Megan A Healey1,2,3, Kelly A Hirko4, Andrew H Beck5, Laura C Collins6, Stuart J Schnitt7, A Heather Eliassen1,2, Michelle D Holmes1,2, Rulla M Tamimi1,2, Aditi Hazra8,9. 1. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 2. Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA. 3. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA. 4. Department of Epidemiology and Biostatistics, College of Human Medicine, Traverse City Campus, Michigan State University, East Lansing, MI, USA. 5. PathAI, Inc, Cambridge, MA, USA. 6. Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA. 7. Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 8. Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA. ahazra@bwh.harvard.edu. 9. Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. ahazra@bwh.harvard.edu.
Abstract
PURPOSE: Ki67 is a proliferation marker commonly assessed by immunohistochemistry in breast cancer, and it has been proposed as a clinical marker for subtype classification, prognosis, and prediction of therapeutic response. However, the clinical utility of Ki67 is limited by the lack of consensus on the optimal cut point for each application. METHODS: We assessed Ki67 by immunohistochemistry using Definiens digital image analysis (DIA) in 2653 cases of incident invasive breast cancer diagnosed in the Nurses' Health Study from 1976 to 2006. Ki67 was scored as continuous percentage of positive tumor cells, and dichotomized at various cut points. Multivariable hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression models for distant recurrence, breast cancer-specific mortality and overall mortality in relation to luminal subtypes defined with various Ki67 cut points, adjusting for breast cancer prognostic factors, clinico-pathologic features and treatment. RESULTS: DIA was highly correlated with manual scoring of Ki67 (Spearman correlation ρ = 0.86). Mean Ki67 score was higher in grade-defined luminal B (12.6%), HER2-enriched (17.9%) and basal-like (20.6%) subtypes compared to luminal A (8.9%). In multivariable-adjusted models, luminal B tumors had higher breast cancer-specific mortality compared to luminal A cancer classified using various cut points for Ki67 positivity including the 14% cut point routinely reported in the literature (HR 1.38, 95% CI 1.11-1.72, p = 0.004). There was no significant difference in clinical outcomes for ER- tumors according to Ki67 positivity defined at various cut points. CONCLUSIONS: Assessment of Ki67 in breast tumors by DIA was a robust and quantitative method. Results from this large prospective cohort study provide support for the clinical relevance of using Ki67 at the 14% cut point for luminal subtype classification and breast cancer prognosis.
PURPOSE: Ki67 is a proliferation marker commonly assessed by immunohistochemistry in breast cancer, and it has been proposed as a clinical marker for subtype classification, prognosis, and prediction of therapeutic response. However, the clinical utility of Ki67 is limited by the lack of consensus on the optimal cut point for each application. METHODS: We assessed Ki67 by immunohistochemistry using Definiens digital image analysis (DIA) in 2653 cases of incident invasive breast cancer diagnosed in the Nurses' Health Study from 1976 to 2006. Ki67 was scored as continuous percentage of positive tumor cells, and dichotomized at various cut points. Multivariable hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression models for distant recurrence, breast cancer-specific mortality and overall mortality in relation to luminal subtypes defined with various Ki67 cut points, adjusting for breast cancer prognostic factors, clinico-pathologic features and treatment. RESULTS: DIA was highly correlated with manual scoring of Ki67 (Spearman correlation ρ = 0.86). Mean Ki67 score was higher in grade-defined luminal B (12.6%), HER2-enriched (17.9%) and basal-like (20.6%) subtypes compared to luminal A (8.9%). In multivariable-adjusted models, luminal B tumors had higher breast cancer-specific mortality compared to luminal A cancer classified using various cut points for Ki67 positivity including the 14% cut point routinely reported in the literature (HR 1.38, 95% CI 1.11-1.72, p = 0.004). There was no significant difference in clinical outcomes for ER- tumors according to Ki67 positivity defined at various cut points. CONCLUSIONS: Assessment of Ki67 in breast tumors by DIA was a robust and quantitative method. Results from this large prospective cohort study provide support for the clinical relevance of using Ki67 at the 14% cut point for luminal subtype classification and breast cancer prognosis.
Entities:
Keywords:
Breast cancer; Ki67; Risk factor; Subtype; Survival
Authors: T Sørlie; C M Perou; R Tibshirani; T Aas; S Geisler; H Johnsen; T Hastie; M B Eisen; M van de Rijn; S S Jeffrey; T Thorsen; H Quist; J C Matese; P O Brown; D Botstein; P E Lønning; A L Børresen-Dale Journal: Proc Natl Acad Sci U S A Date: 2001-09-11 Impact factor: 11.205
Authors: K David Voduc; Maggie C U Cheang; Scott Tyldesley; Karen Gelmon; Torsten O Nielsen; Hagen Kennecke Journal: J Clin Oncol Date: 2010-03-01 Impact factor: 44.544
Authors: Megan A Healey; Rong Hu; Andrew H Beck; Laura C Collins; Stuart J Schnitt; Rulla M Tamimi; Aditi Hazra Journal: Breast Cancer Res Treat Date: 2014-09-16 Impact factor: 4.872
Authors: Laura C Collins; Kimberly S Cole; Jonathan D Marotti; Rong Hu; Stuart J Schnitt; Rulla M Tamimi Journal: Mod Pathol Date: 2011-05-06 Impact factor: 7.842
Authors: A Prat; A Lluch; J Albanell; W T Barry; C Fan; J I Chacón; J S Parker; L Calvo; A Plazaola; A Arcusa; M A Seguí-Palmer; O Burgues; N Ribelles; A Rodriguez-Lescure; A Guerrero; M Ruiz-Borrego; B Munarriz; J A López; B Adamo; M C U Cheang; Y Li; Z Hu; M L Gulley; M J Vidal; B N Pitcher; M C Liu; M L Citron; M J Ellis; E Mardis; T Vickery; C A Hudis; E P Winer; L A Carey; R Caballero; E Carrasco; M Martín; C M Perou; E Alba Journal: Br J Cancer Date: 2014-08-07 Impact factor: 7.640
Authors: Sarah Alexandrou; Sandra Marie George; Christopher John Ormandy; Elgene Lim; Samantha Richelle Oakes; C Elizabeth Caldon Journal: Int J Mol Sci Date: 2019-02-04 Impact factor: 5.923
Authors: Famke Aeffner; Mark D Zarella; Nathan Buchbinder; Marilyn M Bui; Matthew R Goodman; Douglas J Hartman; Giovanni M Lujan; Mariam A Molani; Anil V Parwani; Kate Lillard; Oliver C Turner; Venkata N P Vemuri; Ana G Yuil-Valdes; Douglas Bowman Journal: J Pathol Inform Date: 2019-03-08
Authors: Haydee Lara; Zaibo Li; Esther Abels; Famke Aeffner; Marilyn M Bui; Ehab A ElGabry; Cleopatra Kozlowski; Michael C Montalto; Anil V Parwani; Mark D Zarella; Douglas Bowman; David Rimm; Liron Pantanowitz Journal: Appl Immunohistochem Mol Morphol Date: 2021-08-01