ArticleBMC cancer2013
An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain.
Article in BMC cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Development and performance of female breast cancer incidence risk prediction models: a systematic review and meta-analysis.Annals of medicine · 2025Pooled it
- Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review.Cancers · 2023Review
- Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification.Journal of the National Cancer Institute · 2020Article
- Evaluation of health benefits and harms of the breast cancer screening programme in the Basque Country using discrete event simulation.BMC cancer · 2015Article
- Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2014Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk.
methodsWe included 13,760 women who were first-time participants in the Sabadell-Cerdanyola Breast Cancer Screening Program, in Catalonia, Spain. Projections of risk were obtained at three and five years for invasive cancer using the Gail, Chen and Barlow models. Incidence and mortality data were obtained from the Catalan registries. The calibration and discrimination of the models were assessed using the Hosmer-Lemeshow C statistic, the area under the receiver operating characteristic curve (AUC) and the Harrell's C statistic.
resultsThe Gail and Chen models showed good calibration while the Barlow model overestimated the number of cases: the ratio between estimated and observed values at 5 years ranged from 0.86 to 1.55 for the first two models and from 1.82 to 3.44 for the Barlow model. The 5-year projection for the Chen and Barlow models had the highest discrimination, with an AUC around 0.58. The Harrell's C statistic showed very similar values in the 5-year projection for each of the models. Although they passed the calibration test, the Gail and Chen models overestimated the number of cases in some breast density categories.
conclusionsThese models cannot be used as a measure of individual risk in early detection programs to customize screening strategies. The inclusion of longitudinal measures of breast density or other risk factors in joint models of survival and longitudinal data may be a step towards personalized early detection of BC.
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