Abstract Background: Both clinicopathologic factors and genomic tests have been shown to be prognostic for risk of late distant recurrence (DR); however, few studies have characterized differential patient stratification.Breast Cancer Index (BCI) is a validated gene expression assay for patients with early-stage HR+ breast cancer that provides a prognostic result for high vs low risk of late distant recurrence and a separate predictive result (based on the HoxB13/IL17BR [H/I] ratio) for high vs low likelihood of benefit from extended endocrine therapy. Thus four categories of results are possible based on a patient's tumor biology. To better understand how patient stratification is affected by a combination of clinicopathologic and genomic factors, this study examined BCI assay results within clinicopathologic risk categories based on tumor size and grade. Methods: This study utilized data from the BCI Clinical Database for Correlative Studies, an IRB-approved de-identified database which contains clinicopathologic and molecular variables from 19,126 clinical cases submitted for BCI testing. Clinicopathologic variables, abstracted from pathology reports, were available for a subset of these cases. This analysis evaluated cases from LN- patients with available clinicopathologic data. Chi-squared tests were used to compare BCI results between tumor size and grade subgroups. Results: Analyses included 3843 LN- patients (median age 59.1y; range 26-89y; 74% ≥50y), of which 31%, 52%, 17% were Grade 1, 2, and 3, respectively, and 5%, 22.7%, 48.9%, 21.7%, and 1.6% were T1mi/a, T1b, T1c, T2, and T3, respectively. In analysis based on tumor size, there was a wide distribution of individual BCI Prognostic scores in all tumor size subsets; however, the proportion of patients classified as high risk increased with larger tumor size (T1a/b 39.0%, T1c 50.1%, T2 61.0%; p<.0001). In contrast, BCI Predictive (H/I) was not as strongly correlated with size, with a modestly larger proportion of patients classified as High H/I with larger tumor size (T1a/b 37.2%, T1c 40.5%, and T2 45.3%; p=.005). Within each tumor size category, the proportion of patients classified as BCI High Risk and High H/I increased with tumor grade (p<.0001). However, there was a wide distribution of individual risk assessments by BCI Prognostic and stratification by BCI Predictive (H/I) in all size + grade subsets. In patients with the most favorable clinicopathologic risk profile (T1a/b, G1), BCI classified 20% as high risk, 68% of whom also had High H/I. Conclusion: While BCI results correlated with tumor size and grade, BCI identified substantial proportions of patients with favorable clinicopathologic features as high risk for late DR and apparent high likelihood of benefit from EET; conversely, BCI also identified patients with high risk clinicopathologic features as low risk for late distant recurrence and apparent low likelihood of benefit from EET. These findings help to differentiate between genomic-based and clinicopathologic-based risk/benefit assessment for patients considering EET. Citation Format: Mayordomo J, Falkson C, Kepes J, Israel MA, Schroeder BE, Schnabel CA, Elias A. Correlation of breast cancer index (BCI) prognostic and predictive results to clinicopathologic risk groups in early stage HR+ breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-07-12.