Enrollment of Participants From Marginalized Racial and Ethnic Groups
Bibliographic record
Abstract
Background and Objectives Representation of persons from marginalized racial and ethnic groups in Parkinson disease (PD) trials has been low, limiting the generalizability of therapeutic options for individuals with PD. Two large phase 3 randomized clinical trials sponsored by the National Institute of Neurological Disorders and Stroke (NINDS), STEADY-PD III and SURE-PD3, screened participants from overlapping Parkinson Study Group clinical sites under similar eligibility criteria but differed in participation by underrepresented minorities. The goal of this research is to compare recruitment strategies of PD participants belonging to marginalized racial and ethnic groups. Methods A total of 998 participants with identified race and ethnicity consented to STEADY-PD III and SURE-PD3 from 86 clinical sites. Demographics, clinical trial characteristics, and recruitment strategies were compared. NINDS imposed a minority recruitment mandate on STEADY-PD III but not SURE-PD3. Results Ten percent of participants who consented to STEADY-PD III self-identified as belonging to marginalized racial and ethnic groups compared to 6.5% in SURE-PD3 (difference = 3.9%, 95% confidence interval [CI] 0.4%–7.5%, p value = 0.034). This difference persisted after screening (10.1% of patients in STEADY-PD III vs 5.4% in SURE-PD 3, difference = 4.7%, 95% CI 0.6%–8.8%, p value = 0.038). Discussion Although both trials targeted similar participants, STEADY-PD III was able to consent and recruit a higher percentage of patients from racial and ethnic marginalized groups. Possible reasons include differential incentives for achieving minority recruitment goals. Trial Registration Information This study used data from The Safety, Tolerability, and Efficacy Assessment of Isradipine for Parkinson Disease (STEADY-PD III; NCT02168842) and the Study of Urate Elevation in Parkinson’s Disease (SURE-PD3; NCT02642393).
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How this classification was reachedexpand
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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".