Journal of Clinical Oncology · 2005 · 32 citations · 18 references
MedicineOncologyBreast OncologyChemotherapyMetastasisAdjuvant ChemotherapyAdjuvant TherapyAdjuvant Clinical TrialsAnthracycline-based ChemotherapyBreast Cancer ChemotherapyBreast Cancer Risk StratificationHigh-risk Node-negative Breast CancerMitotic Activity AssessmentRandomized Clinical TrialsTreatment Benefit Interpretation
PURPOSE: We have evaluated whether the mitotic index could predict the benefit of adjuvant anthracycline-based chemotherapy in patients with early breast cancer who are eligible for adjuvant chemotherapy according to Saint Gallen guidelines. PATIENTS AND METHODS: A total of 937 patients from a single institution were included in two randomized trials that compared adjuvant anthracycline-based chemotherapy with no chemotherapy. These patients account for 83% of the overall population included in these trials. The first trial included premenopausal patients with node-negative disease, and the second one included postmenopausal patients, regardless of lymph node status. The treatment benefit was assessed according to the number of mitoses per field (x400). RESULTS: The mitotic index was assessable in 888 patients (94%). All the patients presented as either node-positive or an average-risk breast cancer according to 2003 Saint Gallen consensus conference guidelines. The 5-year overall survival rates were 91% and 87% for patients treated or not with adjuvant chemotherapy (P = .09). In patients with low/medium mitotic index (< three mitoses/field; n = 450), the 5-year overall survival rate was 95% for patients treated or not with adjuvant chemotherapy (P = .56). In patients with high mitotic index (>/= three mitoses/field; n = 438), the 5-year overall survival rates were 86% and 79% for patients treated or not treated with adjuvant chemotherapy, respectively (P = .02). CONCLUSION: A high mitotic index is associated with the efficacy of adjuvant anthracycline-based chemotherapy in patients eligible for adjuvant chemotherapy in daily practice.
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Gene expression profiling predicts clinical outcome of breast cancer
Laura van ‘t Veer, Hongyue Dai, Marc J. van de Vijver et al. · Nature · 2002 · 9.6K citations · Full text
A Gene-Expression Signature as a Predictor of Survival in Breast Cancer
Marc J. van de Vijver, Yudong D. He, Laura van ‘t Veer et al. · New England Journal of Medicine · 2002 · 6.5K citations · Full text
Medicine, Bioinformatics, Oncology +17
Jacques Bonneterre, Henri Roché, Pierre Kerbrat et al. · Journal of Clinical Oncology · 2005 · 274 citations · Full text
Medicine, Oncology, Pharmacology +17