ArticleBreast care (Basel, Switzerland)2024
Use of the Gene Expression Test Prosigna
Article in Breast care (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors at 2 institutions in 2 countries.
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Abstract
Introduction: In hormone receptor-positive (ER+/PR+) and human epidermal growth factor receptor 2-negative (HER2-) early-stage breast cancer (EBC), gene expression tests such as the Prosigna are increasingly used since classic clinicopathological parameters and the proliferation factor Ki-67 often do not allow a definite therapy decision regarding an adjuvant chemotherapy. While the Prosigna test has been validated for postmenopausal patients, few data are available regarding its use in premenopausal patients. The present study compared the Prosigna test with the Ki-67 index in premenopausal patients. Materials and Methods: Premenopausal patients with HR+ HER2-, pN0-1, G1-2 EBC were retrospectively enrolled ( Results: According to Ki-67, patients were in the low (LR)-, intermediate (IR)-, and high-risk (HR) groups in 40%, 36%, and 24% of the cases. The Prosigna gene signature assay assessed the risk of recurrence as LR for 45% of the patients, IR for 35%, and HR for 20%. The most frequent intrinsic subtypes were luminal A in 73% and luminal B in 24% of the patients. A moderate correlation was found between Prosigna and Ki-67 scores with a Pearson correlation coefficient of 0.51. In the overall cohort, 47% of the Ki-67-based therapy decision would correspond to those based on the Prosigna score. After exclusion of IR patients, matching of low/low or high/high results was observed in 57% of the cases. Conclusion: According to the present study, there is only limited concordance regarding the risk group stratification between Ki-67 and Prosigna-based risk assessment. The relevance and frequency of premenopausal breast cancer emphasizes the need for further evaluation of gene expression analyses in this setting and the correlation with classic clinicopathological parameters regarding therapy decision-making.
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