Variability in Breast Cancer Biomarker Assessment and the Effect on Oncological Treatment Decisions: A Nationwide 5-Year Population-Based Study

Abstract

We compared estrogen receptor (ER), progesterone receptor (PR), human epidermal growth-factor receptor 2 (HER2), Ki67, and grade scores among the pathology departments in Sweden. We investigated how ER and HER2 positivity rates affect the distribution of endocrine and HER2-targeted treatments among oncology departments. All breast cancer patients diagnosed between 2013 and 2018 in Sweden were identified in the National Quality Register for Breast Cancer. Cases with data on ER, PR, HER2, Ki67, grade, and treatment were selected (43,261 cases from 29 departments following the guidelines for biomarker testing). The ER positivity rates ranged from 84.2% to 97.6% with 6/29 labs out of the overall confidence intervals (CIs), while PR rates varied between 64.8% and 86.6% with 7/29 labs out of the CIs. HER2 positivity rates ranged from 9.4% to 16.3%, with 3/29 labs out of the overall CIs. Median Ki67 varied between 15% and 30%, where 19/29 labs showed significant intra-laboratory variability. The proportion of grade-II cases varied between 42.9% and 57.1%, and 13/29 labs were outside of the CI. Adjusting for patient characteristics, the proportion of endocrine and anti-HER2 treatments followed the rate of ER and HER2 positivity, illustrating the clinical effect of inter- and intra-laboratory variability. There was limited variability among departments in ER, PR, and HER2 testing. However, even a few outlier pathology labs affected endocrine and HER2-targeted treatment rates in a clinically relevant proportion, suggesting the need for improvement. High variability was found in grading and Ki67 assessment, illustrating the need for the adoption of new technologies in practice.

Independent Clinical Validation of the Automated Ki67 Scoring Guideline from the International Ki67 in Breast Cancer Working Group

“…In the literature, many practical issues have emerged regarding Ki67 assessment, which limits its clinical implementation in breast cancer treatment decisions [ 22 ]. The most discussed factor that hinders the clinical usage of Ki67 is interobserver variability due to the varying scoring methods, selection of tumor areas and subjective assessment of staining positivity [ 23 , 24 ]. There are several DIA platforms offering a solution for scoring Ki67.…”

“…In an international study of 30 ER-positive breast cancer cases, different DIA platforms were chosen by different laboratories, yet they achieved high ICCs for global scores [ 28 ]. Although machine learning-based tools can aid scoring-related reproducibility issues, more focus has to be placed on pre-analytical and analytical processes to achieve complete standardization of Ki67 assessment [ 23 ].…”

Improved breast cancer histological grading using deep learning

“…The intermediate group (NHG 2) accounts for approximately half of the patient population [11,12], but exhibits larger variation with regard to morphological patterns and survival outcomes [13] in comparison with NHG 1 and 3. As histological grade remains central in determining therapeutic regimens [14], the heterogeneity in the NHG 2 group poses challenges for deciding optimal treatment for individual patients.…”

“…This comprises the absolutely largest group of breast cancer patients. In a population-based register study of pathology data with over 45, 000 patients in Sweden[11], more than 60% of the ER+ HER2-patients were reported as NHG2. This clearly shows that methods to identify high-and low risk patients in this patient group could contribute to clinical decision making of adjuvant chemotherapy.…”

The prognostic and predictive impact of low estrogen receptor expression in early breast cancer: a systematic review and meta-analysis

“…This risk has been shown to be higher in low or medium ER expressions 29 but considerably lower compared with other breast cancer biomarkers such as HER2 and Ki-67. 30 , 31 Finally, this meta-analysis included only observational studies which negatively impact the certainty of evidence, as reflected by the grading of evidence according to the GRADE approach.…”