Evidence map›Paper›PMID 42180364›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Integrating enriched case data from national laboratory testing with population-based case-control analyses: a novel statistical likelihood-ratio methodology for PS4 applied to 325,345 breast cancer cases and 671,006 controls.

Sophie Allen, Charlie F Rowlands, Alice Garrett, Fergus Couch, Marcy E Richardson, Tina Pesaran, Joanna Pethick, Katrina Lavelle, Fiona McRonald, Sally Vernon and 21 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

31 authors.

Sophie AllenDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Charlie F RowlandsDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Alice GarrettDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Fergus CouchDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester Minnesota, USA.
Marcy E RichardsonAmbry Genetics, Aliso Viejo California, USA.
Tina PesaranAmbry Genetics, Aliso Viejo California, USA.
Joanna PethickNHS England, National Disease Registration Service, United Kingdom.
Katrina LavelleNHS England, National Disease Registration Service, United Kingdom.
Fiona McRonaldNHS England, National Disease Registration Service, United Kingdom.
Sally VernonNHS England, National Disease Registration Service, United Kingdom.
Beth TorrDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Lucy LoongDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Riyaad AungraheetaBristol Genetics Laboratory, South West Genomic Laboratory Hub, North Bristol NHS Trust, Bristol, UK.
Miranda DurkieSheffield Children's NHS Foundation Trust, Sheffield , United Kingdom.
George J BurghelManchester University Hospitals NHS Foundation Trust, Manchester , United Kingdom.
Alison CallawayUniversity Hospital Southampton NHS Foundation Trust, Salisbury, United Kingdom.
Rachel RobinsonLeeds Teaching Hospitals NHS Trust, Leeds , United Kingdom.
Joanne FieldNottingham University Hospitals NHS Trust, Nottingham , United Kingdom.
Bethan FrugtnietSt George's University Hospitals NHS Foundation Trust, Tooting London, United Kingdom.
Sheila Palmer-SmithCardiff and Vale University Health Board, Cardiff , United Kingdom.
Jonathan GrantWest of Scotland Centre for Genomic Medicine, Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde, Glasgow, UK.
Judith PaganWestern General Hospital, Edinburgh, United Kingdom.
Trudi McDevittCHI at Crumlin, Dublin, Ireland.
Katie SnapeSt George's University Hospitals NHS Foundation Trust, Tooting London, United Kingdom.
Helen HansonRoyal Devon University Healthcare NHS Foundation Trust, Exeter, United Kingdom.
Terri McVeighThe Royal Marsden NHS Foundation Trust, London, United Kingdom.
Chey LovedayOverdog.ai Ltd, London, United Kingdom.
Michael JonesDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
Steven HardyNHS England, National Disease Registration Service, United Kingdom.
Clare TurnbullDivision of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
CanVIG-UK

Funding

The Role of CHFR in Tumorigenesis and Paclitaxel-Sensitivity in Breast CancerP50CA116201 · NCI · MAYO CLINIC ROCHESTER · PI PETER C LUCAS · 2005 to 2026
$49.9M
Risk and penetrance of mutations from breast cancer testing panels.R01CA192393 · NCI · MAYO CLINIC ROCHESTER · PI COUCH, FERGUS JOSEPH, NATHANSON, KATHERINE L. · 2014 to 2018
$6.3M
Resolving the cancer relevance of predisposition gene mutationsR35CA253187 · NCI · MAYO CLINIC ROCHESTER · PI Fergus Joseph Couch · 2020 to 2026
$5.8M
The contribution of RAD51C and RAD51D to breast and ovarian cancerR01CA225662 · NCI · MAYO CLINIC ROCHESTER · PI COUCH, FERGUS JOSEPH, WEROHA, SARAVUT · 2018 to 2024
$2.5M
NCI NIH HHS P50 CA116201NCI NIH HHS R01 CA192393NCI NIH HHS R01 CA225662NCI NIH HHS R35 CA253187Wellcome Trust
6 · The paper itself

Abstract

Background: For many evidence criteria within v3.0 of the ACMG/AMP guidelines, methodologies have been developed to empower their use outside the stipulated evidence strengths. However, no such methodology has been established for case-control data (PS4). With the release of large-scale unselected case-control datasets and expansion of nationally-collected laboratory datasets enriched for pathogenic variant carriers, there is potential to combine datasets across ascertainment contexts in a more quantitative manner using novel likelihood ratio tools. Methods: Using our published PS4-LR-Calculator, we calculated a combined log likelihood ratio (PS4-LLR) across five datasets (three unselected, and two enriched), and estimated enrichment of pathogenic variants in clinically-ascertained laboratory data using truncating variant prevalence. Results: Data were combined for 10,817 missense variants from 325,345 female breast cancer patients and 671,006 controls of Western European ancestry for five breast cancer susceptibility genes ( Conclusion: This flexible, variant-level methodology combines nationally-collected 'enriched' datasets with unselected case-control cohorts, expanding the available information for case-control analysis, boosting power, enabling exploration of atypical penetrance and empowering variant classification.

Indexed as

ACMGbreast cancercase-controlPS4variant classification

Identifiers

PMID42180364
PMCPMC13193145

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.