Assessing non-white ethnic participation in type 2 diabetes mellitus randomized clinical trials: A Meta-Analysis
Bibliographic record
Abstract
Abstract Importance The prevalence of type 2 diabetes mellitus (T2DM) is increasing globally, and the greatest burden is borne by non-white ethnic groups. Randomized clinical trials (RCTs) provide evidence regarding the optimal medical therapy for the treatment of T2DM patients and inform national and international guidelines. However, there are concerns that the enrollment of ethnically diverse people into these trials is limited, which has resulted in a lack of ethnic diversity in RCTs of T2DM. Furthermore, the extent of underrepresentation may differ according to whether a trial is government-funded or industry-funded. Objective To systematically review and meta-analyze the proportion of non-white and white participants relative to their disease burden of T2DM included in large, influential government- and industry-funded RCTs of T2DM pharmacotherapies. Data Sources The PubMed electronic database was searched from January 2000 through January 2021. Study Selection Reports of RCTs of T2DM medications with a total sample size of at least 100 participants published in the year 2000 onwards, in high impact general medical journals (i.e., impact factor >10), were included. Data Extraction and Synthesis Data including the number of participants, proportion of participants by ethnicity, and funding sources, were extracted from trial reports. Main Outcomes and Measures The main outcome was the participation-to-prevalence ratio (PPR), which was calculated for each trial by dividing the percentage of white and non-white participants in the trial by the percentage of white and non-white participants with T2DM for the countries or regions of recruitment represented in each trial. A random-effects meta-analysis was used to generate the pooled PPR and 95% confidence intervals (CI) across study types. A PPR <0.80 indicates underrepresentation and >1.20 indicates overrepresentation. Results A total of 82 trials were included involving 296,964 participants: 14 were government-funded trials, and 68 were industry-funded trials. For government trials, the PPR for white participants was 1.11 (95% CI; 1.00-1.23) and for non-white participants was 0.73 (95% CI:0.62-0.86). Among industry trials, the PPR for white participants was 2.19 (95%CI: 1.91-2.50), and the PPR for non-white participants was 0.33 (95%CI: 0.29-0.38). Heterogeneity was high across all PPRs. Conclusions and Relevance Non-white participants are underrepresented in both government- and industry-funded T2DM trials, compared to white participants. The greatest disparity in ethnic diversity in RCTs is observed for industry-funded trials. Key Points Question What is the representation of non-white participants in type 2 diabetes randomized clinical trials relative to their disease burden? Findings In this meta-analysis, non-white participants are underrepresented in both government-and industry-funded type 2 diabetes randomized trials, compared to white participants. The greatest disparity in ethnic diversity in randomized trials was observed for those funded by industry. Meaning Deliberate strategies to improve recruitment and enrolment of diverse participants proportional to the type 2 diabetes disease burden into industry and government-funded randomized controlled trials are needed to enhance the generalizability of research findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.364 | 0.791 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.010 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".