Emulating randomized trials by observational database studies: the RCT-DUPLICATE initiative in COPD and asthma
Bibliographic record
Abstract
Observational studies are increasingly used to provide real-world evidence in regulatory decision-making. The RCT-DUPLICATE initiative conducted observational studies emulating 2 published randomized trials in patients with asthma and 3 in chronic obstructive pulmonary disease (COPD). For each trial, new-user cohorts were constructed from 2 US healthcare claims databases, comparing initiators of the study and comparator drugs, matched on propensity scores. Proportional hazards models were used to compare the treatments on study outcomes. The observational studies involved more subjects than the corresponding trials, with treatment arms well-matched on baseline characteristics. An asthma example involved emulation of the 26-week FDA-mandated D5896 trial. With 6494 asthma patients per arm, the hazard ratio (HR) of a serious asthma-related event with budesonide-formoterol vs budesonide was 1.29 (95% CI, 0.63-2.65) compared with 1.07 (95% CI, 0.70-1.65) in the trial. A COPD example is the emulation of the one-year IMPACT trial. With 4365 COPD patients per arm, the HR of a COPD exacerbation with triple therapy vs dual bronchodilators was 1.08 (95% CI, 1.00-1.17) compared with 0.84 (95% CI, 0.78-0.91) in the trial. We found mainly discordant results between observational analyses and their emulated randomized trials, likely from the forced discontinuation of treatments prior to randomization in the trials, not mimicable in the observational analyses. This article is part of a Special Collection on Pharmacoepidemiology.
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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 | 0.115 | 0.205 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".