Evidence map›Paper›PMID 41526671›Full record

ArticleEuropean journal of human genetics : EJHG2026

Performance of different polygenic risk scores for breast cancer risk prediction: in-depth evaluations across large UK and Australian cohorts.

Hamzeh M Tanha, Matthew H Law, Nathan Ingold, Catherine M Olsen, Nirmala Pandeya, Roger L Milne, Robert J MacInnis, David C Whiteman, Anne E Cust, Julia Steinberg

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European journal of human genetics : EJHG, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. PRS-BCJournal of medical genetics · 2026
    Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Hamzeh M TanhaThe Daffodil Centre, The University of Sydney, and Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0003-0818-3481
Matthew H LawStatistical Genetics, Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Nathan IngoldStatistical Genetics, Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Catherine M OlsenDepartment of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Nirmala PandeyaDepartment of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
Roger L MilneCancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.ORCID 0000-0001-5764-7268
Robert J MacInnis *Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.
David C Whiteman *Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.ORCID 0000-0003-2563-9559
Anne E Cust *The Daffodil Centre, The University of Sydney, and Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-5331-6370
Julia Steinberg *The Daffodil Centre, The University of Sydney, and Cancer Council NSW, Sydney, NSW, Australia. Julia.steinberg@sydney.edu.au.ORCID 0000-0002-0585-2312

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polygenic risk scores (PGS) have the potential to support enhanced, risk-based screening for breast cancer. Previous studies for many diseases found that genome-wide PGS (GW-PGS) outperform PGS derived by applying hard GWAS significance thresholds. To support future breast cancer risk predictions, we compared the predictive performance of two existing PGS (including PGS313, a leading hard-thresholding PGS) and five newly developed GW-PGS (applying different methods to recent GWAS). We evaluated the performance of PGS Z-scores and of predicted 5-year absolute breast cancer risks based on age alone or age and PGS, across three large cohorts from the UK (UK Biobank) and Australia (QSkin, Melbourne Collaborative Cohort Study). Performance was assessed using discrimination (AUC) and calibration metrics, with dedicated evaluations for European, South Asian and African genetic ancestry groups, different age groups and for UKB, by pre-baseline mammogram screening history. Z-scores from three GW-PGS (LDpred2, PRS-CS, PRS-CS

Indexed as

Breast NeoplasmsGenetic Risk ScoreMultifactorial InheritanceAdultAgedAustraliaCohort StudiesFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMiddle AgedUnited Kingdom

Identifiers

PMID41526671
PMCPMC12858958

What OpenQuestion holds

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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.