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Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases

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Abstract

Background

Estrogen receptor (ER) expression is routinely assessed by immunohistochemistry (IHC) in breast carcinoma. Our study compares visual scoring of ER in invasive breast cancer by histopathologists to quantitation of staining using a fully automated system.

Materials and methods

A tissue microarray was constructed from 4,049 cases (3,484 included in analysis) of invasive breast carcinoma linked to treatment and outcome information. Slides were scored independently by two pathologists and scores were dichotomised, with ER positivity recognized at a cut-off of >1% positive nuclei. The slides were scanned and analyzed with an Ariol automated system.

Results

Using data dichotomised as ER positive or negative, both visual and automated scores were highly consistent: there was excellent concordance between two pathologists (kappa = 0.918 (95%CI: 0.903–0.932)) and between two Ariol machines (kappa = 0.913 (95%CI: 0.897–0.928)). The prognostic significance of ER positivity was similar whether determined by pathologist or automated scoring for both the entire patient cohort and subsets of patients treated with tamoxifen alone or receiving no systemic adjuvant therapy. The optimal cut point for the automated scores using breast cancer disease-specific survival as an endpoint was >0.4% positive nuclei. The concordance between dextran-coated charcoal ER biochemical assay data and automated scores (kappa = 0.728 (95%CI: 0.69–0.75); 0.74 (95%CI: 0.71–0.77)) was similar to the concordance between biochemical assay and pathologist scores (kappa = 0.72 (95%CI: 0.70–0.75; 0.70 (95%CI: 0.67–0.72)).

Conclusion

Fully automated quantitation of ER immunostaining yields results that do not differ from human scoring against both biochemical assay and patient outcome gold standards.

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Acknowledgements

The study was supported in part by an unrestricted educational grant from Sanofi-Aventis, Canada and a Translational Acceleration grant from the Canadian Breast Cancer Research Alliance. TON and DGH are scholars of Michael Smith Foundation for Health Research.

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Correspondence to David G. Huntsman.

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Turbin, D.A., Leung, S., Cheang, M.C.U. et al. Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases. Breast Cancer Res Treat 110, 417–426 (2008). https://doi.org/10.1007/s10549-007-9736-z

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  • DOI: https://doi.org/10.1007/s10549-007-9736-z

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