Gearing up for the future: Exploring facilitators and barriers to inform clinical trial design in frontotemporal lobar degeneration
Bibliographic record
Abstract
Abstract Background Frontotemporal lobar degeneration (FTLD) refers to a group of neurodegenerative conditions, affecting the frontal and/or temporal lobes. Ongoing research has provided insight into developing clinical trials for FTLD and key clinical measures such as structural MRI. To inform clinical trial design and optimize participation, it is imperative to explore facilitators and barriers for potential candidates. Objective The objective of this study is to explore facilitators and barriers to participating in future clinical trials for FTLD. Methods Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) are observational studies focused on characterizing FTLD syndromes in preparation for clinical trials. The 584 participants enrolled across 18 research sites in the United States and Canada completed a survey assessing interest in clinical trial participation. Results 29% of respondents self‐reported as patients (63±10 years), 26% self‐reported as caregivers answering on behalf of patients (65±10 years), and 45% self‐reported as healthy but at risk for FTLD (48±14 years). Travel reimbursement was the most common factor reported to positively influence participation (≧66%), with the healthy but at risk group showing the strongest endorsement (83%). Cost and time involved in travel were possible barriers for about half of the patients (48%) and healthy but at risk respondents (53%). The respondents value receiving feedback on the study findings (≧80%) and being informed of their individual disease progression (≧75%). Particularly, keeping participation confidential was very important for the healthy but at risk group (62%). In regard to research assessments, most participants demonstrated a high interest in physical and neurological exams at a research center (≧87%) whereas only half were interested in doing more invasive procedures such as the lumbar puncture (≧52%). Overall, respondents showed a positive attitude and support for research participation (≧77%) and trusted that their health information would remain confidential in a clinical trial (≧53%). Conclusions Favorable attitudes and interest towards medical research exist among participants. To optimize participation, clinical trials should allocate funding for travel and involve participants in feedback about study results and their disease progression. Alternatives to invasive assessments may increase participation.
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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 | 0.590 | 0.631 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".