Trial reportJCO oncology practice2025
The Trial Enrollment Diversity Dashboard for Acute Leukemia Clinical Research: Intervention Development and Cohort Analysis.
Trial report in JCO oncology practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
purposeParticipation 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.
methodsWe 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.
resultsThe 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]).
conclusionWe 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.