The usefulness of CanAssist breast in the assessment of recurrence risk in patients of ethnic Indian origin.
Ontology highlight
ABSTRACT: Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach. We report CAB risk assessment correlating with disease outcomes in multiple clinically high- and low-risk subgroups. In this retrospective cohort of 925 patients [median age-54 (22-86)] CAB had hazard ratio (HR) of 3 (1.83-5.21) and 2.5 (1.45-4.29), P = 0.0009) in univariate and multivariate analysis. CAB's HR in sub-groups with the other determinants of outcome, T2 (HR: 2.79 (1.49-5.25), P = 0.0001); age [< 50 (HR: 3.14 (1.39-7), P = 0.0008)]. Besides application in node-negative patients, CAB's HR was 2.45 (1.34-4.47), P = 0.0023) in node-p
SUBMITTER: Chandra Doval D
PROVIDER: S-EPMC8187842 | biostudies-literature | 2021 Oct
REPOSITORIES: biostudies-literature
ACCESS DATA