ArticleClinical trials (London, England)2023
Data-driven strategies for increasing patient diversity in Bristol Myers Squibb-sponsored US oncology clinical trials.
Article in Clinical trials (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed, 5 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsDetermining whether clinical trial findings are applicable to diverse, real-world patient populations can be challenging when the full demographic characteristics of enrolled patients are not consistently reported. Here, we present the results of a descriptive analysis of racial and ethnic demographic information for patients in Bristol Myers Squibb (BMS)-sponsored oncology trials in the United States (US) and describe factors associated with increased patient diversity.
methodsBMS-sponsored oncology trials conducted at US sites with study enrollment dates between 1 January 2013 and 31 May 2021 were analyzed. Patient race/ethnicity information was self-reported in case report forms. As principal investigators (PIs) did not report their own race/ethnicity, a deep-learning algorithm (ethnicolr) was used to predict PI race/ethnicity. Trial sites were linked to counties to understand the role of county-level demographics. The impact of working with patient advocacy and community-based organizations to increase diversity in prostate cancer trials was analyzed. The magnitude of associations between patient diversity and PI diversity, US county demographics, and recruitment interventions in prostate cancer trials were assessed by bootstrapping.
resultsA total of 108 trials for solid tumors were analyzed, including 15,763 patients with race/ethnicity information and 834 unique PIs. Of the 15,763 patients, 13,968 (89%) self-reported as White, 956 (6%) Black, 466 (3%) Asian, and 373 (2%) Hispanic. Among 834 PIs, 607 (73%) were predicted to be White, 17 (2%) Black, 161 (19%) Asian, and 49 (6%) Hispanic. A positive concordance was observed between Hispanic patients and PIs (mean = 5.9%; 95% confidence interval (CI) = 2.4, 8.9), a less positive concordance between Black patients and PIs (mean = 1.0%; 95% CI = -2.7, 5.5), and no concordance between Asian patients and PIs. Geographic analyses showed that more non-White patients enrolled in study sites in counties with higher proportions of non-White residents (e.g. a county population that was 5%-30% Black had 7%-14% more Black patients enrolled in study sites). Following purposeful recruitment efforts in prostate cancer trials, 11% (95% CI = 7.7, 15.3) more Black men enrolled in prostate cancer trials.
conclusionMost patients in these clinical trials were White. PI diversity, geographic diversity, and recruitment efforts were related to greater patient diversity. This report constitutes an essential step in benchmarking patient diversity in BMS US oncology trials and enables BMS to understand which initiatives may increase patient diversity. While complete reporting of patient characteristics such as race/ethnicity is critical, identifying diversity improvement tactics with the highest impact is essential. Strategies with the greatest concordance to clinical trial patient diversity should be implemented to make meaningful improvements to the diversity of clinical trial populations.
Indexed as
Identifiers
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.