ArticleTherapeutic innovation & regulatory science2024
Quantifying Clinical Trial Diversity in Pivotal Registration Trials of FDA Novel Drug Approvals.
Article in Therapeutic innovation & regulatory science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed, 1 citations in OpenAlex.
- Lessons learned from the conduct of inpatient clinical trials in a pandemic.Journal of clinical and translational science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHealth care inequity includes the lack of adequate representation of various populations in clinical trials. Government, academic and industry organizations have highlighted these issues and committed to actions to improve. In order to assess the current status and future success of these initiatives a quantitative objective measure to assess the state of clinical trial diversity is needed.
methodsFDA review documents for all novel drug approvals from January 2022 through March 2023 were assessed using a scorecard that considers diversity across different demographic subgroups including age (≥ 65 years old), sex (female), race (Black and Asian) and ethnicity (Hispanic/Latino). The scorecard assigns each drug a letter grade, between A and F, for each subgroup (and overall) based on (1) the percent of each sub-population included in the trials and grades relative to the percent of the US population per the 2020 Census, (2) the number of participants from each subpopulation that received the novel new drug in the trials, (3) the incidence or prevalence of the disease/condition in each of the sub-populations.
resultsThe FDA approved 49 novel new drugs for 50 indications (one drug was simultaneously approved for two indications). There was good representation of elderly and females with only two drugs receiving a D grade in either of these sub-populations. In contrast, Black (5 F grades) and Hispanic (4 F grades) representation was often inadequate. There were 10 drugs (20.0%) where there were no Black participants receiving the novel new drug and 16 (32.0%) approvals where there were 1-9 Black participants receiving the novel drug. In the Hispanic/Latino population there were 4 (8.0%) approvals with no Hispanic participants receiving the novel drug and 15 (30.0%) approvals where there were 1-9 Hispanic participants receiving the drug.
conclusionsThis scorecard provides an objective quantitative approach to assess the current state of diversity in clinical trials supporting new drug approvals. Substantial improvement in racial and ethnic representation is needed. Meaningful change will require actions and cooperation among all stakeholders to address this multifaceted issue and will take commitment, perseverance, and appropriate incentives.
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.