Current globalization of drug interventional clinical trials: characteristics and associated factors, 2011–2013
Bibliographic record
Abstract
Abstracts Background Clinical trial globalization is a major trend for industry-sponsored clinical trials. There has been a shift in clinical trial sites towards emerging regions of Eastern Europe, Latin America, Asia, the Middle East, and Africa. Our study objectives were to evaluate the current characteristics of clinical trials and to find out the associated multiple factors which could explain clinical trial globalization and its implications for clinical trial globalization in 2011–2013. Methods The data elements of “phase,” “recruitment status,” “type of sponsor,” “age groups,” and “design of trial” from 30 countries were extracted from the ClinicalTrials.gov website. Ten continental representative countries including the USA were selected and the design elements were compared to those of the USA. Factors associated with trial site distribution were chosen for a multilinear regression analysis. Results The USA, Germany, France, Canada, and United Kingdom were the “top five” countries which frequently held clinical trials. The design elements from nine continental representative countries were quite different from those of the USA; phase 1 trials were more prevalent in India (OR 1.517, p
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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 | 0.047 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".