Prognostic validation of artificial intelligence (AI)–based Stratipath breast risk stratification in TAILORx.

Abstract

555 Background: Stratipath Breast is an AI-based prognostic medical device for risk stratification of early-stage breast cancer using routine H&E-stained histopathology whole slide images (WSIs). AI-based analyses of histopathology slides offer an alternative to costly and logistically demanding genomic assays. In this study, the prognostic performance of Stratipath Breast was validated in the TAILORx trial (NCT00310180). Methods: WSIs from patients enrolled in TAILORx were analyzed by Stratipath Breast. After histopathology quality control and availability of clinical endpoints and WSIs, 5,519 patients were included. Stratipath Breast binary risk category, multi-level risk group, and continuous risk score were evaluated. The prognostic performance was analyzed by Kaplan-Meier statistic and log rank test, as well as concordance index (C-index). Multivariable Cox Proportional Hazard (PH) model adjusting for age, tumor size, histologic subtype and continuous Oncotype DX recurrence score (RS), both without and with histologic grade, was used to assess independent prognostic value. Recurrence-free interval (RFI) and distant recurrence-free interval (DRFI) were evaluated. Results: 53.9% (2,975/5,519) of patients were classified as Stratipath low risk and 46.1% (2,544/5,519) as high risk. A significant association of Stratipath risk category and group with RFI and DRFI was confirmed (p < 0.05). In multivariable Cox PH analyses, Stratipath high-risk category was an independent prognostic factor associated with worse outcomes (RFI HR = 1.54, 95%CI:1.29-1.84, p < 0.05; DRFI HR = 1.61, 95%CI: 1.30-1.99, p < 0.05). Stratipath risk category remained significant in multivariable analysis when histologic grade was included, whereas grade did not. RS remained prognostic significant in multivariable analyses together with Stratipath Breast, indicating potentially complementary prognostic information. C-index improved with inclusion of Stratipath Breast together with clinical variables and RS, exceeding that of grade. Conclusions: In the TAILORx trial Stratipath Breast was found to provide significant prognostic value. Stratipath Breast also provided independent prognostic value in multivariable analysis adjusting for standard clinicopathologic factors and RS. These findings support the clinical relevance of AI-driven morphology-based biomarkers for breast cancer risk stratification.