Trends in Canadian Respiratory Clinical Trials from 2001 to 2011
Bibliographic record
Abstract
Clinical research bridges patients' unmet medical need with innovative medicines, increases knowledge acquisition by clinicians, and creates solutions to improve the sustainability and quality of the Canadian health care system and economy. The Canadian Institutes of Health Research and the Canadian Lung Association have recently raised concerns over declining research activities within the Canadian respiratory community. While there are currently >3000 ongoing clinical trials in Canada, the number of trials investigating common respiratory diseases is unknown. The objective of the present study was to monitor the trends in industry- and non-industry-sponsored respiratory clinical trials in Canada from 2001 to 2011. Trialtrove 2012 (Citeline, an Informa UK business), a database containing summarized clinical trial information regarding pharmaceutical products, was searched using common chronic respiratory disease terms: "allergic rhinitis", "asthma", "chronic obstructive pulmonary disease (COPD)", "cystic fibrosis", "respiratory infections", "pulmonary fibrosis" and "smoking cessation". Over the past 10 years, the number of respiratory clinical trials conducted in Canada has increased (4.49 per year; P=0.004). From 2001 to 2011, the majority of trials were performed in asthma, followed closely by respiratory infections and COPD. Over the past decade, the number of trials investigating COPD and respiratory infections increased (P<0.05), while asthma trials showed a declining trend since 2007. Of the clinical trials performed during this 10-year period, the majority were in phase III, with a significant increase in the number of phase II trials (2.49 per year; P=0.008). However, certain trends observed are concerning and warrant further monitoring in the coming years.
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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 | 0.025 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.019 | 0.041 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".