Evidence map›Paper›PMID 42405977›Full record

ReviewJournal of community genetics2026

Experiences of implementation of personalised risk estimates for breast cancer in clinical practice: a systematic review and qualitative synthesis.

N B Fennell, S Abukar, I Kuhn, P Linneker, C Wilson, M Tischkowitz, S Archer

Abstract readReview
In one paragraph

Review in Journal of community genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

N B FennellDepartment of Genomic Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK. nf381@cam.ac.uk.ORCID https://orcid.org/0000-0002-5711-6341
S AbukarSchool of Clinical Medicine, University of Cambridge, Cambridge, UK.
I KuhnMedical Library, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-2879-4020
P LinnekerSchool of Clinical Medicine, University of Cambridge, Cambridge, UK.
C WilsonDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-2047-2817
M TischkowitzDepartment of Genomic Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK.ORCID http://orcid.org/0000-0002-7880-0628
S ArcherDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-1349-7178

Funding

Cancer Research UK C22770/A31523
6 · The paper itself

Abstract

Breast cancer risk prediction tools are increasingly used in clinical practice to guide early detection, prevention, and shared decision-making. Unlike population-level screening, personalised risk estimates incorporate individual factors (family history, genetics, lifestyle, breast density), providing tailored assessments. These tools show promise for improving patient engagement and targeted prevention, but require effective implementation to ensure they enhance rather than complicate care. This review explores healthcare professionals' experiences with providing personalised breast cancer risk estimates and women's experiences of receiving them in clinical settings. Four online databases were searched for qualitative studies on the use of personalised risk estimates in clinical practice. Data were analysed using inductive thematic analysis. Seven papers were included; the majority based in the UK screening setting. Most used interview and focus-groups, with thematic analysis. Both healthcare professionals and women expressed high acceptance of personalised risk estimates. Women found the information empowering and useful for future health planning. Effective communication and prompt follow-up from healthcare professionals were crucial for positive experiences. Professionals highlighted challenges in implementation, including the need for additional healthcare professionals, safe care pathways, and technology. The studies focused on stratified breast screening, raising questions about offering less frequent screening to lower-risk women. This approach must be supported by strong evidence, and women should retain choice in screening intervals. Personalised risk estimates are favourably viewed in clinical practice, but studies mainly examined research settings. Further research is needed to understand real-world implementation, identify barriers, and optimise use across diverse clinical environments.

Indexed as

Breast cancerBreast screeningClinical implementationRisk stratificationSystematic review

Identifiers

PMID42405977
PMCPMC13337996

What Socratic 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 Socratic graph.