Participant Engagement Unit

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ABSTRACT: PARTICIPANT ENGAGEMENT UNIT (PEU) H/L tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (<50 years of age) diagnoses compared to other H/L subgroups. Moreover, Mexican H/L showed higher prevalence of rectal cancer cases compared to other H/L and NHW. Our most current analyses using the California Cancer Registry data (unpublished results), including data for 52,557 H/L diagnosed between 1995-2017, show that ~43% of US H/L are diagnosed before 62 years old (median age of diagnosis across NHW and H/L). Moreover, they show a greater proportion of distant tumor diagnoses compared to NHW, and greater proportion of metastatic CRC. Overall, in spite of the various disparities observed among H/L that contribute to their cancer burden, there are scarce studies that have focused on this minority population, contributing to further disparities in this group. Therefore, there is an urgent need to increase resources that will contribute much needed data about the tumor landscape of US H/L taking into account genetic ancestry. Therefore, to address the lack of knowledge about the CRC tumor landscape among H/L, and increase engagement and participation of H/L in genetic research, we propose to develop effective and culturally tailored participant engagement approaches tailored to H/L, through the following specific aims, 1) to address the knowledge gap in H/L CRC participation using a culturally appropriate direct cancer participant engagement platform for recruiting, consenting, and communicating genomic risk based on cancer genomic sequencing; 2) to deploy current best practices for collection and quality assessment of biospecimens and relevant clinical and epidemiological data among H/L participants; 3) To develop and assess the effectiveness of using culturally sensitive strategies for communication in clinical settings, that consider participant preferences in receiving results from genomic analyses, and return of their clinical and epidemiological data; and 4) To continuously improve participant engagement by assessing benchmarks and working with the Engagement Optimization Unit to identify strategies to optimize informed consent, communication of results, and follow-up, taking into account the patients and providers perspectives. The results of these aims will be integrated across an engagement optimization framework to create a robust and validated model for engaging H/L cancer patients into cancer genomic research studies.