Evidence map›Paper›PMID 41953376›Full record

ArticleInternational journal of breast cancer2026

Impact of Adjuvant Chemotherapy on Survival Outcomes in Intermediate- and High-Risk ER+/HER2- Breast Cancer Stratified by Genomic Profiling: A Meta-Analysis.

Max Seabrook, Ahamed S M Navas, Hannah-Maria Francis, Zina Aladili, Ahsan Rao

Abstract read
In one paragraph

Article in International journal of breast cancer, 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. Article
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

5 authors.

Max SeabrookGeneral Surgery, Royal Cornwall Hospitals NHS Trust, Truro, UK, rcht.nhs.uk.ORCID https://orcid.org/0000-0002-9447-624X
Ahamed S M NavasDepartment of Surgery, Mid and South Essex NHS Foundation Trust, Basildon, UK.ORCID https://orcid.org/0009-0007-3668-1118
Hannah-Maria FrancisDepartment of Surgery, Mid and South Essex NHS Foundation Trust, Basildon, UK.ORCID https://orcid.org/0009-0004-6185-5720
Zina AladiliDepartment of Surgery, Mid and South Essex NHS Foundation Trust, Basildon, UK.ORCID https://orcid.org/0000-0001-6981-5986
Ahsan RaoDepartment of Surgery, Mid and South Essex NHS Foundation Trust, Basildon, UK.ORCID https://orcid.org/0000-0001-8728-8729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Genomic recurrence score (RS) testing guides adjuvant treatment decisions in oestrogen receptor-positive, HER2-negative early breast cancer. Evidence remains mixed regarding the survival benefit of adding chemotherapy to endocrine therapy (CET) in intermediate- and high-risk RS groups. This meta-analysis assessed overall mortality, breast cancer-specific mortality (BCSM) and recurrence outcomes according to RS category. Methods: Medline, Embase, PubMed and Google Scholar were searched from 1 January to 20 June 2024 for studies reporting outcomes in ER+/HER2- patients treated with CET versus endocrine therapy (ET) alone, stratified by RS. Random-effects modelling generated pooled risk ratios (RRs) with 95% confidence intervals (CIs). Heterogeneity was evaluated using Results: Fifteen studies comprising 630,741 patients were included. In the high-risk group (RS > 25), CET significantly reduced 5-year overall mortality compared with ET (5.9% vs. 7.9%; RR 0.57, 95% CI 0.45-0.72; Conclusion: Chemotherapy provides a clear survival benefit in high-risk RS groups, including node-negative patients, whereas intermediate-risk groups show limited benefit. These findings support selective use of CET guided by genomic risk stratification.

Identifiers

PMID41953376
PMCPMC13053945

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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.