Comparison of Recurrence Risk Prediction by the CanAssist Breast Test and the PREDICT Online Tool in Early Breast Cancer Patients

早期乳腺癌患者中CanAssist乳腺检测与PREDICT在线工具复发风险预测的比较

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Abstract

Introduction Several methods, such as multi-marker (both gene/protein) tests and online/free tools, are available for the prognostication of early breast cancer (EBC) patients. This article compares the risk assessment between the immunohistochemistry-based (IHC) CanAssist Breast (CAB) test and the online/free prognostic tool PREDICT in EBC patients treated at Rajiv Gandhi Cancer Institute and Research Centre (RGCIRC) between May 2017 and June 2022. Methodology The current study cohort comprises 130 patients. Risk proportions were assessed by CAB and the online/free tool PREDICT. Concordance between the risk groups of CAB and PREDICT was assessed by the kappa coefficient, which was used to evaluate the significance. Results The low-risk (LR) and high-risk (HR) proportions for CAB and PREDICT were 61:39 and 46:54 percent, respectively. CAB stratified a significantly (P=0.027) higher number of patients as LR compared to PREDICT. Interestingly, in the subgroup analysis of the age and clinicopathological parameters CAB stratified 28% of patients with grade 3 tumors as LR, whereas PREDICT stratified all grade 3 tumors as HR. The overall treatment compliance using CAB was 89%. Conclusion CAB, a relatively new multi-marker prognostic test entailing five relevant protein biomarkers provides augmented and relevant prognostic information over PREDICT in all patients. Thus, CAB helps optimize treatment for HR+/HER2- EBC patients as its risk stratification is independent of age and clinical parameters and assigns recurrence risk based on tumor biology.

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