Evidence map›Paper›PMID 42862556›Full record

ArticleJAMA network open2026

Immunohistochemistry vs Molecular Breast Cancer Subtyping Among African Populations.

Shahin Sayed, Li Feng, Hela Koka, Manel Haj Mansour, Difei Wang, Maria Brown, Kristine Jones, Margaret Maina, Veronica Ngundo, Alfred Mburu Githuka and 14 more

Abstract read
In one paragraph

Article in JAMA network open, 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

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

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.

Shahin SayedAga Khan University Hospital, Nairobi, Kenya.
Li FengDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Hela KokaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Manel Haj MansourAga Khan University Hospital, Nairobi, Kenya.
Difei WangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Maria BrownDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Kristine JonesDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Margaret MainaAga Khan University Hospital, Nairobi, Kenya.
Veronica NgundoAga Khan University Hospital, Nairobi, Kenya.
Alfred Mburu GithukaAga Khan University Hospital, Nairobi, Kenya.
Zaitun AjuogaAga Khan University Hospital, Nairobi, Kenya.
Shaoqi FanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Amber N HursonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Xing HuaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Petra LenzDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Rosemary Wangari KamauAIC Kijabe Hospital, Kijabe, Kenya.
Beryl Akinyi OoroAIC Kijabe Hospital, Kijabe, Kenya.
Francis MakokhaMount Kenya University, Nairobi, Kenya.
Stefan AmbsCenter for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Aaron M RozeboomDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Amy HutchinsonDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Belynda HicksDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Mustapha AbubakarDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Xiaohong R YangDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Breast cancer subtyping based on immunohistochemistry (IHC) guides systemic therapy where gene expression profiling assays are unavailable, yet its validity against molecular reference standards remains poorly characterized in African populations, where laboratory infrastructure and access to pathology services are limited. Objective: To evaluate concordance between IHC-based breast cancer subtyping and PAM50 intrinsic subtypes in East and West African populations and identify resource-appropriate strategies to improve classification. Design, Setting, and Participants: This cross-sectional study included Kenyan (diagnosed 2012-2022) and Ghanaian women (diagnosed 2013-2015) with invasive breast cancer, from whom formalin-fixed, paraffin-embedded tumor specimens were collected during the same periods. Gene expression profiling and data analyses were performed between April 2020 and August 2026 for both cohorts. Exposures: Tumor subtyping using standard IHC markers (estrogen receptor [ER], progesterone receptor [PR], and ERBB2 status and Ki-67) and histologic grade vs PAM50 intrinsic subtyping derived from a gene expression panel. Main Outcomes and Measures: Concordance between IHC-based and PAM50 intrinsic subtypes was assessed using Cohen κ statistics, with sensitivity and specificity calculated against PAM50. Results: Among 460 women in Kenya with breast cancer (mean [SD] age at diagnosis, 50.3 [12.5] years), 224 (49.4%) had grade 3 disease and 148 (42.3%) had stage III or IV tumors. A total of 451 women in Ghana with breast cancer (mean [SD] age, 49.9 [12.0] years; 317 [75.1%] with grade 3 disease) were enrolled as a validation cohort. PAM50 classified patients' tumors as luminal A (201 tumors [43.7%]), luminal B (82 tumors [17.8%]), ERBB2-enriched (50 tumors [10.9%]), basal-like (99 tumors [21.5%]), and normal-like (28 tumors [6.1%]). Concordance between IHC and PAM50 was highest for basal-like tumors (sensitivity ranging from 73.3% [95% CI, 61.9%-82.9%] to 79.6% [95% CI, 70.3%-87.1%]; specificity ranging from 96.9% [95% CI, 93.9%-98.6%] to 97.3% [95% CI, 94.9%-98.7%]) and moderate for ERBB2-enriched tumors (sensitivity was 50.0% across all schemes, with 95% CIs ranging from 33.8%-66.2% to 35.5%-64.5%; specificity ranging from 97.6% [95% CI, 95.6%-98.9%] to 97.9% [95% CI, 95.6%-99.2%]). Luminal subtypes showed substantial misclassification using ER, PR, and ERBB2 status alone. Incorporation of Ki-67 (≥20%) or histologic grade improved discrimination between luminal A and luminal B tumors, increasing luminal B classification from 12.2% (95% CI, 8.5%-16.7%) to 41.2% (95% CI, 35.2%-47.4%), even when PR status was excluded from the panel. Findings were independently validated in women with breast cancer from Ghana. Conclusions and Relevance: In this cross-sectional study of African breast cancer populations, standard IHC markers performed well for basal-like tumors but frequently misclassified luminal subtypes without proliferation markers. When testing was constrained, proliferation markers contributed more to molecular approximation than PR, with histologic grade providing useful information when Ki-67 was unavailable. These findings support tiered, resource-adapted classification where molecular assays are inaccessible.

Indexed as

Breast NeoplasmsImmunohistochemistryAdultBiomarkers, TumorCross-Sectional StudiesErb-b2 Receptor Tyrosine KinasesFemaleGhanaHumansKenyaMiddle AgedReceptors, EstrogenReceptors, ProgesteroneSensitivity and SpecificityWest African PeopleBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, EstrogenReceptors, Progesterone

Identifiers

PMID42862556
PMCPMC13659570

What Socratic 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 Socratic graph.