Evidence map›Paper›PMID 16170241›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2005

How can the evaluation of genetic tests be enhanced? Lessons learned from the ACCE framework and evaluating genetic tests in the United Kingdom.

Simon Sanderson, Ron Zimmern, Mark Kroese, Julian Higgins, Christine Patch, Jon Emery

Abstract read
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In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Parental experience of whole genome sequencing for children with sensorineural hearing loss.International journal of qualitative studies on health and well-being · 2026
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  10. The Parent PrU: A measure to assess personal utility of pediatric genomic results.Genetics in medicine : official journal of the American College of Medical Genetics · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Simon SandersonUniversity of Cambridge and Cambridge Genetics Knowledge Park, Cambridge, UK.
Ron Zimmern
Mark Kroese
Julian Higgins
Christine Patch
Jon Emery

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in genetic technology are increasing the availability of genetic tests, not only for rare single gene disorders, but also for common diseases such as breast and colo-rectal cancer. Before there can be widespread uptake of these tests, they must be evaluated to confirm the benefits of their use. But how should genetic tests be evaluated, given the speed at which new tests are emerging? One highly influential approach is the analytic validity, clinical validity, clinical utility and ethical, legal and social issues (ACCE) framework, which has provided a benchmark for the evaluation of genetic tests. The approach has been adopted and adapted by the United Kingdom Genetic Testing Network, with the help of the Public Health Genetics Unit in Cambridge, to evaluate new genetic tests for use in the National Health Service. We discuss a number of conceptual, methodological, and practical issues concerning the evaluation of genetic tests, based on lessons learned from applying the ACCE framework and from the UK experience, and make a number of recommendations to further strengthen the evaluation of genetic tests.

Indexed as

Genetic Carrier ScreeningGenetic TestingGenetic Diseases, InbornHeterozygoteHumansUnited Kingdom

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.