To promote health equity within the United States (US), randomized clinical trials should strive for unbiased representation. Thus, there is impetus to identify demographic disparities overall and by disease category in US clinical trial recruitment, by trial phase, level of masking, and multi-center status, relative to national demographics. A systematic review and meta-analysis were conducted using MEDLINE, Embase, CENTRAL, and ClinicalTrials.gov, between 01/01/2008 to 12/30/2019. Clinical trials (N = 5,388) were identified based on the following inclusion criteria: study type, location, phase, and participant age. Each clinical trial was independently screened by two researchers. Data was pooled using a random-effects model. Median proportions for gender, race, and ethnicity of each trial were compared to the 2010 US Census proportions, matched by age. A second analysis was performed comparing gender, race, and ethnicity proportions by trial phase, multi-institutional status, quality, masking, and study start year. 2977 trials met inclusion criteria (participants, n = 607,181) for data extraction. 36% of trials reported ethnicity and 53% reported race. Three trials (0.10%) included transgender participants (n = 5). Compared with 2010 US Census data, females (48.3%, 95% CI 47.2-49.3, p < 0.0001), Hispanics (11.6%, 95% CI 10.8-12.4, p < 0.0001), American Indians and Alaskan Natives (AIAN, 0.19%, 95% CI 0.15-0.23, p < 0.0001), Asians (1.27%, 95% CI 1.13-1.42, p < 0.0001), Whites (77.6%, 95% CI 76.4-78.8, p < 0.0001), and multiracial participants (0.25%, 95% CI 0.21-0.31, p < 0.0001) were under-represented, while Native Hawaiians and Pacific Islanders (0.76%, 95% CI 0.71-0.82, p < 0.0001) and Blacks (17.0%, 95% CI 15.9-18.1, p < 0.0001) were over-represented. Inequitable representation was mirrored in analysis by phase, institutional status, quality assessment, and level of masking. Between 2008 to 2019 representation improved for only females and Hispanics. Analysis stratified by 44 disease categories (i.e., psychiatric, obstetric, neurological, etc.) exhibited significant yet varied disparities, with Asians, AIAN, and multiracial individuals the most under-represented. These results demonstrate disparities in US randomized clinical trial recruitment between 2008 to 2019, with the reporting of demographic data and representation of most minorities not having improved over time.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807581PMC
http://dx.doi.org/10.1038/s41598-022-23664-1DOI Listing

Publication Analysis

Top Keywords

clinical trials
12
united states
8
states randomized
8
randomized clinical
8
systematic review
8
review meta-analysis
8
clinical trial
8
trial phase
8
inclusion criteria
8
gender race
8

Similar Publications

Objective: Previous experiments have demonstrated that BGM0504, a GLP-1R/GIPR dual agonist drug by molecular dynamics-guided optimization, had enhanced agonistic activity compared to tirzepatide. This study aims to investigate its safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) in Chinese healthy volunteers.

Methods: A randomized, double-blind, placebo-controlled and dose-escalation Phase I study was conducted as follows: a single dose (2.

View Article and Find Full Text PDF

Patient stratification remains a challenge for optimal treatment of prostate cancer (PCa). This clinical heterogeneity implies intra-tumoural heterogeneity, with different prostate epithelial cell subtypes not all targeted by current treatments. We reported that such cell subtypes are traceable in liquid biopsies through representative transcripts.

View Article and Find Full Text PDF

Objective: To determine the feasibility, efficacy, and safety of cold stored compared to room temperature platelet transfusion in patients with traumatic brain injury.

Summary Background Data: Data demonstrating the safety and efficacy of cold stored platelet transfusion are lacking following traumatic brain injury.

Methods: A phase 2, randomized, open label, clinical trial was performed at a single U.

View Article and Find Full Text PDF

Traditional drug discovery methods such as wet-lab testing, validations, and synthetic techniques are time-consuming and expensive. Artificial Intelligence (AI) approaches have progressed to the point where they can have a significant impact on the drug discovery process. Using massive volumes of open data, artificial intelligence methods are revolutionizing the pharmaceutical industry.

View Article and Find Full Text PDF

This literature review explores the emerging role of digital twin (DT) technology in ophthalmology, emphasizing its potential to revolutionize personalized medicine. DTs integrate diverse data sources, including genetic, environmental, and real-time patient data, to create dynamic, predictive models that enhance risk assessment, surgical planning, and postoperative care. The review highlights vital case studies demonstrating the application of DTs in improving the early detection and management of diseases such as glaucoma and age-related macular degeneration.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!