ArticleNPJ genomic medicine2026
The clinical utility of carrier screening.
Article in NPJ genomic medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.