eprintid: 21994
rev_number: 13
eprint_status: archive
userid: 1589
dir: disk0/00/02/19/94
datestamp: 2016-10-26 12:32:37
lastmod: 2024-05-07 15:16:29
status_changed: 2016-10-26 12:32:37
type: article
metadata_visibility: show
creators_name: Abubakar, Mustapha
creators_name: Orr, Nick
creators_name: Daley, Frances
creators_name: Coulson, Penny
creators_name: Ali, H. Raza
creators_name: Blows, Fiona
creators_name: Benitez, Javier
creators_name: Milne, Roger
creators_name: Brenner, Herman
creators_name: Stegmaier, Christa
creators_name: Mannermaa, Arto
creators_name: Chang-Claude, Jenny
creators_name: Rudolph, Anja
creators_name: Sinn, Peter
creators_name: Couch, Fergus J.
creators_name: Devilee, Peter
creators_name: Tollenaar, Rob A. E. M.
creators_name: Seynaeve, Caroline
creators_name: Figueroa, Jonine
creators_name: Sherman, Mark E.
creators_name: Lissowska, Jolanta
creators_name: Hewitt, Stephen
creators_name: Eccles, Diana
creators_name: Hooning, Maartje J.
creators_name: Hollestelle, Antoinette
creators_name: Martens, John W. M.
creators_name: van Deurzen, Carolien H. M.
creators_name: Wang, Qin
creators_name: Bolla, Manjeet K
creators_name: Jones, Michael
creators_name: Schoemaker, Minouk
creators_name: Wesseling, Jelle
creators_name: van Leeuwen, Flora E.
creators_name: Van't Veer, Laura
creators_name: Easton, Douglas
creators_name: Swerdlow, Anthony J.
creators_name: Dowsett, Mitch
creators_name: Pharoah, Paul D.
creators_name: Schmidt, Marjanka K.
creators_name: Garcia-Closas, Montserrat
title: Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups
subjects: ddc-610
divisions: i-850300
divisions: i-912000
abstract: 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.
date: 2016
publisher: BioMed Central
id_scheme: DOI
ppn_swb: 1653741392
own_urn: urn:nbn:de:bsz:16-heidok-219948
language: eng
bibsort: ABUBAKARMUPROGNOSTIC2016
full_text_status: public
publication: Breast Cancer Research
volume: 18
number: 104
place_of_pub: London
pagerange: 1-13
issn: 1465-542X
citation:   Abubakar, Mustapha ; Orr, Nick ; Daley, Frances ; Coulson, Penny ; Ali, H. Raza ; Blows, Fiona ; Benitez, Javier ; Milne, Roger ; Brenner, Herman ; Stegmaier, Christa ; Mannermaa, Arto ; Chang-Claude, Jenny ; Rudolph, Anja ; Sinn, Peter ; Couch, Fergus J. ; Devilee, Peter ; Tollenaar, Rob A. E. M. ; Seynaeve, Caroline ; Figueroa, Jonine ; Sherman, Mark E. ; Lissowska, Jolanta ; Hewitt, Stephen ; Eccles, Diana ; Hooning, Maartje J. ; Hollestelle, Antoinette ; Martens, John W. M. ; van Deurzen, Carolien H. M. ; Wang, Qin ; Bolla, Manjeet K ; Jones, Michael ; Schoemaker, Minouk ; Wesseling, Jelle ; van Leeuwen, Flora E. ; Van't Veer, Laura ; Easton, Douglas ; Swerdlow, Anthony J. ; Dowsett, Mitch ; Pharoah, Paul D. ; Schmidt, Marjanka K. ; Garcia-Closas, Montserrat  (2016) Prognostic value of automated KI67 scoring in breast cancer: a centralised evaluation of 8088 patients from 10 study groups.  Breast Cancer Research, 18 (104).  pp. 1-13.  ISSN 1465-542X     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/21994/1/13058_2016_Article_765.pdf