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dc.contributor.authorAbubakar, M
dc.contributor.authorHowat, WJ
dc.contributor.authorDaley, F
dc.contributor.authorZabaglo, L
dc.contributor.authorMcDuffus, L-A
dc.contributor.authorBlows, F
dc.contributor.authorCoulson, P
dc.contributor.authorRaza Ali, H
dc.contributor.authorBenitez, J
dc.contributor.authorMilne, R
dc.contributor.authorBrenner, H
dc.contributor.authorStegmaier, C
dc.contributor.authorMannermaa, A
dc.contributor.authorChang-Claude, J
dc.contributor.authorRudolph, A
dc.contributor.authorSinn, P
dc.contributor.authorCouch, FJ
dc.contributor.authorTollenaar, RAEM
dc.contributor.authorDevilee, P
dc.contributor.authorFigueroa, J
dc.contributor.authorSherman, ME
dc.contributor.authorLissowska, J
dc.contributor.authorHewitt, S
dc.contributor.authorEccles, D
dc.contributor.authorHooning, MJ
dc.contributor.authorHollestelle, A
dc.contributor.authorWm Martens, J
dc.contributor.authorHm van Deurzen, C
dc.contributor.authorkConFab Investigators,
dc.contributor.authorBolla, MK
dc.contributor.authorWang, Q
dc.contributor.authorJones, M
dc.contributor.authorSchoemaker, M
dc.contributor.authorBroeks, A
dc.contributor.authorvan Leeuwen, FE
dc.contributor.authorVan't Veer, L
dc.contributor.authorSwerdlow, AJ
dc.contributor.authorOrr, N
dc.contributor.authorDowsett, M
dc.contributor.authorEaston, D
dc.contributor.authorSchmidt, MK
dc.contributor.authorPharoah, PD
dc.contributor.authorGarcia-Closas, M
dc.date.accessioned2016-09-05T13:22:06Z
dc.date.issued2016-07-01
dc.identifier.citationThe journal of pathology. Clinical research, 2016, 2 (3), pp. 138 - 153
dc.identifier.issn2056-4538
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/99
dc.identifier.eissn2056-4538
dc.identifier.doi10.1002/cjp2.42
dc.description.abstractAutomated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.
dc.formatElectronic-eCollection
dc.format.extent138 - 153
dc.languageeng
dc.language.isoeng
dc.publisherWILEY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectkConFab Investigators
dc.titleHigh-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium.
dc.typeJournal Article
dcterms.dateAccepted2016-02-27
rioxxterms.versionofrecord10.1002/cjp2.42
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2016-07
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfThe journal of pathology. Clinical research
pubs.issue3
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Complex Trait Genetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Endocrinology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Endocrinology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Endocrinology/Endocrinology (hon.)
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Complex Trait Genetics
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Breast Cancer Research/Endocrinology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Genetics and Epidemiology/Aetiological Epidemiology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Endocrinology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Endocrinology/Endocrinology (hon.)
pubs.publication-statusPublished
pubs.volume2
pubs.embargo.termsNo embargo
pubs.oa-locationhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4958735/pdf/CJP2-2-138.pdf
icr.researchteamComplex Trait Genetics
icr.researchteamAetiological Epidemiology
icr.researchteamEndocrinology
dc.contributor.icrauthorAbubakar, Mustapha
dc.contributor.icrauthorJones, Michael
dc.contributor.icrauthorSchoemaker, Minouk
dc.contributor.icrauthorSwerdlow, Anthony
dc.contributor.icrauthorGarcia-Closas, Montserrat


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