Navigating the clinical trial maze: Identifying barriers to enrollment among patients with advanced cancer in a community-academic partnership.
Authors: Aakash Desai, Madhan Srinivasan Kumar, Tiffany Huggins, Ellen McNeeley, Nusrat Jahan, Furhan Yunus, Maya Khalil, Jan Ole Kemnade, Bassel F. El-Rayes, Mehmet Akce, Rebecca Christian Arend
Journal: Journal of Clinical Oncology (2024)

e15191 Background: Further research is required to pinpoint barriers responsible for disparities in clinical trial enrollment. In Alabama, a community-academic partnership has been established to broaden clinical trial access and eliminate disparities. This study aims to examine referral patterns for phase 1 and precision oncology clinical trials and identify screening and enrollment barriers. Methods: Between July-December 2023, we conducted weekly virtual meetings for patients (n=115) seen at Infirmary Health Oncology clinic (Mobile, AL) [community site] who had Next Generation Sequencing data and were potentially eligible for a clinical trial. We recorded key sociodemographic variables, retrospectively analyzed genomic data, examined trial enrollment, and explored non-participation reasons. Descriptive statistics were employed for analysis. Results: A total of 115 patients were included in this retrospective study. The median age was 70 years (range: 38-90), 60% were male vs. 40% female, and the majority were Caucasian (63%). The most common tumor types were: non-small cell lung cancer (27.8%), colorectal cancer (13.0%), pancreatic cancer (11.3%), small cell lung cancer (10.4%), and breast cancer (6.9%). We found that genomic alterations commonly included: TP53 (34.7%), KRAS (20%), PTEN (13.9%), NF (11.3%), CDK (7.8%), and PIK3CA (6.1%). Of the patients prescreened, 11.3% did not return to clinic for subsequent follow up visits and 16.5% did not have an available trial. 33% were pre-screened for clinical trial but did not meet trial eligibility criteria because of cancer stage, number of prior therapies therapy, or some other exclusion criteria. Among these, 18.4% were not eligible due to HIV or immunosuppressed status, a second malignancies, brain metastasis or poor performance status. 45 of the 115 patients (39.1%) had a clinical trial available at UAB. However, 26 (57.7%) of these patients were ultimately unable to participate due to: technical factors (n=10, 38.5%) [biopsy not obtainable/QNS/repeat biopsy needed], patient preference (n=9, 34.6%) and physician preference (n=7, 26.9%). Of the 19 (42.22%) remaining patients who were potentially eligible, only 3 (15.8%) patients were eventually enrolled on a clinical trial. All 3 patients went onto disease specific phase 2-3 trials, rather than a precision medicine or phase 1 trial. Conclusions: Our study highlights key factors affecting referrals, screening, and barriers to clinical trial enrollment. Early referrals and improved screening processes are crucial for considering trials, with prior therapy lines and functional status playing significant roles in trial non-enrollment. Our community-academic partnership aims to overcome barriers like travel and trial access, while also leveraging technology (eg. AI and databases) to address technical obstacles in trial participation.