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Correlation Between Oncotype Dx Recurrence Score and PREDICT Estimates in Early Breast Cancer: A Single Institution
Ezzeldin M Ibrahim1, Bushra A Al-Quzi2, Ahmed Y Shaheen2
1Oncology Department, King's College London-Jeddah, Jeddah, Kingdom of Saudi Arabia.
Purpose:
Oncotype Dx Recurrence Score (RS) is prognostic and predictive of chemotherapy benefit in women with node-negative and node-positive in hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) early breast cancer. Nevertheless, its direct cost may be inhibitive. This study assesses the correlation between the RS and the free online PREDICT tools' estimations of adjuvant chemotherapy benefit.
Patients And Methods:
A retrospective review of the electronic medical records of 112 patients with tumors tested for the RS and the PREDICT tool was used to estimate survival benefits. The correlation between RS and PREDICT estimations was analyzed using Spearman rank and McNemar tests.
Results:
The median age of patients was 53 (95% CI, 50 to 55) years, with most patients having negative axillary lymph nodes (78%). While the absolute value for RS showed significant positive correlations with adjuvant chemotherapy's benefit as estimated by PREDICT, no significant correlations were found between the two methods in the percentage of chemotherapy gain. Notably, discordance rates between 48% and 67% between RS-based risk assignments and those based on PREDICT estimates were significant across the study population and subgroups. Only one disease recurrence and one breast cancer-related death were documented over a median follow-up of 23.5 (95% CI, 19.8 to 27.2) months.
Conclusion:
Our findings highlight a significant discordance between RS and PREDICT tools in predicting the benefits of adjuvant chemotherapy in patients with HR+, HER2- early breast cancer. While both tools aim to personalize cancer treatment, their discordance varies, suggesting that PREDICT could not substitute RS to predict adjuvant chemotherapy benefits regardless of patient risk classification. Further studies are needed to explore these relationships and optimize precision medicine approaches in breast cancer management.
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