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01.12.2013 | Research article | Ausgabe 1/2013 Open Access

BMC Cancer 1/2013

An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

Zeitschrift:
BMC Cancer > Ausgabe 1/2013
Autoren:
Arantzazu Arrospide, Carles Forné, Montse Rué, Núria Torà, Javier Mar, Marisa Baré
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1471-2407-13-587) contains supplementary material, which is available to authorized users.

Competing interest

The authors declare that they have no competing interest in the research.

Authors’ contributions

MB and MR conceived and coordinated the study, discussed the results and reviewed the manuscript. AA and CF performed the statistical analysis and drafted the manuscript. JM and NT discussed the results and reviewed the manuscript. All authors read and approved the final manuscript.

Abstract

Background

The aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk.

Methods

We 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.

Results

The 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.

Conclusions

These 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.
Zusatzmaterial
Additional file 1: Table S1: Incidence rates of breast cancer and mortality rates from other causes in Catalonia. (DOCX 13 KB)
12885_2013_4193_MOESM1_ESM.docx
Literatur
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