A novel model for Ki67 assessment in breast cancer

被引:29
|
作者
Romero, Quinci [1 ]
Bendahl, Par-Ola [1 ]
Ferno, Marten [1 ]
Grabau, Dorthe [3 ]
Borgquist, Signe [1 ,2 ]
机构
[1] Lund Univ, Div Oncol, Dept Clin Sci Lund, SE-22185 Lund, Sweden
[2] Skane Univ Hosp, Dept Oncol, Lund, Sweden
[3] Lund Univ, Dept Clin Sci, Div Pathol, SE-22185 Lund, Sweden
来源
DIAGNOSTIC PATHOLOGY | 2014年 / 9卷
关键词
Ki67; Breast cancer; Proliferation; Counting strategy; Statistical model; PROLIFERATIVE ACTIVITY; KI-67; ANTIGEN; MIB-1; RECOMMENDATIONS; METAANALYSIS; BIOMARKERS; MARKERS;
D O I
10.1186/1746-1596-9-118
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
Background: Ki67 is currently the proliferation biomarker of choice, with both prognostic and predictive value in breast cancer. A lack of consensus regarding Ki67 use in pre-analytical, analytical and post-analytical practice may hinder its formal acceptance in the clinical setting. Methods: One hundred breast cancer samples were stained for Ki67. A standard estimation of Ki67 using fixed denominators of 200, 400 and 1 000 counted tumor cells was performed, and a cut-off at 20% was applied, Ki67static. A novel stepwise counting strategy for Ki67 estimation, Ki67(scs), was developed based on rejection regions derived from exact two-sided binomial confidence intervals for proportions. Ki67scs was defined by the following parameters: the cut-off (20%), minimum (50) and maximum (400) number of tumor cells to count, increment (10) and overall significance level of the test procedure (0.05). Results from Ki67scs were compared to results from the Ki67static estimation with fixed denominators. Results: For Ki67scs, the median number of tumor cells needed to determine Ki67 status was 100; the average, 175. Among 38 highly proliferative samples, the average Ki67scs fraction was 45%. For these samples, the fraction decreased from 39% to 37% to 35% with static counting of 200, 400 and 1 000 cells, respectively. The largest absolute difference between the estimation methods was 23% (42% (Ki67scs) vs. 19% (Ki67static)) and resulted in an altered sample classification. Among the 82 unequivocal samples, 74 samples received the same classification using both Ki67scs and Ki67static. Of the eight disparate samples, seven were classified highly proliferative by Ki67static when 200 cells were counted; whereas all eight cases were classified as low proliferative when 1 000 cells were counted. Conclusions: Ki67 estimation using fixed denominators may be inadequate, particularly for tumors demonstrating extensive heterogeneity. We propose a time saving stepwise counting strategy, which acknowledges small highly proliferative hot spots. Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/3588156111195336
引用
收藏
页数:8
相关论文
共 50 条
  • [1] A novel model for Ki67 assessment in breast cancer
    Quinci Romero
    Pär-Ola Bendahl
    Mårten Fernö
    Dorthe Grabau
    Signe Borgquist
    Diagnostic Pathology, 9
  • [2] Ki67 assessment in breast cancer: an update
    Penault-Llorca, Frederique
    Radosevic-Robin, Nina
    PATHOLOGY, 2017, 49 (02) : 166 - 171
  • [3] Number Needed To Count: A Novel Model for Ki67 Assessment in Breast Cancer.
    Bendahl, P-O
    Romero, Q.
    Grabau, D.
    Borgquist, S.
    CANCER RESEARCH, 2011, 71
  • [4] Assessment of Ki67 in Breast Cancer: Recommendations from the International Ki67 in Breast Cancer Working Group
    Dowsett, Mitch
    Nielsen, Torsten O.
    A'Hern, Roger
    Bartlett, John
    Coombes, R. Charles
    Cuzick, Jack
    Ellis, Matthew
    Henry, N. Lynn
    Hugh, Judith C.
    Lively, Tracy
    McShane, Lisa
    Paik, Soon
    Penault-Llorca, Frederique
    Prudkin, Ljudmila
    Regan, Meredith
    Salter, Janine
    Sotiriou, Christos
    Smith, Ian E.
    Viale, Giuseppe
    Zujewski, Jo Anne
    Hayes, Daniel F.
    JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2011, 103 (22): : 1656 - 1664
  • [5] Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group
    Nielsen, Torsten O.
    Leung, Samuel C. Y.
    Rimm, David L.
    Dodson, Andrew
    Acs, Balazs
    Badve, Sunil
    Denkert, Carsten
    Ellis, Matthew J.
    Fineberg, Susan
    Flowers, Margaret
    Kreipe, Hans H.
    Laenkholm, Anne-Vibeke
    Pan, Hongchao
    Penault-Llorca, Friderique M.
    Polley, Mei-Yin
    Salgado, Roberto
    Smith, Ian E.
    Sugie, Tomoharu
    Bartlett, John M. S.
    McShane, Lisa M.
    Dowsett, Mitch
    Hayes, Daniel F.
    JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2021, 113 (07): : 808 - 819
  • [6] Ki67 Assessment in Breast Cancer: Are We There Yet?
    Reis-Filho, Jorge S.
    Davidson, Nancy E.
    JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2021, 113 (07): : 797 - 798
  • [7] RE: Assessment of Ki67 in Breast Cancer: Updated Recommendations from the International Ki67 in Breast Cancer Working Group
    Zhang, Jiandi
    Yang, Maozhou
    JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2021, 113 (11): : 1595 - 1596
  • [8] Ki67 and proliferation in breast cancer
    Pathmanathan, Nirmala
    Balleine, Rosemary L.
    JOURNAL OF CLINICAL PATHOLOGY, 2013, 66 (06) : 512 - 516
  • [9] Impact of intratumoural heterogeneity on the assessment of Ki67 expression in breast cancer
    M. A. Aleskandarany
    A. R. Green
    I Ashankyty
    A Elmouna
    M Diez-Rodriguez
    C. C. Nolan
    I. O. Ellis
    E. A. Rakha
    Breast Cancer Research and Treatment, 2016, 158 : 287 - 295
  • [10] An Interobserver Reproducibility Analysis of Ki67 Visual Assessment in Breast Cancer
    Shui, Ruohong
    Yu, Baohua
    Bi, Rui
    Yang, Fei
    Yang, Wentao
    PLOS ONE, 2015, 10 (05):