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Development of an evidence-based approach to external quality assurance for breast cancer hormone receptor
Nikita Makretsov1, C Blake Gilks, Reza Alaghehbandan
1Department of Pathology, Memorial University of Newfoundland, St John's, Canada.
Context:
External quality assurance and proficiency testing programs for breast cancer predictive biomarkers are based largely on traditional ad hoc design; at present there is no universal consensus on definition of a standard reference value for samples used in external quality assurance programs.
Objective:
To explore reference values for estrogen receptor and progesterone receptor immunohistochemistry in order to develop an evidence-based analytic platform for external quality assurance.
Design:
There were 31 participating laboratories, 4 of which were previously designated as "expert" laboratories. Each participant tested a tissue microarray slide with 44 breast carcinomas for estrogen receptor and progesterone receptor and submitted it to the Canadian Immunohistochemistry Quality Control Program for analysis. Nuclear staining in 1% or more of the tumor cells was a positive score. Five methods for determining reference values were compared.
Results:
All reference values showed 100% agreement for estrogen receptor and progesterone receptor scores, when indeterminate results were excluded. Individual laboratory performance (agreement rates, test sensitivity, test specificity, positive predictive value, negative predictive value, and κ value) was very similar for all reference values. Identification of suboptimal performance by all methods was identical for 30 of 31 laboratories. Estrogen receptor assessment of 1 laboratory was discordant: agreement was less than 90% for 3 of 5 reference values and greater than 90% with the use of 2 other reference values.
Conclusions:
Various reference values provide equivalent laboratory rating. In addition to descriptive feedback, our approach allows calculation of technical test sensitivity and specificity, positive and negative predictive values, agreement rates, and κ values to guide corrective actions.