Evidence map›Paper›PMID 42016302›Full record

ArticleESMO real world data and digital oncology2026

Multi-site validation of an AI-based biomarker test for determining ER, PR, and HER2 status from H&E-stained breast cancer slides.

F Ntelemis, S Wolf, C Bass, A Geraldes, J Schmidt, N Kumar, S Singhal, D Mehrotra, A Marcia, J Blackwood and 14 more

Abstract read
In one paragraph

Article in ESMO real world data and digital oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

24 authors.

F NtelemisPanakeia Technologies, Cambridge, UK.
S WolfPanakeia Technologies, Cambridge, UK.
C BassPanakeia Technologies, Cambridge, UK.
A GeraldesPanakeia Technologies, Cambridge, UK.
J SchmidtPanakeia Technologies, Cambridge, UK.
N KumarPanakeia Technologies, Cambridge, UK.
S SinghalPanakeia Technologies, Cambridge, UK.
D MehrotraPanakeia Technologies, Cambridge, UK.
A MarciaPanakeia Technologies, Cambridge, UK.
J BlackwoodPanakeia Technologies, Cambridge, UK.
O MaiquesBarts Cancer Institute, Queen Mary University of London, London, UK.
A IronsideDepartment of Pathology, NHS Lothian, Western General Hospital, Edinburgh, UK.
J J StavesDepartment of Histopathology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
D LeffDepartment of Histopathology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
I H UmSchool of Medicine, University of St Andrews, St Andrews, UK.
J LoaneNHS Greater Glasgow and Clyde, Glasgow, UK.
G BrysonNHS Greater Glasgow and Clyde, Glasgow, UK.
D J HarrisonDepartment of Pathology, NHS Lothian, Western General Hospital, Edinburgh, UK.
S A KhurramDepartment of Histopathology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
L SparyWales Cancer Biobank, Cardiff University, Cardiff, UK.
R ClarksonWales Cancer Biobank, Cardiff University, Cardiff, UK.
J N KatherElse Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany.
P PandyaPanakeia Technologies, Cambridge, UK.
S ArslanPanakeia Technologies, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth factor receptor 2 (HER2) is essential for managing breast cancer (BC) patients, as these biomarkers guide targeted therapies. Traditional methods such as immunohistochemistry (IHC) and Materials and methods: PPB was validated on a large, diverse cohort of 3138 unique BC samples from five sites across the UK and United States. The validation included both biopsy and resection specimens, digitally scanned using multiple imaging platforms. Standard performance characteristics were assessed by comparison with IHC and ISH reference assays. Results: PPB consistently demonstrated high performance across multiple cohorts, confirming its effectiveness for establishing the status of ER/PR and assessing HER2 negativity for BC patients. HER2 achieved an average sensitivity of 90.6% (±0.6) and a concordance of 93.7% (±7.8%) when determining the negative status. For ER, we measured an overall sensitivity and specificity of 98.2% (±0.3%) and 62.0% (±7.3%), averaged over all sites, respectively. For PR the averaged sensitivity and specificity across all sites were 97.9% (±1.0%) and 45.7% (±1.6%), respectively. Conclusions: Integrating PPB into routine clinical workflows could enable rapid and accurate assessment of BC biomarkers, improving access to targeted therapies and enhancing clinical decision making.

Indexed as

artificial intelligencebreast cancerdiagnostic biomarkersdigital pathologyprecision medicine

Identifiers

PMID42016302
PMCPMC13094427

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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.