PP207 Topic: AS19–Other: Ethics/Endocrine/Metabolism/Burns/Genetics/Rheumatology/Other: TIMELINES AND CHALLENGES GETTING MULTI-CENTRE RESEARCH UP AND RUNNING: EXPERIENCE FROM THE SQUEEZE TRIAL
Bibliographic record
Abstract
Aims & Objectives: Many steps need to occur before a research study can begin. Key milestones include obtaining grant funding, Research Ethics Board (REB) approvals, institutional contracts, and study launch date. These important milestones take time to achieve, and sometimes lead to significant delays launching a study. We sought to describe our real-world experience and timelines obtaining REB approvals and contracts for the SQUEEZE Trial. Methods: The multicentre phase of the SQUEEZE Trial [NCT03080038] began enrolling participants in 2017. REB approval and research contract time (in days) were calculated for each site based on first submission and final approval dates. Overall launch time for each site was calculated by taking the earliest of the REB and contract submission dates and the date of study initiation. Descriptive statistics were used to calculate the mean (sd) time to obtain REB approval, contract, and time to site launch. REB approval was not required for this ‘timelines’ study. Results: Nine Canadian sites enrolled participants in the SQUEEZE trial. REB approval time ranged from 2-319 days with a mean of 107.0 days (SD=95.72). Contract time ranged from 20-343 days with a mean of 178.0 days (SD=93.2). Overall trial launch time ranged from 154-550 days with a mean of 267.7 days (SD=133.5). Conclusions: The time required to obtain site REB approvals and contracts for pediatric clinical trials can be quite lengthy. Timelines were faster for sites that used a centralized REB. The Canadian Tri-Council Policy Statement guidelines are interpreted and applied differently by REBs across Canada, which contributed to the delays experienced. Keywords: Contracts, Research, pediatrics, ethics, clinical trials
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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 | 0.027 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.186 | 0.047 |
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".