Evidence map›Paper›PMID 36646003›Full record

ReviewBreast (Edinburgh, Scotland)2023

Polygenic risk scores and breast cancer risk prediction.

Eleanor Roberts, Sacha Howell, D Gareth Evans

Open access · goldAbstract readReview
In one paragraph

Review in Breast (Edinburgh, Scotland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 1 pooled it
38.5field-weighted citation impact, top 1% of its field
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

76 citing papers in PubMed, 1 synthesis or guideline pooled it, 111 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
    Article
  4. Review
  5. Review
  6. PRS-BCJournal of medical genetics · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

16 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Eleanor RobertsDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Sacha HowellDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK.
D Gareth EvansManchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK. Electronic address: gareth.evans@mft.nhs.uk.
Manchester Academic Health Science Centre · GB

Funding

Cancer Research UK 27859
6 · The paper itself

Abstract

Polygenic Risk Scores (PRS) are a major component of accurate breast cancer risk prediction and have the potential to improve screening and prevention strategies. PRS combine the risk from Single nucleotide polymorphisms (SNPs) associated with breast cancer in Genome Wide Association Studies (GWAS) and explain over 30% of breast cancer heritability. When incorporated into risk models, the more personalised risk assessment derived from PRS, help identify women at higher risk of breast cancer development and enables the implementation of stratified screening and prevention approaches. This review describes the role of PRS in breast cancer risk prediction including the development of PRS and their clinical application. We have also examined the role of PRS within more well-established risk prediction models which incorporate known classic risk factors and discuss the interaction of PRS with these factors and their capacity to predict breast cancer subtypes. Before PRS can be implemented on a population-wide scale, there are several challenges that must be addressed. Perhaps the most pressing of these is the use of PRS in women of non-White European origin, where PRS have been shown to have attenuated risk prediction both in discrimination and calibration. We discuss progress in developing and applying PRS in non-white European populations. PRS represent a significant advance in breast cancer risk prediction and their further development will undoubtedly enhance personalisation.

Indexed as

Breast NeoplasmsFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideRisk AssessmentRisk FactorsBreastCancerPolygenicPredictionPreventionRiskScoresscreening

Identifiers

PMID36646003
PMCPMC9982311
OpenAlexW4313898012

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.