Impact of Clinical Trial Design on Recruitment of Racial and Ethnic Minorities.

Knowledge related to how oncology treatment trial design influences enrollment of racial and ethnic minorities is limited. Rigorous identification of clinical trial design parameters that associate favorably with minority accrual provides educational opportunities for individuals interested in designing more representative treatment trials. We identified oncology trials with a minimum of 10 patients at an NCI-Designated Comprehensive Cancer Center from 2010 to 2021. We defined a study endpoint of racial and ethnic minority accrual greater than zero. Multivariable logistic regression was used to determine whether co-variables predicted our study endpoint. P-values of less than 0.05 were considered significant. A total of 352 cancer trials met eligibility criteria. These studies enrolled a total of 7981 patients with a total of 926 racial and ethnic minorities leading to a median enrollment of 10%. Trials open in community sites (yes versus no) were more likely to have a minority patient (OR, 2.21; 95% CI, 1.02-4.96) as well as pilot/phase I studies compared to phase II/III (OR, 3.19; 95% CI, 1.34-8.26). Trials incorporating immunotherapy (yes versus no) were less likely to have a minority patient (OR, 0.47; 95% CI, 0.23-0.94). Trials open in community sites as well as early phase treatment studies were more likely to accrue minority patients. However, studies including immunotherapy were less likely to accrue racial and ethnic minorities. Knowledge gained from our analysis may help individuals design oncology treatment trials that are representative of more diverse populations.

Sharing behavioral data through a grid infrastructure using data standards.

OBJECTIVE: In an effort to standardize behavioral measures and their data representation, the present study develops a methodology for incorporating measures found in the National Cancer Institute's (NCI) grid-enabled measures (GEM) portal, a repository for behavioral and social measures, into the cancer data standards registry and repository (caDSR). METHODS: The methodology consists of four parts for curating GEM measures into the caDSR: (1) develop unified modeling language (UML) models for behavioral measures; (2) create common data elements (CDE) for UML components; (3) bind CDE with concepts from the NCI thesaurus; and (4) register CDE in the caDSR. RESULTS: UML models have been developed for four GEM measures, which have been registered in the caDSR as CDE. New behavioral concepts related to these measures have been created and incorporated into the NCI thesaurus. Best practices for representing measures using UML models have been utilized in the practice (eg, caDSR). One dataset based on a GEM-curated measure is available for use by other systems and users connected to the grid. CONCLUSIONS: Behavioral and population science data can be standardized by using and extending current standards. A new branch of CDE for behavioral science was developed for the caDSR. It expands the caDSR domain coverage beyond the clinical and biological areas. In addition, missing terms and concepts specific to the behavioral measures addressed in this paper were added to the NCI thesaurus. A methodology was developed and refined for curation of behavioral and population science data.