Evidence map›Paper›PMID 39990602›Full record

ArticleContemporary clinical trials communications2025

Demographic clinical trial diversity assessment methods: Use of real-world data.

Hua Chen, Nnadozie Emechebe, Sudeep Karve, Leon Raskin, Jailene Leal, Ning Cheng, Wendy Sebby, Kim Ribeiro, Samuel Crawford

Abstract read
In one paragraph

Article in Contemporary clinical trials communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hua ChenDepartment of Pharmaceutical Health Outcomes and Policy, College of Pharmacy, University of Houston, USA.
Nnadozie EmechebeAbbVie, Inc, North Chicago, IL, USA.
Sudeep KarveAbbVie, Inc, North Chicago, IL, USA.
Leon RaskinAbbVie, Inc, North Chicago, IL, USA.
Jailene LealAbbVie, Inc, North Chicago, IL, USA.
Ning ChengAbbVie, Inc, North Chicago, IL, USA.
Wendy SebbyAbbVie, Inc, North Chicago, IL, USA.
Kim RibeiroAbbVie, Inc, North Chicago, IL, USA.
Samuel CrawfordAbbVie, Inc, North Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diversity in clinical trials is defined by the inclusion of clinical trial participants from various demographic groups that are representative of the broader population impacted by a disease state. Diversity in clinical trials is critical in identifying potential differences in safety and efficacy of treatments across races, ethnicities, ages, sexes, or other variables. In the United States, clinical trial diversity is often benchmarked against US Census data, which may limit the representativeness of patient demographics in clinical trials. Disease-specific, demographic estimates from real-world data (RWD) can facilitate benchmarking of clinical trials, support trial enrollment and the development of trial diversity plans. Notably, development and dissemination of these estimates from RWD can be challenging without a standardized process. To address this issue, we developed a new evaluation framework to assess patient demographics and characteristics within specific disease populations using RWD and disease population estimates. Suitable databases were identified using predefined criteria such as accessibility to patient-level data, availability of all demographic variables of interest, sufficient sample size of the disease population, and availability of population weights to enhance generalizability. Concurrent data were gathered via targeted literature reviews for each disease condition. Together, this data was used to create disease-specific, demographic estimate profiles to inform diverse enrollment goals for prospective clinical trials. We present two examples of application of this framework to illustrate the results in the case of two disease states, rheumatoid arthritis and stroke.

Indexed as

BenchmarkingClinical trial diversityDisease populationDiversity planHealth equityReal-world dataRWD

Identifiers

PMID39990602
PMCPMC11847083

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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.