Alberto Gallardo1, Barbara Garcia-Valdecasas2, Paola Murata3, Rolando Teran4, Laura Lopez4, Agusti Barnadas3, Enrique Lerma4. 1. Department of Pathology, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Sant Quinti 87-89, 08041, Barcelona, Spain. agallardoa@santpau.cat. 2. Department of Gynaecology and Obstetrics, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. 3. Department of Medical Oncology, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Barcelona, Spain. 4. Department of Pathology, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Sant Quinti 87-89, 08041, Barcelona, Spain.
Abstract
INTRODUCTION: Ki67 is a prognostic marker in early breast cancer, but its real usefulness remains controversial. The standard cut-off values for Ki67 have not been universally accepted and different values may be used depending on the type of biopsy (fine needle biopsy versus surgical specimen biopsy). The objective of this study was to evaluate the prognostic significance of Ki67 and to determine the most accurate prognostic cut-off. MATERIALS AND METHODS: 495 tissue samples from patients with luminal tumours who underwent breast surgery between 2005 and 2011 were collected from the Department of Pathology at Hospital de la Santa Creu i Sant Pau, Barcelona. Patients with stage IV, HER2-positive tumours or triple-negative breast carcinoma were excluded from the study. Pathology data including tumour grading and ki67 percentage were obtained retrospectively from clinical records. In all cases, the percentage of ki67 was evaluated in fine needle biopsies. RESULTS: In the multivariate analysis, Ki67 as a continuous variable was associated with poor overall survival (OS) and cancer-specific survival (CSS) (OS p = 0.0001, HR 1.037, CI 1.014-1.059; CSS p = 0.0001, HR 1.063, CI 1.031-1.096) (Cox regression model). CSS was poor when associated with a KI67 cut-off point >14% (p = 0.013, HR 14.85; CI 1.074-120.53) (Cox regression model). Disease-free survival (DFS) was not associated with Ki67 CONCLUSIONS: Prognosis of luminal breast carcinoma can be predicted using Ki67 as a continuous variable and a standard cut-off value of 14%. Information about the specimen type used to determine ki67 should be recorded in the pathological report.
INTRODUCTION: Ki67 is a prognostic marker in early breast cancer, but its real usefulness remains controversial. The standard cut-off values for Ki67 have not been universally accepted and different values may be used depending on the type of biopsy (fine needle biopsy versus surgical specimen biopsy). The objective of this study was to evaluate the prognostic significance of Ki67 and to determine the most accurate prognostic cut-off. MATERIALS AND METHODS: 495 tissue samples from patients with luminal tumours who underwent breast surgery between 2005 and 2011 were collected from the Department of Pathology at Hospital de la Santa Creu i Sant Pau, Barcelona. Patients with stage IV, HER2-positive tumours or triple-negative breast carcinoma were excluded from the study. Pathology data including tumour grading and ki67 percentage were obtained retrospectively from clinical records. In all cases, the percentage of ki67 was evaluated in fine needle biopsies. RESULTS: In the multivariate analysis, Ki67 as a continuous variable was associated with poor overall survival (OS) and cancer-specific survival (CSS) (OS p = 0.0001, HR 1.037, CI 1.014-1.059; CSS p = 0.0001, HR 1.063, CI 1.031-1.096) (Cox regression model). CSS was poor when associated with a KI67 cut-off point >14% (p = 0.013, HR 14.85; CI 1.074-120.53) (Cox regression model). Disease-free survival (DFS) was not associated with Ki67 CONCLUSIONS: Prognosis of luminal breast carcinoma can be predicted using Ki67 as a continuous variable and a standard cut-off value of 14%. Information about the specimen type used to determine ki67 should be recorded in the pathological report.
Entities:
Keywords:
Breast carcinoma; KI67; Multivariate analysis; Prognosis
Authors: Maria Cristina Leonardi; Ida Rosalia Scognamiglio; Barbara Alicja Jereczek-Fossa; Giovanni Corso; Patrick Maisonneuve; Samantha Dicuonzo; Damaris Patricia Rojas; Maria Alessia Zerella; Anna Morra; Marianna Alessandra Gerardi; Mattia Zaffaroni; Alessandra De Scalzi; Antonia Girardi; Francesca Magnoni; Emilia Montagna; Cristiana Iuliana Fodor; Viviana Enrica Galimberti; Paolo Veronesi; Roberto Orecchia; Roberto Pacelli Journal: Breast Cancer Res Treat Date: 2021-04-27 Impact factor: 4.872