A randomized, double‐blind, placebo‐controlled, delayed start study to assess rasagiline as a disease modifying therapy in Parkinson's disease (the ADAGIO study): Rationale, design, and baseline characteristics
Bibliographic record
Abstract
A neuroprotective therapy is the single most important unmet medical need in Parkinson's disease. Several promising agents in the laboratory have been tested in the clinic, but none has been established in clinical trials to have a disease modifying effect despite positive results because of potential confounding symptomatic or pharmacologic effects. The delayed start design was developed to try to avoid a symptomatic confound when testing a putative neuroprotective therapy. In this study design, patients are randomly assigned to study drug or placebo in the first phase of the study, and both groups receive the active drug in the second phase. If benefits seen at the end of phase I persist through the end of phase II, they cannot be readily explained by a symptomatic effect (as patients in both groups are receiving the same medication) and benefits in the early start group must relate to the early initiation of the treatment. Although the precise mechanism responsible for such an effect can be debated, positive results in a delayed start study indicate that patients who receive early treatment have a better outcome than those where the treatment is delayed. We are using the delayed start design to assess the potential disease modifying effects of rasagiline in a prospective double blind controlled trial (the ADAGIO study). We here describe the rationale for the study and baseline characteristics of the 1,176 patients who have been enrolled into the trial.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".