Ines Vasconcelos1, Afsana Hussainzada2, Stefan Berger3, Ellen Fietze3, Jörg Linke3, Friederike Siedentopf2, Winfried Schoenegg4. 1. Berlin Breast Center Kurfürstendamm, Kurfürstendamm 216, 10719 Berlin, Germany. Electronic address: ines.mv@gmail.com. 2. Martin Luther Clinic Breast Center, Caspar-Theyß-Straße 27-31, 14193 Berlin, Germany. 3. Gemeinschaftspraxis für Pathologie am Bundeswehrkrankenhaus, Scharnhorststrasse 13, 10115 Berlin, Germany. 4. Berlin Breast Center Kurfürstendamm, Kurfürstendamm 216, 10719 Berlin, Germany.
Abstract
AIMS: To evaluate how the St. Gallen intrinsic subtype classification for breast cancer surrogates predicts disease features, recurrence patterns and disease free survival. MATERIALS AND METHODS: Subtypes were classified by immunohistochemical staining according to St. Gallen subtypes classification in a 5-tyre system: luminal A, luminal B HER2-neu negative, luminal B HER2-neu positive, HER2-neu non luminal or basal-like. Data were obtained from the records of patients with invasive breast cancer treated at our institution. Recurrence data and site of first recurrence were recorded. The chi(2) test, analysis of variance, and multivariate logistic regression analysis were used to determine associations between surrogates and clinicopathologic variables. RESULTS: A total of 2.984 tumors were classifiable into surrogate subtypes. Significant differences in age, tumor size, nodal involvement, nuclear grade, multicentric/multifocal disease (MF/MC), lymphovascular invasion, and extensive intraductal component (EIC) were observed among surrogates (p < 0.0001). After adjusting for confounding factors surrogates remained predictive of nodal involvement (luminal B HER2-neu pos. OR = 1.49 p = 0.009, non-luminal HER2-neu pos. OR = 1.61 p = 0.015 and basal-like OR = 0.60, p = 0.002) while HER2-neu positivity remained predictive of EIC (OR = 3.10, p < 0.0001) and MF/MC (OR = 1.45, p = 0.02). Recurrence rates differed among the surrogates and were time-dependent (p = 0.001) and site-specific (p < 0.0001). CONCLUSION: The St. Gallen 5-tyre surrogate classification for breast cancer subtypes accurately predicts breast cancer presenting features (with emphasis on prediction of nodal involvement), recurrence patterns and disease free survival.
AIMS: To evaluate how the St. Gallen intrinsic subtype classification for breast cancer surrogates predicts disease features, recurrence patterns and disease free survival. MATERIALS AND METHODS: Subtypes were classified by immunohistochemical staining according to St. Gallen subtypes classification in a 5-tyre system: luminal A, luminal B HER2-neu negative, luminal B HER2-neu positive, HER2-neu non luminal or basal-like. Data were obtained from the records of patients with invasive breast cancer treated at our institution. Recurrence data and site of first recurrence were recorded. The chi(2) test, analysis of variance, and multivariate logistic regression analysis were used to determine associations between surrogates and clinicopathologic variables. RESULTS: A total of 2.984 tumors were classifiable into surrogate subtypes. Significant differences in age, tumor size, nodal involvement, nuclear grade, multicentric/multifocal disease (MF/MC), lymphovascular invasion, and extensive intraductal component (EIC) were observed among surrogates (p < 0.0001). After adjusting for confounding factors surrogates remained predictive of nodal involvement (luminal B HER2-neu pos. OR = 1.49 p = 0.009, non-luminal HER2-neu pos. OR = 1.61 p = 0.015 and basal-like OR = 0.60, p = 0.002) while HER2-neu positivity remained predictive of EIC (OR = 3.10, p < 0.0001) and MF/MC (OR = 1.45, p = 0.02). Recurrence rates differed among the surrogates and were time-dependent (p = 0.001) and site-specific (p < 0.0001). CONCLUSION: The St. Gallen 5-tyre surrogate classification for breast cancer subtypes accurately predicts breast cancer presenting features (with emphasis on prediction of nodal involvement), recurrence patterns and disease free survival.
Authors: Kishan R Bharadwa; Kuheli Dasgupta; Suma Mysore Narayana; C Ramachandra; Suresh M C Babu; Annapoorni Rangarajan; Rekha V Kumar Journal: Eur J Breast Health Date: 2021-12-30
Authors: Giulia Galli; Giacomo Bregni; Stefano Cavalieri; Luca Porcu; Paolo Baili; Amash Hade; Francesca Di Salvo; Milena Sant; Roberto Agresti; Massimiliano Gennaro; Secondo Folli; Maria C De Santis; Biagio Paolini; Maria L Carcangiu; Filippo de Braud; Serena Di Cosimo Journal: Breast Care (Basel) Date: 2017-12-12 Impact factor: 2.860