Adaptive designs in clinical trials: a systematic review-part I
Bibliographic record
Abstract
Abstract Background: Adaptive designs (ADs) are intended to make clinical trials more flexible, offering efficient and potentially cost-saving benefits. Despite a large number of methods-based research papers in the literature on different adaptations to trials, the advantages and limitations of such designs remain unfamiliar to large parts of the clinical community including those in pediatric medicine where efficient clinical trials are essential to inform care. This systematic review provides an overview of the use of ADs in published clinical trials (Part I) and compares the application of AD in trials in adult and pediatric studies, providing real-world examples and recommendations for the child health community (Part II). Methods: Published studies from 2010 to April 2020 were searched in the following databases: MEDLINE (Ovid), Embase (Ovid), and International Pharmaceutical Abstracts (Ovid). Protocols, reports, and a secondary analysis using AD were included. We did not include any trial registrations and interventions other than drugs or vaccines. Data from the published literature on study characteristics, types of adaptations, statistical analysis, stopping boundaries, logistical challenges, operational considerations and ethical considerations were extracted and summarized herein. Results : Out of 23,886 retrieved studies, 317 publications of adaptive trials, 267 (84.2%) trial reports, and 50 (15.8%) study protocols), were included. Most trials included only adult participants (265, 83.9%), 16 trials (5.4%) were limited to only children and 28 (8.9%) were for both children and adults. Dose finding designs were used in the highest proportion of the included AD (82, 22.4 %), followed by adaptive randomization (56, 14.4%), group sequential design in 47 trials (12.8%), then drop-the-losers (pick-the-winner) design in 28 trials (7.6%) and seamless phase 2-3 design in 27 trials (7.4%). Approximately 203 (64%) studies used frequentist statistical methods and 75 (23.7%) used Bayesian methods. Conclusion: In Part I of this review, we provide a comprehensive overview of the landscape and methodological features of adaptive clinical trials. We found that adaptive designs were applied mostly in Phase II oncology trials, aimed to establish efficacy and determine the choice of doses for the Phase III of the trials. Phase I trials of new drugs that included adaptations most frequently aimed to identify the maximum tolerable dose. Adaptation details were not uniformly reported across all trials and were hardly reported in the pediatric trials. Study protocol registration: DOI:10.1186/s13063-018-2934-7
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.462 | 0.932 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.012 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".