Quality improvement of biomarker assessment in breast cancer
| Autor: | Carmen van Dooijeweert |
|---|---|
| Přispěvatelé: | van Diest, P.J., van der Wall, E., Deckers, I.A.G., Baas, I.O., University Utrecht |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Oncology
medicine.medical_specialty Quality management business.industry medicine.medical_treatment borstkanker ductaal carcinoom in situ receptoren histologische graad gradering variatie real-world data pathologie spiegelinformatie e-learning medicine.disease Tumor tissue Breast cancer Internal medicine Histologic grade Medicine Biomarker (medicine) spiegelinformatie Hormone therapy business Grading (tumors) e-learning |
| Popis: | Breast cancer treatment is largely guided by the results of tumor tissue analyses, i.e. evaluation of so called biomarkers, by pathologists. These biomarkers determine whether the tumor is sensitive to treatment with hormone therapy or treatment against the HER2-protein. Histologic grade represents the degree of aggressiveness and (co)determines whether additional treatment, for example with chemotherapy, is required. Given the importance of these biomarkers with regard to breast cancer treatment, we investigated whether there are differences in the results of biomarker assessment between pathology laboratories and between pathologists within individual laboratories. These analyses were performed with data from over 33.000 patients treated for breast cancer in the Netherlands between 2013 and 2016. Variation in biomarker assessment was limited, with exception of variation in grading, which was substantial, both between laboratories and between pathologists within the same laboratory. Realizing that grade is decisive for the indications for additional chemotherapy and hormone therapy in 35% and 30% of breast cancer patients, it seems likely that variation in grading lead to variation in treatment. This could potentially affect survival of breast cancer patients, which is still under investigation. To promote uniform grading, these data were reported back to the laboratories by means of feedback reports. An e-learning module, in which pathologists were trained in grading of breast cancer, was also developed. Both initiatives showed promising results. Additional initiatives, such as artificial intelligence, should be developed with priority to limit the variation in grading as much as possible. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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