Assessment of interlaboratory variation in the immunohistochemical determination of estrogen receptor status using a breast cancer tissue microarray

Am J Clin Pathol. 2002 May;117(5):723-8. doi: 10.1309/PEF8-GL6F-YWMC-AG56.


The determination of tumor cell estrogen receptor (ER) expression status by immunohistochemical analysis has become standard practice, yet assay reproducibility has not been assessed adequately. By using a breast cancer tissue microarray, we examined interlaboratory variability in ER reporting. A 2-fold redundant tissue microarray block was created from 29 breast cancers. Unstained slides were distributed to 5 laboratories, and each laboratory immunostained and scored 1 slide for ER. Interlaboratory agreement ranged from moderate to high (overall kappa = 0.54 for 0-3+ grading; overall kappa = 0.84 for negative vs positive assessment of ER status). When 1 observer scored each of the 5 slides, interlaboratory agreement was slightly better (kappa = 0.63 for 0-3+ scoring; kappa = 0.96 for negative vs positive scoring). One laboratory, which had used an antibody and antigen retrieval method different from the others, demonstrated only fair concordance with the other 4 laboratories, but there was substantial intralaboratory interobserver agreement and excellent agreement with an outside observer reviewing the slide stained in that laboratory. The tissue microarray was an efficient and effective tool for identifying variability in ER reporting and should prove valuable in other external quality assurance programs.

Publication types

  • Comparative Study

MeSH terms

  • Breast Neoplasms / chemistry*
  • Breast Neoplasms / pathology
  • Female
  • Histocytological Preparation Techniques*
  • Hospitals, Community
  • Hospitals, University
  • Humans
  • Immunohistochemistry
  • Laboratories*
  • Neoplasm Invasiveness / pathology
  • Observer Variation
  • Pathology, Clinical / methods*
  • Receptors, Estrogen / analysis*
  • Reproducibility of Results
  • Single-Blind Method


  • Receptors, Estrogen