The Trial Enrollment Diversity Dashboard for Acute Leukemia Clinical Research: Intervention Development and Cohort Analysis.

Autor:	Hantel A; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.; Center for Bioethics, Harvard Medical School, Boston, MA., Walsh TP; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA., Li KY; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA., Awan S; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA., Littlejohn E; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA., Lathan CS; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.; Center for Bioethics, Harvard Medical School, Boston, MA., Abel GA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.; Center for Bioethics, Harvard Medical School, Boston, MA.
Jazyk:	angličtina
Zdroj:	JCO oncology practice [JCO Oncol Pract] 2024 Oct 01, pp. OP2400319. Date of Electronic Publication: 2024 Oct 01.
DOI:	10.1200/OP.24.00319
Abstrakt:	Purpose: Participation in acute leukemia clinical trials is inequitable across multiple sociodemographic categories. Tools that provide researchers with performance feedback on the representativeness of the patients they enroll are limited. We aimed to develop an electronic health record (EHR)-based dashboard to provide such feedback and to describe any enrollment inequities uncovered. Methods: We created a visual dashboard linking leukemia clinical trial registration and EHR data at the Dana-Farber Cancer Institute. Accuracy of a patient inclusion and assignment algorithm was tested with a target area under the receiver-operator curve (AUROC) of >0.90 against manual review. Demographic metric identification, visualization construction, and dashboard refinement were performed through stakeholder cognitive testing. Analysis of a recent 5-year cohort generated by the final algorithm assessed bivariate associations between enrollment and demographic metrics. Multivariable logistic regression included significant bivariate results. Results: The final algorithm assignment AUROC was 0.98. Metrics were identified and visualizations successfully constructed. Fourteen individuals participated in testing and identified areas for revision: category mergers, denominator filters, and data delivery preferences. In the initial cohort of 1,315 patients, 1,020 (77.6%) had enrolled in any study protocol: 553 (42.1%) in a treatment trial and 936 (71.2%) in a biobanking study. In a multivariable model, older age (odds ratio [OR], 0.83 [95% CI, 0.73 to 0.94]) and Non-Hispanic Black race-ethnicity (OR, 0.38 [95% CI, 0.18 to 0.82]) were associated with lower enrollment, and English primary language with higher enrollment (OR, 2.50 [95% CI, 1.30 to 4.79]). Conclusion: We developed a research participation equity performance feedback dashboard for clinical researchers, and we identified actionable inequities. Next steps include feasibility and efficacy testing as well as implementation.
Databáze:	MEDLINE
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