Implementation of Home Infusions in a Multinational Preclinical Alzheimer’s Disease Study
Bibliographic record
Abstract
Abstract Background The A4 Study is a Phase 3 clinical trial investigating solanezumab in preclinical Alzheimer’s disease. The COVID‐19 pandemic impacted the delivery of elective health services worldwide and social distancing restrictions created challenges for clinical trial participants to continue monthly infusions. In an effort to retain A4 participants, decentralized clinical trial methods were implemented, including deployment of mobile research nurses to conduct home visits. Method The A4 Study is a 4.5 year double‐blind trial, followed by an optional 4 year open‐label treatment period. The study launched in 2014 and 1163 males and females between the ages of 65 and 85 years old have been dosed. Home visits were not originally included in the study protocol, but were implemented in 2020 to mitigate the COVID‐19 pandemic impact on study conduct. PCM Trials offered home visits as an option to allow participants to continue to receive investigational product. Mobile research nurses traveled to participant homes and administered the 30‐ to 60‐minute intravenous infusions every 4 weeks. Result To date, more than 1,400 home infusions visits have been conducted in the A4 Study. 124 participants were enrolled in home infusions (99 in the United States; 1 in Canada and 24 in Australia) from 18 sites. Conclusion Implementation of home visits led to several positive outcomes, including reduced participant burden (particularly for participants living in rural/remote locations), study continuity and maintenance of treatment regimen, and retention of participants. Considering the length of the study, the infusion frequency, and the age of the participants, home visits have been a valuable option to help study completion and compliance. Data integrity and participant safety were ensured and maintained with the use of home visits in the A4 study.
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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 | 0.032 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".