Maj-Britt Jensen1, Torsten O Nielsen2, Ann S Knoop3, Anne-Vibeke Laenkholm4, Eva Balslev5, Bent Ejlertsen1,3. 1. a Danish Breast Cancer Cooperative Group (DBCG) , Secretariat and Statistical Office, Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark. 2. b Department of Pathology and Laboratory Medicine , University of British Columbia , Vancouver , Canada. 3. c Department of Oncology , Rigshospitalet, Copenhagen University Hospital , Copenhagen , Denmark. 4. d Department of Surgical Pathology , Zealand University Hospital , Slagelse , Denmark. 5. e Department of Pathology , Herlev University Hospital , Herlev , Denmark.
Abstract
BACKGROUND: Following loco-regional treatment for early breast cancer accurate prognostication is essential for communicating benefits of systemic treatment. The aim of this study was to determine time to recurrence and long-term mortality rates in high risk patients according to patient characteristics and subtypes as assigned by immunohistochemistry panels. PATIENTS AND METHODS: In November 1977 through January 1983, 2862 patients with tumors larger than 5 cm or positive axillary nodes were included in the DBCG 77 trials. Archival tumor tissue from patients randomly assigned to no systemic treatment was analyzed for ER, PR, Ki67, EGFR and HER2. Intrinsic subtypes were defined as follows: Luminal A, ER or PR >0%, HER2-negative, PR >10% and Ki67 < 14%; Luminal B, ER or PR >0%, (PR ≤10% or HER2-positive or Ki67 ≥ 14%); HER2E, ER 0%, PR 0%, HER2 positive; Core basal, ER 0%, PR 0%, HER2 negative and EGFR positive. Multivariate categorical and fractional polynomials (MFP) models were used to construct prognostic subsets by clinicopathologic characteristics. RESULTS: In a multivariate model, mortality rate was significantly associated with age, tumor size, nodal status, invasion, histological type and grade, as well as subtype classification. CONCLUSIONS: With 35 years of follow-up, in this population of high-risk patients with no systemic therapy, no subgroup based on a composite prognostic score and/or molecular subtypes could be identified without excess mortality as compared to the background population.
RCT Entities:
BACKGROUND: Following loco-regional treatment for early breast cancer accurate prognostication is essential for communicating benefits of systemic treatment. The aim of this study was to determine time to recurrence and long-term mortality rates in high risk patients according to patient characteristics and subtypes as assigned by immunohistochemistry panels. PATIENTS AND METHODS: In November 1977 through January 1983, 2862 patients with tumors larger than 5 cm or positive axillary nodes were included in the DBCG 77 trials. Archival tumor tissue from patients randomly assigned to no systemic treatment was analyzed for ER, PR, Ki67, EGFR and HER2. Intrinsic subtypes were defined as follows: Luminal A, ER or PR >0%, HER2-negative, PR >10% and Ki67 < 14%; Luminal B, ER or PR >0%, (PR ≤10% or HER2-positive or Ki67 ≥ 14%); HER2E, ER 0%, PR 0%, HER2 positive; Core basal, ER 0%, PR 0%, HER2 negative and EGFR positive. Multivariate categorical and fractional polynomials (MFP) models were used to construct prognostic subsets by clinicopathologic characteristics. RESULTS: In a multivariate model, mortality rate was significantly associated with age, tumor size, nodal status, invasion, histological type and grade, as well as subtype classification. CONCLUSIONS: With 35 years of follow-up, in this population of high-risk patients with no systemic therapy, no subgroup based on a composite prognostic score and/or molecular subtypes could be identified without excess mortality as compared to the background population.
Authors: Felipe Andrés Cordero da Luz; Eduarda da Costa Marinho; Camila Piqui Nascimento; Lara de Andrade Marques; Patrícia Ferreira Ribeiro Delfino; Rafael Mathias Antonioli; Marcelo José Barbosa Silva; Rogério Agenor de Araújo Journal: Ecancermedicalscience Date: 2022-01-20
Authors: Felipe Andrés Cordero da Luz; Eduarda da Costa Marinho; Camila Piqui Nascimento; Lara de Andrade Marques; Patrícia Ferreira Ribeiro Delfino; Rafael Mathias Antonioli; Rogério Agenor de Araújo; Marcelo José Barbosa Silva Journal: Ecancermedicalscience Date: 2022-05-04