External validation of Adjuvant! Online breast cancer prognosis tool. Prioritising recommendations for improvement

David Hajage, Yann de Rycke, Marc Bollet, Alexia Savignoni, Martial Caly, Jean-Yves Pierga, Hugo M Horlings, Marc J Van de Vijver, Anne Vincent-Salomon, Brigitte Sigal-Zafrani, Claire Senechal, Bernard Asselain, Xavier Sastre, Fabien Reyal, David Hajage, Yann de Rycke, Marc Bollet, Alexia Savignoni, Martial Caly, Jean-Yves Pierga, Hugo M Horlings, Marc J Van de Vijver, Anne Vincent-Salomon, Brigitte Sigal-Zafrani, Claire Senechal, Bernard Asselain, Xavier Sastre, Fabien Reyal

Abstract

Background: Adjuvant! Online is a web-based application designed to provide 10 years survival probability of patients with breast cancer. Several predictors have not been assessed in the original Adjuvant! Online study. We provide the validation of Adjuvant! Online algorithm on two breast cancer datasets, and we determined whether the accuracy of Adjuvant! Online is improved with other well-known prognostic factors.

Patients and methods: The French data set is composed of 456 women with early breast cancer. The Dutch data set is composed of 295 women less than 52 years of age. Agreement between observation and Adjuvant! Online prediction was checked, and logistic models were performed to estimate the prognostic information added by risk factors to Adjuvant! Online prediction.

Results: Adjuvant! Online prediction was overall well-calibrated in the French data set but failed in some subgroups of such high grade and HER2 positive patients. HER2 status, Mitotic Index and Ki67 added significant information to Adjuvant! Online prediction. In the Dutch data set, the overall 10-year survival was overestimated by Adjuvant! Online, particularly in patients less than 40 years old.

Conclusion: Adjuvant! Online needs to be updated to adjust overoptimistic results in young and high grade patients, and should consider new predictors such as Ki67, HER2 and Mitotic Index.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Mean predicted versus observed survival.
Figure 1. Mean predicted versus observed survival.
French population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The grey thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.
Figure 2. Mean predicted versus observed survival.
Figure 2. Mean predicted versus observed survival.
Dutch population. The data were divided into 5% intervals for the predicted values. Observed percentages were calculated for each interval subset and were plotted against the average predicted values. The thin line of slope = 1 and intercept = 0 corresponds to a perfect agreement between observed and predicted values.
Figure 3. Difference (Δ) between observed outcome…
Figure 3. Difference (Δ) between observed outcome and Adjuvant! Online prediction in three other major confirmation studies , , .

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Source: PubMed

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