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"Score the Core" Web-based pathologist training tool improves the accuracy of breast cancer IHC4 scoring
Jesse A Engelberg1, Hanna Retallack2, Ronald Balassanian3
1Center for Comparative Medicine, University of California Davis, Davis, CA 95616.
Abstract:
Hormone receptor status is an integral component of decision-making in breast cancer management. IHC4 score is an algorithm that combines hormone receptor, HER2, and Ki-67 status to provide a semiquantitative prognostic score for breast cancer. High accuracy and low interobserver variance are important to ensure the score is accurately calculated; however, few previous efforts have been made to measure or decrease interobserver variance. We developed a Web-based training tool, called "Score the Core" (STC) using tissue microarrays to train pathologists to visually score estrogen receptor (using the 300-point H score), progesterone receptor (percent positive), and Ki-67 (percent positive). STC used a reference score calculated from a reproducible manual counting method. Pathologists in the Athena Breast Health Network and pathology residents at associated institutions completed the exercise. By using STC, pathologists improved their estrogen receptor H score and progesterone receptor and Ki-67 proportion assessment and demonstrated a good correlation between pathologist and reference scores. In addition, we collected information about pathologist performance that allowed us to compare individual pathologists and measures of agreement. Pathologists' assessment of the proportion of positive cells was closer to the reference than their assessment of the relative intensity of positive cells. Careful training and assessment should be used to ensure the accuracy of breast biomarkers. This is particularly important as breast cancer diagnostics become increasingly quantitative and reproducible. Our training tool is a novel approach for pathologist training that can serve as an important component of ongoing quality assessment and can improve the accuracy of breast cancer prognostic biomarkers.
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