Please use this identifier to cite or link to this item: https://doi.org/10.18632/oncotarget.24398
Title: Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer
Authors: Tay, T.K.Y
Thike, A.A
Pathmanathan, N
Jara-Lazaro, A.R
Iqbal, J 
Sng, A.S.H
Ye, H.S
Lim, J.C.T
Koh, V.C.Y
Tan, J.S.Y
Yeong, J.P.S
Chow, Z.L
Li, H.H 
Cheng, C.L
Tan, P.H
Keywords: Ki 67 antigen
adult
aged
algorithm
Article
breast cancer
cancer prognosis
cancer recurrence
cancer survival
clinical outcome
computer analysis
computer assisted image analysis
controlled study
differential diagnosis
estrogen receptor positive breast cancer
female
human
human cell
human tissue
image analysis
luminal A breast cancer
luminal B breast cancer
major clinical study
middle aged
overall survival
prediction
scoring system
tissue microarray
tumor invasion
very elderly
young adult
Issue Date: 2018
Citation: Tay, T.K.Y, Thike, A.A, Pathmanathan, N, Jara-Lazaro, A.R, Iqbal, J, Sng, A.S.H, Ye, H.S, Lim, J.C.T, Koh, V.C.Y, Tan, J.S.Y, Yeong, J.P.S, Chow, Z.L, Li, H.H, Cheng, C.L, Tan, P.H (2018). Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer. Oncotarget 9 (14) : 11619-11630. ScholarBank@NUS Repository. https://doi.org/10.18632/oncotarget.24398
Rights: Attribution 4.0 International
Abstract: Background: Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers. Methods: Quantitative scoring of Ki67 on tissue microarray (TMA) sections of 440 invasive breast cancers was performed using Aperio ePathology ImmunoHistochemistry Nuclear Image Analysis algorithm, with TMA slides digitally scanned via Aperio ScanScope XT System. Results: On multivariate analysis, tumours with Ki67 ?14% had an increased likelihood of recurrence (HR 1.941, p=0.021) and shorter overall survival (HR 2.201, p=0.016). Similar findings were observed in the subset of 343 ER positive breast cancers (HR 2.409, p=0.012 and HR 2.787, p=0.012 respectively). The value of Ki67 associated with ER+HER2-PR < 20% tumours (Luminal B subtype) was found to be < 17%. Conclusion: Using CAIA, we found optimal thresholds for Ki67 that predict a poorer prognosis and an association with the Luminal B subtype of breast cancer. Further investigation and validation of these thresholds are recommended. © Tay et al.
Source Title: Oncotarget
URI: https://scholarbank.nus.edu.sg/handle/10635/178105
ISSN: 19492553
DOI: 10.18632/oncotarget.24398
Rights: Attribution 4.0 International
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