Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models

E. Laas, P. Mallon, M. Delomenie, Vincent Gardeux, J. Y. Pierga, P. Cottu, F. Lerebours, D. Stevens, R. Rouzier, F. Reyal

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Abstract

BACKGROUND: Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level.

METHODS: We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction.

RESULTS: Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95% CI 0.71-0.77) for the Cancermath.net model and 0.72 (95% CI 0.69-0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90% with a median score dispersion at 0.08 (range 0.06-0.10). Dispersion, however, reached 30% for the subgroups with a predicted survival between 10 and 50%.

CONCLUSION: This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups.

Original languageEnglish (US)
Pages (from-to)912-917
Number of pages6
JournalBritish Journal of Cancer
Volume112
Issue number5
DOIs
StatePublished - Mar 3 2015

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Breast Neoplasms
Survival
Calibration
Hormones
Population
Datasets

ASJC Scopus subject areas

  • Medicine(all)

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Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models. / Laas, E.; Mallon, P.; Delomenie, M.; Gardeux, Vincent; Pierga, J. Y.; Cottu, P.; Lerebours, F.; Stevens, D.; Rouzier, R.; Reyal, F.

In: British Journal of Cancer, Vol. 112, No. 5, 03.03.2015, p. 912-917.

Research output: Contribution to journalArticle

Laas, E, Mallon, P, Delomenie, M, Gardeux, V, Pierga, JY, Cottu, P, Lerebours, F, Stevens, D, Rouzier, R & Reyal, F 2015, 'Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models', British Journal of Cancer, vol. 112, no. 5, pp. 912-917. https://doi.org/10.1038/bjc.2014.641
Laas, E. ; Mallon, P. ; Delomenie, M. ; Gardeux, Vincent ; Pierga, J. Y. ; Cottu, P. ; Lerebours, F. ; Stevens, D. ; Rouzier, R. ; Reyal, F. / Are we able to predict survival in ER-positive HER2-negative breast cancer? A comparison of web-based models. In: British Journal of Cancer. 2015 ; Vol. 112, No. 5. pp. 912-917.
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abstract = "BACKGROUND: Several prognostic models have been proposed and demonstrated to be predictive of survival outcomes in breast cancer. In the present article, we assessed whether three of these models are comparable at an individual level.METHODS: We used a large data set (n=965) of women with hormone receptor-positive and HER2-negative early breast cancer from the public data set of the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. We compared the overall performance of three validated web-based models: Adjuvant!, CancerMath.net and PREDICT, and we assessed concordance of these models in 10-year survival prediction.RESULTS: Discrimination performances of the three calculators to predict 10-year survival were similar for the Adjuvant! Model, 0.74 (95{\%} CI 0.71-0.77) for the Cancermath.net model and 0.72 (95{\%} CI 0.69-0.75) for the PREDICT model). Calibration performances, assessed graphically, were satisfactory. Predictions were concordant and stable in the subgroup, with a predicted survival higher than 90{\%} with a median score dispersion at 0.08 (range 0.06-0.10). Dispersion, however, reached 30{\%} for the subgroups with a predicted survival between 10 and 50{\%}.CONCLUSION: This study revealed that the three web-based predictors equally perform well at the population level, but exhibit a high degree of discordance in the intermediate and poor prognosis groups.",
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AU - Gardeux, Vincent

AU - Pierga, J. Y.

AU - Cottu, P.

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