Abstract A138: Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system
Authors: Xicola Rosa Munoz , Singh Vinit , Rafter Thomas , Liu Jing , Brown Quiana , Kashyap Nitu , Llor Xavier 
Published: September 2024

Three percent of cancers are due to inherited cancer-predisposing syndromes, the most common ones being Hereditary Breast and Ovarian cancer syndrome and Lynch syndrome. Surveillance and preventive measures among diagnosed individuals lead to early detection, prevention of future cancers, and appropriate treatment modalities ultimately resulting in lower cancer mortality. Thus, identifying these individuals through genetic testing is of most importance. While guidelines have been drafted to identify people who need to be ruled out based on personal and family history of cancer, less than 30% of qualifying individuals are currently tested and these numbers are much worse among underserved communities. Lack of awareness, largely due to guideline complexity, has been documented as a critical factor for the low testing rates while clinician’s unconscious bias contributes to disparities. The objective of this project was to increase the identification of individuals at risk, especially among the underserved groups. We hypothesized that this could be accomplished by establishing a mechanism of automatic identification of candidates leveraging the electronic health records (EHR), the ARCAGEN-ID (At-Risk Cancer Genetic Syndrome Identification) system. Methods: An inclusion logic was designed based on 218 rules that evaluate personal and family history of specific cancers and age at diagnosis, relevant to NCCN/ACMG guidelines for genetic testing. Structured data was pulled from discrete fields in the EHR. External data was accessed by enabling the standard interoperability exchange of information system. The system was applied to the wellness registry, a cohort of 1,357,337 patients with an active EHR in our healthcare system. Results: The ARCAGEN-ID system identified 57,628 individuals at-risk (4.25%). Of those, 45,646 (79.2%) had no evidence of prior genetic test, cancer genetics evaluation, or referral. A manual chart review of 559 cases showed an identification accuracy rate of 96.2%. The ARCAGEN-ID identified a lower proportion of self-reported African Americans, Hispanics and Medicaid insured patients than the overall wellness registry (likely reflecting less complete relevant information in the EHR). However, patients in those categories were significantly overrepresented among the ones who were not previously referred for genetic testing. Thus, ARCAGEN-ID significantly increased the identification of individuals from minority groups by 12.7 to 23% in each category. Regarding criteria for inclusion, individuals identified only through ARCAGEN-ID were more likely identified because of family history of cancer only, representing 80.69%. In conclusion, a fully automated system that leverages the EHR was able to multiply by 5 the number of individuals who need to be ruled out for an inherited cancer syndrome while addressing the bias against underserved communities seen under current routine care.

Citation Format: Rosa Munoz Xicola, Vinit Singh, Thomas Rafter, Jing Liu, Quiana Brown, Nitu Kashyap, Xavier Llor. Decreasing disparities in inherited cancer syndrome identification through a systems approach, The At-Risk Cancer Genetic Syndrome Identification (ARCAGEN-ID) system [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A138.