Abstract P3-09-02: Risk stratification using clinical risk factors and genetic variants in a personalized screening trial
Authors: Y Shieh, E Ziv, M Eklund, L Sabacan, R Firouzian, L Madlensky, H Anton-Culver, A Borowsky, A LaCroix, A Naeim, B Parker, L van't Veer, L Esserman, J Tice
Journal: Cancer Research (2018)

Abstract Introduction: Tailoring breast cancer screening according to individual risk may represent an improvement over the current practice of age-based screening. WISDOM (Women Informed to Screen Depending on Measures of Risk) is an ongoing randomized trial comparing the safety, efficacy, cost, and patient acceptability of personalized versus annual screening. Women in the personalized arm receive screening recommendations based on sequencing of 9 genes associated with hereditary breast cancer and a 5-year risk estimate from the Breast Cancer Surveillance Consortium (BCSC) risk model modified by a polygenic risk score (PRS) comprised of 75 single nucleotide polymorphisms. WISDOM represents the first-ever use of a PRS to prospectively modify risk estimates and allows comparison of risk model performance in a population-based setting. Thus, we evaluated the risk estimates generated by: 1) the Breast Cancer Risk Assessment Tool (BCRAT) based on the Gail model, 2) the BCSC model, and 3) the BCSC model modified by the PRS (BCSC-PRS). Methods: We analyzed participants in the personalized screening arm of the WISDOM Study (NCT02620852). The trial opened in October 2016 and is enrolling participants aged 40-74 years. Participants' self-reported demographic and risk factor information were collected through an online portal. Genotyping of participants in the personalized arm was done using a custom panel from Color Genomics. 5-year risk estimates were generated using the BCRAT (2011 version), BCSC, and BCSC-PRS models. In the latter, the PRS was used as a Bayesian likelihood ratio to modify the BCSC 5-year risk estimate. We compared the distributions of BCRAT, BCSC, and BCSC-PRS risk estimates around a low-risk (&amp;lt;1%) and moderately high-risk (≥3%) threshold using a paired statistical test (McNemar). Results: To date, WISDOM has enrolled 2,065 participants, of whom 1,157 are in the personalized arm and 830 have completed risk assessment. The median age was 57 years (interquartile range, IQR 49-64). 83% were Caucasian, 2% African-American, and 7% Asian. 8% self-reported as Hispanic. The median 5-year risk was 1.7% (IQR 1.1-2.3%) using the BCRAT, 1.6% (IQR 1.1-2.3%) using the BCSC model, and 1.5% (IQR 0.9-2.7%) using the BCSC-PRS model. The BCSC-PRS model classified more women into the low (&amp;lt;1%) and moderately high (≥3%) risk categories compared with the BCRAT (p &amp;lt; 0.001) and BCSC model (p &amp;lt; 0.001), Table. 5-year risk classification according to the BCRAT, BCSC and BCSC-PRS models &amp;lt;1%1-3%≥3% n (%)n (%)n (%)Gail161 (19)556 (67)113 (14)BCSC159 (19)568 (68)103 (12)BCSC-PRS275 (33)379 (46)176 (21) Discussion: Adding a PRS to the BCSC model categorized significantly more women below the low-risk threshold and above the moderately high-risk threshold compared with the BCSC model and BCRAT. Furthermore, the BCSC and BCRAT generated similar distributions of risk estimates. Follow-up with incident breast cancer data is needed to determine whether the reclassification provided by the PRS improves risk stratification and clinical outcomes. However, our preliminary findings suggest that incorporating genetic variants into a validated clinical model is feasible and could enhance risk prediction. Citation Format: Shieh Y, Ziv E, Eklund M, Sabacan L, Firouzian R, Madlensky L, Anton-Culver H, Borowsky A, LaCroix A, Naeim A, Parker B, van't Veer L, Esserman L, Tice J, WISDOM Study and Athena Network Investigators WS. Risk stratification using clinical risk factors and genetic variants in a personalized screening trial [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 P3-09-02.