Sustained effect of prasinezumab on Parkinson’s disease motor progression in the open-label extension of the PASADENA trial
Bibliographic record
Abstract
Abstract The PASADENA study is an ongoing Phase II, multicenter, randomized, double-blind, placebo-controlled trial evaluating the safety and efficacy of intravenous prasinezumab, administered every 4 weeks, in early-stage Parkinson’s disease (PD). During the double-blind study period, prasinezumab-treated individuals showed less progression of motor signs (Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale [MDS-UPDRS] Part III). We evaluated here whether the effect of prasinezumab on motor progression, assessed as change in MDS-UPDRS Part III in OFF- and ON-state, and MDS-UPDRS Part II scores was sustained over 4 years from the start of the trial. We compared participants enrolled in the PASADENA open-label extension (OLE) to an external comparator arm derived from the Parkinson's Progression Markers Initiative (PPMI) observational study. Both PASADENA delayed- (n = 94) and early-start (n = 177) groups showed a slower decline (less increase in score) on MDS-UPDRS Part III in OFF- (-51% for the delayed-start group and − 65% for the early-start group) and ON-state (-94% for the delayed-start group and − 118% for the early-start group), and on MDS-UPDRS Part II (-48% for the delayed-start group and − 40% for the early-start group), compared with the PPMI external comparator (n = 303). This exploratory analysis, which requires confirmation in future studies, suggests that the effect of prasinezumab in slowing motor progression in PD may be sustained long-term.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".