ArticleCancers2021
Variability in Breast Cancer Biomarker Assessment and the Effect on Oncological Treatment Decisions: A Nationwide 5-Year Population-Based Study.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The prognostic and predictive impact of low estrogen receptor expression in early breast cancer: a systematic review and meta-analysis.ESMO open · 2021Pooled it
- Patient characteristics, treatment patterns, and survival across estrogen receptor expression subgroups in HER2-negative breast cancer: a population-based cohort study.The Lancet regional health. Europe · 2026Article
- A bottom-up initiated digital external quality assessment scheme for the state-of-the-art pathology in Sweden: reduced variability between pathology departments.Virchows Archiv : an international journal of pathology · 2026Article
- Article
- Pathological response to pembrolizumab-based neoadjuvant therapy in ER-low vs. ER-zero breast cancer: a Swedish population-based cohort study.Breast cancer research : BCR · 2025Article
- Prognostic significance of tumour Ki-67 dynamics during neoadjuvant treatment in patients with breast cancer: a population-based cohort study.The Lancet regional health. Europe · 2025Article
- Global scoring method of Ki67 immunohistochemistry in breast cancer demonstrates improved concordance using real-world multi-institutional data.Breast cancer research : BCR · 2025Article
- Analyzing the Gaps in Breast Cancer Diagnostics in Poland-A Retrospective Observational Study in the Data Donation Model.Diagnostics (Basel, Switzerland) · 2025Article
- A method for spatial interpretation of weakly supervised deep learning models in computational pathology.Scientific reports · 2025Article
- An international study of stain variability in histopathology using qualitative and quantitative analysis.Journal of pathology informatics · 2025Article
- Triple-negative breast cancer at Helen Joseph Hospital: Prevalence, age and imaging features.SA journal of radiology · 2025Article
- Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.BMC cancer · 2024Article
- The analytical and clinical validity of AI algorithms to score TILs in TNBC: can we use different machine learning models interchangeably?EClinicalMedicine · 2024Article
- Impact of Molecular Profiling on Therapy Management in Breast Cancer.Journal of clinical medicine · 2024Review
- Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images.Breast cancer research : BCR · 2024Article
- Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.Breast cancer research and treatment · 2024Article
- Ensemble-based deep learning improves detection of invasive breast cancer in routine histopathology images.Heliyon · 2024Article
- Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images.Breast cancer research : BCR · 2024Article
- Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research.Histopathology · 2024Review
- Real-world overall survival and characteristics of patients with ER-zero and ER-low HER2-negative breast cancer treated as triple-negative breast cancer: a Swedish population-based cohort study.The Lancet regional health. Europe · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
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.
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