Show simple item record

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.authorAli, HR
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.authorMartens, JWM
dc.contributor.authorvan Deurzen, CHM
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.accessioned2020-12-22T04:40:02Z
dc.date.available2020-12-22T04:40:02Z
dc.date.issued2016-07-01
dc.identifierpii: CJP242
dc.identifier.citationAbubakar, M., Howat, W. J., Daley, F., Zabaglo, L., McDuffus, L. -A., Blows, F., Coulson, P., Ali, H. R., Benitez, J., Milne, R., Brenner, H., Stegmaier, C., Mannermaa, A., Chang-Claude, J., Rudolph, A., Sinn, P., Couch, F. J., Tollenaar, R. A. E. M., Devilee, P. ,... Garcia-Closas, M. (2016). High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium. JOURNAL OF PATHOLOGY CLINICAL RESEARCH, 2 (3), pp.138-153. https://doi.org/10.1002/cjp2.42.
dc.identifier.issn2056-4538
dc.identifier.urihttp://hdl.handle.net/11343/258115
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.languageEnglish
dc.publisherWILEY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleHigh-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium
dc.typeJournal Article
dc.identifier.doi10.1002/cjp2.42
melbourne.affiliation.departmentMelbourne School of Population and Global Health
melbourne.source.titleJournal of Pathology: Clinical Research
melbourne.source.volume2
melbourne.source.issue3
melbourne.source.pages138-153
dc.rights.licenseCC BY
melbourne.elementsid1185254
melbourne.contributor.authorMilne, Roger
dc.identifier.eissn2056-4538
melbourne.accessrightsOpen Access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record