• William R Carpenter, Seth Tyree, Yang Wu, Anne-Marie Meyer, Lisa DiMartino, Leah Zullig, and Paul A Godley.
• Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. bill.carpenter@unc.edu
• Clin Trials. 2012 Aug 1; 9 (4): 426-35.

BackgroundThe Institute of Medicine (IOM) has recommended that each person with cancer should have access to clinical trials, which have been associated with improving care quality and disparities. With no effective enrollment monitoring system, patterns of trial enrollment remain unclear.PurposeWe developed a population-based, statewide system designed to facilitate monitoring of cancer trial enrollment and targeting of future interventions to improve it.MethodsPerson-level cancer incidence data from the North Carolina Central Cancer Registry (NCCCR), person-level treatment trial accrual data from the National Cancer Institute (NCI), and county-level Area Resource Files (ARF) measures for 12 years, 1996-2007, were studied. Deidentified person-level data necessitated county-level analysis. Enrollment rates were estimated as the ratio of trial enrollment to cancer incidence for each race, gender, year, and county combination. Multivariable analysis examined factors associated with trial accrual. Sensitivity analyses examined spurious fluctuations and temporal discordance of incidence and enrollment.ResultsThe NCI treatment trial enrollment rate was 2.39% for whites and 2.20% for minorities from 1996 to 2007, and 2.88% and 2.47%, respectively, from 2005 to 2007. Numerous counties had no minority enrollment. The 2005-2007 enrollment rates for white and minority females was 4.04% and 3.59%, respectively, and for white and minority males was 1.74% and 1.36%, respectively. Counties with a medical school or NCI Community Clinical Oncology Program (CCOP)-affiliated practice had higher trial enrollment.LimitationsWe examined NCI trial accrual only - industry-sponsored and investigator-initiated trials were excluded; however, studies comprise the majority of all clinical trial participants. Delays in data availability may hinder the immediacy of population-based analyses.ConclusionsModel stability and consistency suggest that this system is effective for population-based enrollment surveillance. For North Carolina, it suggests a worsening disparity in minority trial enrollment, though our analyses elucidate targets for intervention. Regional enrollment variation suggests the importance of access to clinical research networks and infrastructure. Substantial gender differences merit further examination.

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