Trends in the content and format of main and optional consent forms in oncology clinical trials.
Bibliographic record
Abstract
153 Background: Informed consent forms (ICFs) should provide prospective subjects with an opportunity to balance the risks and benefits of study participation. However, there are growing concerns about the quality of ICFs. Optional ICFs are also increasingly used as the number of companion studies and biomarker evaluations requiring additional tests become more frequent. We examined trends in the content and format of main and optional ICFs. Methods: ICFs from clinical trials at a tertiary cancer center in British Columbia from 2000 to 2015 were reviewed. We focused on breast or gastrointestinal (GI) cancer studies. Readability was evaluated with the Flesch Reading Ease Score (FRES) and Flesch Kincaid Grade Level (FKGL) where a higher FRES (maximum 100) and a lower FKGL (maximum 12) indicated easier readability. We applied t-tests and linear regressions to examine variations among clinical trials and changes over time. Results: We identified 133 main ICFs of which 70% had optional ICFs and where 57% and 43% were breast and GI cancer studies. Phase III trials (44%), industry funded investigations (70%), and studies involving palliative therapies (72%) were most common. Trials from recent years were more likely to have optional ICFs than those from earlier years (p < 0.001). The median length and median word count in main and optional ICFs were 16 and 6 pages and 6183 and 1862 words, respectively. These changed significantly over time whereby main ICFs increased approximately by 1 page and 364 words per year over the 15 year period (p < 0.001). Industry funded trials also had longer ICFs (p = 0.006). Study methods, risks, and confidentiality occupied 29%, 20%, and 11% of the content on ICFs, respectively. Sections pertaining to eligibility (p < 0.001) and screening procedures (p = 0.007) also increased with time, particularly for industry funded studies (p = 0.006). In terms of readability, optional ICFs were generally more difficult to read than main ICFs (FRES 48.3 vs 50.0, p = 0.024; FKGL 11.8 vs 11.1, p < 0.001), especially in recent years (p < 0.001). Conclusions: This is one of the first analyses to include optional ICFs. Length of ICFs is increasing and readability is discordant with the average reading level of potential trial participants.
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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 | 0.403 | 0.812 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.021 | 0.024 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier 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".