ArticleData in brief2024
A dataset of breast cancer risk factors in Cuban women: Epidemiological evidence from Havana.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- Machine Learning and Explainable AI for Breast Cancer Patient Prioritization: An Intelligent Decision-Support Framework.Bioengineering (Basel, Switzerland) · 2026Article
- Data preparation method for machine learning-based breast cancer risk prediction: A Cuban case study.MethodsX · 2025Article
- Analysis of the time to breast cancer diagnosis in Cuba: an observational study.BMC public health · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This dataset compiles breast cancer risk factors from 1697 Cuban women who attended consultations at the Hospital Universitario Clínico-Quirúrgico Comandante Manuel Fajardo in Havana, Cuba. The data were collected to develop a breast cancer risk estimation model specifically tailored to the Cuban population. The dataset includes 23 variables encompassing internationally recognized risk factors such as family history of breast cancer, lifestyle habits, demographic characteristics, and clinical outcomes. The data were extracted from electronic records and anonymized to protect patient privacy, in compliance with the principles of the Declaration of Helsinki and with the approval of the hospital's scientific and ethics committees. This dataset can be employed in the development of predictive models and in comparative studies of risk factors across different populations. It is important to note that the data originate from a single hospital, which may limit their representativeness at the national level.
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Registered trials
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