A meta-research study revealed several challenges in obtaining placebos for investigator-initiated drug trials
Bibliographic record
Abstract
OBJECTIVES: To systematically assess the kind of placebos used in investigator-initiated randomized controlled trials (RCTs), from where they are obtained, and the hurdles that exist in obtaining them. STUDY DESIGN AND SETTING: PubMed was searched for recently published noncommercial, placebo-controlled randomized drug trials. Corresponding authors were invited to participate in an online survey. RESULTS: From 423 eligible articles, 109 (26%) corresponding authors (partially) participated. Twenty-one of 102 (21%) authors reported that the placebos used were not matching (correctly labeled in only one publication). The main sources in obtaining placebos were hospital pharmacies (32 of 107; 30%) and the manufacturer of the study drug (28 of 107; 26%). RCTs with a hypothesis in the interest of the manufacturer of the study drug were more likely to have obtained placebos from the drug manufacturer (18 of 49; 37% vs. 5 of 29; 17%). Median costs for placebos and packaging were US$ 58,286 (IQR US$ 2,428- US$ 160,770; n = 24), accounting for a median of 10.3% of the overall trial budget. CONCLUSION: Although using matching placebos is widely accepted as a basic practice in RCTs, there seems to be no standard source to acquire them. Obtaining placebos requires substantial resources, and using nonmatching placebos is common.
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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 | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | 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 | 0.514 | 0.679 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.024 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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, 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".