Twenty years of participation of racialised groups in type 2 diabetes randomised clinical trials: a meta-epidemiological review
Bibliographic record
Abstract
AIMS/HYPOTHESIS: Type 2 diabetes mellitus prevalence is increasing globally and the greatest burden is borne by racialised people. However, there are concerns that the enrolment of racialised people into RCTs is limited, resulting in a lack of ethnic and racial diversity. This may differ depending whether an RCT is government funded or industry funded. The aim of this study was to review the proportions of racialised and white participants included in large RCTs of type 2 diabetes pharmacotherapies relative to the disease burden of type 2 diabetes in these groups. METHODS: The Ovid MEDLINE database was searched from 1 January 2000 to 31 December 2020. English language reports of RCTs of type 2 diabetes pharmacotherapies published in select medical journals were included. Studies were included in this review if they had a sample size of at least 100 participants and all participants were adults with type 2 diabetes. Industry-funded trials must have recruited participants from at least two countries. Government-funded trials were not held to the same standard because they are typically conducted in a single country. Data including the numbers and proportions of participants by ethnicity and race were extracted from trial reports. The participation-to-prevalence ratio (PPR) was calculated for each trial by dividing the percentage of white and racialised participants in each trial by the percentage of white and racialised participants with type 2 diabetes, respectively, for the regions of recruitment. A random-effects meta-analysis was used to generate the pooled PPRs and 95% CIs across study types. A PPR <0.80 indicates under-representation and a PPR >1.20 indicates over-representation. Risk of bias assessments were not conducted for this study as the objective was to examine recruitment of racialised and white participants rather than evaluate the trustworthiness of clinical trial outcomes. RESULTS: A total of 83 trials were included, involving 283,122 participants, of which 15 were government-funded and 68 were industry-funded trials. In government-funded trials, the PPR for white participants was 1.11 (95% CI 0.99, 1.24) and the PPR for racialised participants was 0.72 (95% CI 0.60, 0.86). In industry-funded trials, the PPR for white participants was 1.95 (95% CI 1.74, 2.18) and the PPR for racialised participants was 0.36 (95% CI 0.32, 0.42). The limitations of this study include the reliance on investigator-reported ethnicity and race to classify participants as 'white' or 'racialised', the use of estimates for type 2 diabetes prevalence and demographic data, and the high levels of heterogeneity of pooled estimates. However, despite these limitations, the results were consistent with respect to direction. CONCLUSIONS/INTERPRETATION: Racialised participants are under-represented in government- and industry-funded type 2 diabetes trials. Strategies to improve recruitment and enrolment of racialised participants into RCTs should be developed. REGISTRATION: Open Science Framework registration no. f59mk ( https://osf.io/f59mk ) FUNDING: The authors received no financial support for this research or authorship of the article.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.089 | 0.179 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".