TY - JOUR
T1 - Prognostic value of automated KI67 scoring in breast cancer
T2 - A centralised evaluation of 8088 patients from 10 study groups
AU - Abubakar, Mustapha
AU - Orr, Nick
AU - Daley, Frances
AU - Coulson, Penny
AU - Ali, H. Raza
AU - Blows, Fiona
AU - Benitez, Javier
AU - Milne, Roger
AU - Brenner, Herman
AU - Stegmaier, Christa
AU - Mannermaa, Arto
AU - Chang-Claude, Jenny
AU - Rudolph, Anja
AU - Sinn, Peter
AU - Couch, Fergus J.
AU - Devilee, Peter
AU - Tollenaar, Rob A.E.M.
AU - Seynaeve, Caroline
AU - Figueroa, Jonine
AU - Sherman, Mark E.
AU - Lissowska, Jolanta
AU - Hewitt, Stephen
AU - Eccles, Diana
AU - Hooning, Maartje J.
AU - Hollestelle, Antoinette
AU - Martens, John W.M.
AU - Deurzen, Carolien H.M.
AU - Investigators, k. Con Fab
AU - Bolla, Manjeet K.
AU - Wang, Qin
AU - Jones, Michael
AU - Schoemaker, Minouk
AU - Wesseling, Jelle
AU - van Leeuwen, Flora E.
AU - Van 't Veer, Laura
AU - Easton, Douglas
AU - Swerdlow, Anthony J.
AU - Dowsett, Mitch
AU - Pharoah, Paul D.
AU - Schmidt, Marjanka K.
AU - Garcia-Closas, Montserrat
N1 - Publisher Copyright:
© 2016 The Author(s).
PY - 2016/10/18
Y1 - 2016/10/18
N2 - Background: The value of KI67 in breast cancer prognostication has been questioned due to concerns on the analytical validity of visual KI67 assessment and methodological limitations of published studies. Here, we investigate the prognostic value of automated KI67 scoring in a large, multicentre study, and compare this with pathologists' visual scores available in a subset of patients. Methods: We utilised 143 tissue microarrays containing 15,313 tumour tissue cores from 8088 breast cancer patients in 10 collaborating studies. A total of 1401 deaths occurred during a median follow-up of 7.5 years. Centralised KI67 assessment was performed using an automated scoring protocol. The relationship of KI67 levels with 10-year breast cancer specific survival (BCSS) was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models adjusted for known prognostic factors. Results: Patients in the highest quartile of KI67 (>12 % positive KI67 cells) had a worse 10-year BCSS than patients in the lower three quartiles. This association was statistically significant for ER-positive patients (hazard ratio (HR) (95 % CI) at baseline = 1.96 (1.31-2.93); P = 0.001) but not for ER-negative patients (1.23 (0.86-1.77); P = 0.248) (P-heterogeneity = 0.064). In spite of differences in characteristics of the study populations, the estimates of HR were consistent across all studies (P-heterogeneity = 0.941 for ER-positive and P-heterogeneity = 0.866 for ER-negative). Among ER-positive cancers, KI67 was associated with worse prognosis in both node-negative (2.47 (1.16-5.27)) and node-positive (1.74 (1.05-2.86)) tumours (P-heterogeneity = 0.671). Further classification according to ER, PR and HER2 showed statistically significant associations with prognosis among hormone receptor-positive patients regardless of HER2 status (P-heterogeneity = 0.270) and among triple-negative patients (1.70 (1.02-2.84)). Model fit parameters were similar for visual and automated measures of KI67 in a subset of 2440 patients with information from both sources. Conclusions: Findings from this large-scale multicentre analysis with centrally generated automated KI67 scores show strong evidence in support of a prognostic value for automated KI67 scoring in breast cancer. Given the advantages of automated scoring in terms of its potential for standardisation, reproducibility and throughput, automated methods appear to be promising alternatives to visual scoring for KI67 assessment.
AB - Background: The value of KI67 in breast cancer prognostication has been questioned due to concerns on the analytical validity of visual KI67 assessment and methodological limitations of published studies. Here, we investigate the prognostic value of automated KI67 scoring in a large, multicentre study, and compare this with pathologists' visual scores available in a subset of patients. Methods: We utilised 143 tissue microarrays containing 15,313 tumour tissue cores from 8088 breast cancer patients in 10 collaborating studies. A total of 1401 deaths occurred during a median follow-up of 7.5 years. Centralised KI67 assessment was performed using an automated scoring protocol. The relationship of KI67 levels with 10-year breast cancer specific survival (BCSS) was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models adjusted for known prognostic factors. Results: Patients in the highest quartile of KI67 (>12 % positive KI67 cells) had a worse 10-year BCSS than patients in the lower three quartiles. This association was statistically significant for ER-positive patients (hazard ratio (HR) (95 % CI) at baseline = 1.96 (1.31-2.93); P = 0.001) but not for ER-negative patients (1.23 (0.86-1.77); P = 0.248) (P-heterogeneity = 0.064). In spite of differences in characteristics of the study populations, the estimates of HR were consistent across all studies (P-heterogeneity = 0.941 for ER-positive and P-heterogeneity = 0.866 for ER-negative). Among ER-positive cancers, KI67 was associated with worse prognosis in both node-negative (2.47 (1.16-5.27)) and node-positive (1.74 (1.05-2.86)) tumours (P-heterogeneity = 0.671). Further classification according to ER, PR and HER2 showed statistically significant associations with prognosis among hormone receptor-positive patients regardless of HER2 status (P-heterogeneity = 0.270) and among triple-negative patients (1.70 (1.02-2.84)). Model fit parameters were similar for visual and automated measures of KI67 in a subset of 2440 patients with information from both sources. Conclusions: Findings from this large-scale multicentre analysis with centrally generated automated KI67 scores show strong evidence in support of a prognostic value for automated KI67 scoring in breast cancer. Given the advantages of automated scoring in terms of its potential for standardisation, reproducibility and throughput, automated methods appear to be promising alternatives to visual scoring for KI67 assessment.
KW - Automated KI67
KW - Breast cancer
KW - Prognostication
KW - Visual KI67
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UR - http://www.scopus.com/inward/citedby.url?scp=84992454911&partnerID=8YFLogxK
U2 - 10.1186/s13058-016-0765-6
DO - 10.1186/s13058-016-0765-6
M3 - Article
C2 - 27756439
AN - SCOPUS:84992454911
SN - 1465-5411
VL - 18
JO - Breast Cancer Research
JF - Breast Cancer Research
IS - 1
M1 - 104
ER -