The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Disparity of Race Reporting and Representation in Clinical Trials Leading to Cancer Drug Approvals From 2008 to 2018
Open accessAbstract
IMPORTANCE: Representative racial/ethnic participation in research, especially in clinical trials that establish standards of care, is necessary to minimize disparities in outcomes and to uphold societal equity in health care. OBJECTIVE: To evaluate the frequency of race reporting and proportional race representation in trials supporting US Food and Drug Administration (FDA) oncology drug approvals. DESIGN, SETTING, AND PARTICIPANTS: Database study of all reported trials supporting FDA oncology drug approvals granted between July 2008 and June 2018. Primary reports of trials were obtained from PubMed and ClinicalTrials.gov. Food and Drug Administration approvals were identified using the FDA archives. The US population-based cancer estimates by race were calculated using National Cancer Institute-Surveillance, Epidemiology, and End Results and US Census databases. MAIN OUTCOMES AND MEASURES: Primary outcomes were the proportion of trials reporting race and the proportion of patients by race participating in trials. Secondary outcomes included race subgroup analyses reporting and gaps between race proportion in trials and the US population. Descriptive statistics, Fisher exact, and χ2 tests were used to analyze the data. Proportions and odds ratios (OR) with 95% CIs were reported. RESULTS: Among 230 trials with a total of 112 293 participants, 145 (63.0%) reported on at least 1 race, 18 (7.8%) documented the 4 major races in the United States (white, Asian, black, and Hispanic), and 58 (25.2%) reported race subgroup analyses. Reporting on white, Asian, black, and Hispanic races was included in 144 (62.6%), 110 (47.8%), 88 (38.2%), and 23 (10.0%) trials, respectively. Between July 2008 and June 2013 vs July 2013 and June 2018, the number of trials reporting race (45 [56.6%] vs 100 [67.1%]; OR, 1.63; 95% CI, 0.93-2.87; P = .09) and race subgroup analysis (13 [16.1%] vs 45 [30.2%]; OR, 2.26, 95% CI, 1.16-4.67; P = .03) changed minimally and varied across races. Whites, Asians, blacks, and Hispanics represented 76.3%, 18.3%, 3.1% and 6.1% of trial participants, respectively, and the proportion for each race enrolled over time changed nominally (blacks, 3.6% vs 2.9% and Hispanics, 5.3% vs 6.7%) from July 2008 to June 2013 vs July 2013 to June 2018. Compared with their proportion of US cancer incidence, blacks (22% of expected) and Hispanics (44% of expected) were underrepresented compared with whites (98% of expected) and Asians (438% of expected). CONCLUSIONS AND RELEVANCE: Race and race subgroup analysis reporting occurs infrequently, and black and Hispanic races are consistently underrepresented compared with their burden of cancer incidence in landmark trials that led to FDA oncology drug approvals. Enhanced minority engagement is needed in trials to ensure the validity of results and reliable benefits to all.
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“In addition, geographic, sociocultural and economic disparities in access to enrollment, have led to a remarkable underrepresentation of several groups in these studies.”
From Multimodal biomedical AI (2022) · cites this paper as [32]
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“Among these, only 3.1 and 6.1% of trial participants identified as Black and Hispanic, respectively.”
From Enablers and barriers of clinical trial participation in adult patients from minority ethnic groups: a systematic review (2025) · cites this paper as [18]
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“A 2019 review revealed that of the cancer therapies approved by the US Food and Drug Administration (FDA) between 2008 and 2018, only 63% of the relevant trials reported race-related data [18].”
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“This limits the generalizability of results and leads to a scenario whereby widespread underrepresentation in biomedical research further perpetuates existing disparities 32 .”
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Metadata
- Authors
- Loree, J. M., Anand, S., Dasari, A., Unger, J. M., Gothwal, A., Ellis, L. M., Varadhachary, G., Kopetz, S., Overman, M. J., & Raghav, K.
- Affiliations
- BC Cancer Agency (CA)
- The University of Texas MD Anderson Cancer Center (US)
- Fred Hutch Cancer Center (US)
- Baylor University (US)
- Corresponding author
- Raghav, Kanwal
- ORCID
- Venue
- JAMA Oncology
- Publisher
- American Medical Association (AMA)
- Published
- 2019-10-10
- Volume
- 5
- Issue
- 10
- Pages
- e191870
- ISSN
- 2374-2437 (ISSN-L)
- PMC
- PMC6696743
- OpenAlex
- W2969031691
- Semantic Scholar
- 7ef4c8e3b560e1041587d5370115a6db62f37be5
- Cited by
- 570
- References
- 30
- Citations by year
- 2026: 59 · 2025: 67 · 2024: 89 · 2023: 104 · 2022: 120 · 2021: 99 · 2020: 31
- FWCI
- 57.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Oncology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (UG1CA189974, P30CA016672)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Social Sciences › Anthropology › Race, Genetics, and Society
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- racial disparities, oncology drug approval, FDA drug approval, cancer clinical trials, health equity, racial disparities in cancer outcomes, racial disparities in cancer survival, racial disparities in cancer incidence, racial disparities in cancer mortality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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