparing minimal screening (cystic fibrosis and spinal muscular atrophy) against a 176-condition expanded carrier screening (ECS) panel. Carrier frequencies were estimated using data from >60,000 screened patients (primarily with private insurance). Disease-specific costs and life-years lost were drawn from published literature and a cost-of-care database. The model evaluated outcomes per 100,000 pregnancies and tested parameter uncertainty using one-way and probabilistic sensitivity analyses.

What was found

The model predicted 290 affected pregnancies per 100,000 pregnancies for conditions on the ECS panel. On average, an affected condition resulted in 26 undiscounted life-years lost and $1,100,000 in lifetime costs. Relative to minimal screening, preconception ECS was projected to lower affected birth rates with an incremental cost-effectiveness ratio under $50,000 per life-year gained.

Why it matters

Demonstrates that expanding routine carrier screening beyond single-gene guidelines to broader panels may offer a cost-effective strategy for preventing severe childhood Mendelian diseases.

Limits

The study is a theoretical simulation dependent on model assumptions regarding reproductive decisions and literature-derived lifetime cost estimates. The underlying genetic frequency data came from a predominantly privately insured population, which may limit generalizability to other socioeconomic or demographic groups.

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