Sponsor/research ethics boards (REB) communications about informed consent (IC) and time to local activation (LA): An NCIC CTG pilot study.
Bibliographic record
Abstract
6131 Background: Communications between sponsors, investigators and REBs about IC details may affect a centre’s LA time. We evaluated factors associated with these communications and LA times for a series of NCIC CTG trials. Methods: A sample of NCIC CTG sponsored phase III trials (P3T) was selected based on mandatory compliance with regulatory requirements and NCIC CTG central ethics review (initiated in 2003). Two independent and trained reviewers systematically extracted data. We assessed LA times, number of IC communications between NCIC CTG and centre/REB, and IC elements leading to communication. Results: Between Apr 2003-Dec 2008, 63 P3Ts were activated by NCIC CTG; 16 (25.4%) were selected for inclusion, including 15 requiring Health Canada (HC) approval. A mean of 4.5 trials/centre (TC) were activated among 15 centres (range 1-10), resulting in 72 data sets. Median LA time was 11.3 mos with variation by centre (interquartile range [IR] = 0.66–21.78 mos) and trial (IR= 0.36–21.62 mos) and was 19.2 mos in 2003-05 and 10.1 mos in 2006-08 (p=0.006). Median LA times were 11.9, 9.2, 12.1, 14.6 and 21.5 mos for number of communications = 1, 2, 3, 4 and 5 (p-trend = 0.007). The number of IC elements requiring communication per TC trended towards longer LA time (0.3 mo/additional element; p=0.06). The top 5 IC elements leading to at least one communication per TC were: tissue banking language (39), confidentiality terms (25), risk frequency categorization (24), description of trial details (18), and risks to the subject (13); 3 of these are HC regulatory requirements. An exploratory analysis assessing all 65 elements found only communication about “subject responsibilities” (e.g., questionnaires) to be associated with longer LA time (7.5 mos; p=0.04 [corrected for multiple comparisons]). Conclusions: For NCIC CTG trials, LA times are longer than desired, may have reduced over time and are associated with more frequent communications between NCIC CTG and REB and possibly with more IC elements needing review. Systematic evaluations may assist in identifying elements associated with sponsor/REB interactions. Processes to standardize consent language may help reduce LA times.
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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 | 0.091 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".