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Open Access Highly Accessed Research

A novel model for Ki67 assessment in breast cancer

Quinci Romero1, Pär-Ola Bendahl1, Mårten Fernö1, Dorthe Grabau3 and Signe Borgquist12*

Author Affiliations

1 Division of Oncology, Department of Clinical Sciences Lund, Lund University, SE-221 85 Lund, Sweden

2 Department of Oncology, Skåne University Hospital, Lund, Sweden

3 Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden

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Diagnostic Pathology 2014, 9:118  doi:10.1186/1746-1596-9-118

Published: 16 June 2014

Abstract

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, Ki67scs, 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.

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/3588156111195336 webcite

Keywords:
Ki67; Breast cancer; Proliferation; Counting strategy; Statistical model