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<p>Carrier screening aims to identify couples at risk of having children with serious genetic disorders. However, screening panels vary markedly in size, gene content and price, with little guidance to assess clinical utility or value. We analysed 89 carrier screening panels from 30 global providers, modelling test performance using pathogenic variants from gnomAD v4.1.0 and ClinVar across ten ancestry groups and two synthetic populations (representing the United States and Australia). We evaluated how panel size, content, price and clinical utility interrelate. We also compared value per dollar spent to guide clinical decision-making and fair pricing. Clinical utility showed no consistent relationship with panel size or price. Instead, mid-sized, pan-ancestry “Goldilocks” panels delivered the greatest utility, outperforming both smaller and larger panels, while delivering more equitable outcomes. We developed a visual “clinical utility meter” to compare relative test performance and an “efficiency frontier” framework to identify the best value tests for a given price. This data-driven framework and visual tool can support rational test design and selection for value-based laboratory medicine.</p>

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The clinical utility of carrier screening

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月25日

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  • Mia J. Gruzin,
  • Leslie Burnett

摘要

Carrier screening aims to identify couples at risk of having children with serious genetic disorders. However, screening panels vary markedly in size, gene content and price, with little guidance to assess clinical utility or value. We analysed 89 carrier screening panels from 30 global providers, modelling test performance using pathogenic variants from gnomAD v4.1.0 and ClinVar across ten ancestry groups and two synthetic populations (representing the United States and Australia). We evaluated how panel size, content, price and clinical utility interrelate. We also compared value per dollar spent to guide clinical decision-making and fair pricing. Clinical utility showed no consistent relationship with panel size or price. Instead, mid-sized, pan-ancestry “Goldilocks” panels delivered the greatest utility, outperforming both smaller and larger panels, while delivering more equitable outcomes. We developed a visual “clinical utility meter” to compare relative test performance and an “efficiency frontier” framework to identify the best value tests for a given price. This data-driven framework and visual tool can support rational test design and selection for value-based laboratory medicine.