Representativeness of Randomized Control Trials in Kidney Transplantation
Bibliographic record
Abstract
Background: Differences between participants in randomized controlled trials (RCTs) and the target patient population may impact the intervention effect of trial findings in clinical practice. The purpose of this study was to determine the extent to which participants in clinical trials were similar to transplant recipients who underwent transplantation in the U.S. at the time of clinical trial enrolment. Methods: We undertook a systematic search of PubMed, Embase and ClinicalTrials. gov for RCTs completed between 1990 to 2020 that included adults ≥ 18 years of age in kidney transplant recipients. Trials were included if at least one U.S. center participated and ≥ 100 participants were randomized. For each trial, the inclusion and exclusion criteria were extracted and applied to the scientific registry of transplant recipients (SRTR) to identify patients undergoing transplantation during the trial enrollment period. Demographics of interest included participant age, the proportion of women, and the proportion of patients from race and ethnic minority groups. Results: Our search identified 5206 records, 43 trials met the study inclusion criteria. Participants characteristics included age, sex, race/ethnicity, cause of kidney failure, donor source, and comorbid conditions. From the trials, a total of 13591 participants enrolled. 74% enrolled patients only in the U.S., and 52% were multicenter studies. After searching each trial's inclusion and exclusion criteria during the trial enrollment period, 1,011,861 transplant recipients were identified in the SRTR who were potentially eligible for trial participation. Trial participants were younger, more likely to be White, and less likely to be Black or Asian (table 1). Demographic differences between trial participants and transplant eligible transplant recipients in the U.S. persisted in more recent trials. Conclusions: We conclude that women and non-White patients are under-represented in kidney transplant trials. These differences may limit the applicability of trial findings to the real-world setting. Efforts to improve the representativeness of transplant trials are needed. - Trial participants Mean (SD) Contemporary trial Mean (SD) P value Age (years) 47.7 (± 3.0) 49.1 (± 1.8) 0.02 Women (%) 35.7 (± 6.3) 39.0 (± 1.8) <0.01 Race (%) White 66.7 (± 18.5) 53.6 (± 3.4) <0.01 Black 20.7 (± 12.9) 26.0 (± 1.0) <0.01 Asian 5.0 (± 4.2) 5.1 (± 1.1) 0.06 Hispanic ethnicity (%) 15.0 (± 11.9) 13.6 (± 2.0) 0.6
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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 | 0.641 | 0.840 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".