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Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial

Schmidt, M. ; Victor, A. ; Bratzel, D. ; Boehm, D. ; Cotarelo, C. ; Lebrecht, A. ; Siggelkow, W. ; Hengstler, J. G. ; Elsäßer, A. ; Gehrmann, M. ; Lehr, H. -A ; Koelbl, H. ; von Minckwitz, G. ; Harbeck, N. ; Thomssen, C.

In: Annals of Oncology, 2008, vol. 20, no. 2, p. 258-264

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    Titre
    • Long-term outcome prediction by clinicopathological risk classification algorithms in node-negative breast cancer—comparison between Adjuvant!, St Gallen, and a novel risk algorithm used in the prospective randomized Node-Negative-Breast Cancer-3 (NNBC-3) trial
    Auteur
    • Schmidt, M.. Department of Obstetrics and Gynecology
    • Victor, A.. Department of Medical Biometrics, Epidemiology and Informatics
    • Bratzel, D.. Department of Obstetrics and Gynecology
    • Boehm, D.. Department of Obstetrics and Gynecology
    • Cotarelo, C.. Department of Pathology, Johannes Gutenberg University, Mainz
    • Lebrecht, A.. Department of Obstetrics and Gynecology
    • Siggelkow, W.. Department of Obstetrics and Gynecology
    • Hengstler, J. G.. Leibniz Research Centre for Working Environment and Human Factors (IfADo) at the Dortmund University of Technology, Dortmund
    • Elsäßer, A.. Department of Medical Biometrics, Epidemiology and Informatics
    • Gehrmann, M.. Siemens Medical Solutions, Diagnostics GmbH, Leverkusen, Germany
    • Lehr, H. -A. Institute of Pathology, Centre Hospitalier Universite Vaudois, University of Lausanne, Switzerland
    • Koelbl, H.. Department of Obstetrics and Gynecology
    • von Minckwitz, G.. German Breast Group, Neu-Isenburg and Goethe University, Frankfurt
    • Harbeck, N.. Department of Obstetrics and Gynecology, Technical University of Munich, Munich
    • Thomssen, C.. Department of Gynecology, University Hospital, Halle/Saale, Germany
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Annals of Oncology, 2008, vol. 20, no. 2, p. 258-264. Oxford University Press
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:289590
    Summary
    Background: Defining risk categories in breast cancer is of considerable clinical significance. We have developed a novel risk classification algorithm and compared its prognostic utility to the Web-based tool Adjuvant! and to the St Gallen risk classification. Patients and methods: After a median follow-up of 10 years, we retrospectively analyzed 410 consecutive node-negative breast cancer patients who had not received adjuvant systemic therapy. High risk was defined by any of the following criteria: (i) age <35 years, (ii) grade 3, (iii) human epithelial growth factor receptor-2 positivity, (iv) vascular invasion, (v) progesterone receptor negativity, (vi) grade 2 tumors >2 cm. All patients were also characterized using Adjuvant! and the St Gallen 2007 risk categories. We analyzed disease-free survival (DFS) and overall survival (OS). Results: The Node-Negative-Breast Cancer-3 (NNBC-3) algorithm enlarged the low-risk group to 37% as compared with Adjuvant! (17%) and St Gallen (18%), respectively. In multivariate analysis, both Adjuvant! [P = 0.027, hazard ratio (HR) 3.81, 96% confidence interval (CI) 1.16-12.47] and the NNBC-3 risk classification (P = 0.049, HR 1.95, 95% CI 1.00-3.81) significantly predicted OS, but only the NNBC-3 algorithm retained its prognostic significance in multivariate analysis for DFS (P < 0.0005). Conclusion: The novel NNBC-3 risk algorithm is the only clinicopathological risk classification algorithm significantly predicting DFS as well as OS