Increasing Racial and Ethnic Equity, Diversity, and Inclusion in Cancer Treatment Trials: Evaluation of an ASCO-Association of Community Cancer Centers Site Self-Assessment. Issue 4 (11th April 2023) - Guerra, Carmen; Pressman, Alice; Hurley, Patricia; Garrett-Mayer, Elizabeth; Bruinooge, Suanna S.; Howson, Alexandra; Kaltenbaugh, Melinda; Hanley Williams, Jen; Boehmer, Leigh; Bernick, Lea Ann; Byatt, Leslie; Charlot, Marjory; et al.
Abstract : Clinical trial participants do not reflect the racial and ethnic diversity of people with cancer. ASCO and the Association of Community Cancer Centers collaborated on a quality improvement study to enhance racial and ethnic equity, diversity, and inclusion (EDI) in cancer clinical trials. The groups conducted a pilot study to examine the feasibility, utility, and face validity of a two-part clinical trial site self-assessment to enable diverse types of research sites in the United States to (1) review internal data to assess racial and ethnic disparities in screening and enrollment and (2) review their policies, programs, procedures to identify opportunities and strategies to improve EDI. Overall, 81% of 62 participating sites were satisfied with the assessment; 82% identified opportunities for improvement; and 63% identified specific strategies and 74% thought the assessment had potential to help their site increase EDI. The assessment increased awareness about performance (82%) and helped identify specific strategies (63%) to increase EDI in trials. Although most sites (65%) were able to provide some data on the number of patients that consented, only two sites were able to provide all requested trial screening, offering, and enrollment data by race and ethnicity. Documenting and evaluating such data are critical steps toward improving EDI and are key to identifying and addressing disparities more broadly. ASCO and Association of Community Cancer Centers will partner with sites to better understand their processes and the feasibility of collecting screening, offering, and enrollment data in systematic and automated ways.