ArticleScientific reports2024
Development of a model to predict the age at breast cancer diagnosis in a global population.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mastitis as a risk factor for breast cancer: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Beyond Biology: Uncovering Structural and Sociocultural Predictors of Breast Cancer Incidence Worldwide.Current oncology (Toronto, Ont.) · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Knowing the mean age at diagnosis of breast cancer (BC) in a country is important for setting up an efficient BC screening program. The aim of this study was to develop and validate a model to predict the mean age at diagnosis of BC at the country level. To develop the model, we used the CI5plus database from the IARC, which contains incidence data for 122 selected populations for a minimum of 15 consecutive years from 1993 to 2012 and data from the World Bank. The standard model was fitted with a generalized linear model with the age of the population, growth domestic product per capita (GDPPC) and fertility rate as fixed effects and continent as a random effect. The model was validated in registries of the Cancer Incidence in Five Continents that are not included in the CI5plus database (1st validation set: 1950-2012) and in the most recently released volume (2nd validation set: 2013-2017). The intercept of the model was 30.9 (27.8-34.1), and the regression coefficients for population age, GDPPC and fertility rate were 0.55 (95% CI: 0.53-0.58, p < 0.001), 0.46 (95% CI: 0.26-0.67, p < 0.001) and 1.62 (95% CI: 1.42-1.88, p < 0.001), respectively. The marginal R
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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.