How current reporting practices may mask differences: A call for examining cancer-specific demographic enrollment patterns in cancer treatment clinical trials

Abstract

Background: A lack of diversity among clinical trial (CT) participants remains a critical problem. Few studies have examined recruitment variability in cancer treatment CTs by cancer type. Given the increasing organ-specific specialization of oncologic care, an understanding of this variability may affect institutional recruitment practices. Methods: This study examines three data sources from 2010 through 2014. The analyzed sample includes 3,580 CT participants identified in the institutional Clinical Trials Management System (CTMS) database and 20,305 incident cases of invasive cancer within a Comprehensive Cancer Center (CCC) institutional catchment area. A total of 341,114 incident cases of primary invasive cancer were identified through the California Cancer Registry (CCR). The primary study measurements were sociodemographic characteristics of the three populations (age, sex, race/ethnicity, and health insurance). Results: Racial/ethnic disparities were observed, with more incident cases of Whites seen in cancer center (68%) and enrolled in CTs (72%) compared to incident cases in catchment area (67%) (p < 0.001) overall. More older adults (65) were enrolled in prostate cancer CTs (58%) than seen in cancer center (45%) (p < 0.001). Alternatively, fewer older adults were enrolled in breast and colorectal CTs than seen in cancer center (p < 0.001). Among colon (p < 0.001), breast (p < 0.001), and prostate (p<0.001) cancer types, insurance type significantly varied between incident cases in catchment area, cancer center, and among CT participants. For colorectal cancer, no difference in sex distribution was observed overall. A significant difference in insurance type within each cancer type was observed (p < 0.001). Conclusions: These findings suggest that reporting overall recruitment frequencies may mask differences by cancer type. Keywords: Representativeness in clinical trials, Cancer disparities, Recruitment science, Precision medicine