ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2025
Unveiling the Stroma: Reproductive Factors and the Tumor Microenvironment in African Breast Cancer.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Comment on
Authors and funding
1 author.
Funding
Abstract
Breast cancer incidence rates for Black and White women in the United States have recently converged, with mortality rates remaining disproportionately higher for Black women. This disparity is more pronounced given the higher prevalence of hormone receptor-negative tumors in women of African ancestry, tumors which are more aggressive and harder to treat. Abubakar and colleagues' analysis of 792 breast cancer cases from the Ghana Breast Health Study offers new insights into the stromal tumoral microenvironment in sub-Saharan African women. Using machine learning techniques, tumor-associated stromal cellular density was associated with more aggressive tumors, higher tumor grade, and parity versus nulliparity, whereas breastfeeding did not significantly affect stromal characteristics. This commentary spotlights the innovative combination of traditional diagnostic methods, such as hematoxylin and eosin staining, with machine learning techniques within the Ghana Breast Health Study as a promising approach for improving breast cancer prognostication in low-resource settings. Moreover, this commentary underscores the need for inclusive, equity-driven research approaches that consider biological factors, host factors, and social and structural drivers of health when examining breast cancer disparities. See related article by Abubakar et al., p. 462.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.