A Phase 2b, multicenter, randomized, double-blind, placebo-controlled study to evaluate the efficacy and safety of intravenous prasinezumab in early-stage Parkinson's disease (PADOVA): Rationale, design, and baseline data
Bibliographic record
Abstract
INTRODUCTION: Prasinezumab was shown to potentially delay motor progression in individuals with early-stage Parkinson's disease (PD) who were either treatment-naïve or on monoamine oxidase type B inhibitor (MAO-Bi) therapy in the PASADENA study. We report the rationale, design, and baseline patient characteristics of the PADOVA study, designed to evaluate prasinezumab in an early-stage PD population receiving standard-of-care (SOC) symptomatic medications. METHODS: PADOVA (NCT04777331) is a Phase 2b, multicenter, randomized, double-blind, placebo-controlled, parallel-group study, in which individuals with early-stage PD on SOC stable symptomatic monotherapy (levodopa or MAO-Bi) receive intravenous prasinezumab 1500 mg every 4 weeks. The primary endpoint is time to confirmed motor progression, defined as ≥5 points increase from baseline on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III in practically defined OFF-medication state. RESULTS: 586 participants were enrolled between May 5th, 2021 and March 22nd, 2023. At baseline, 74.2 % and 25.8 % of participants were receiving levodopa and MAO-Bi, respectively. Mean age was 64.2 years and 63.5 % were male. Mean time from diagnosis was 18.6 months, 85 % of participants were in Hoehn & Yahr (H&Y) Stage 2, and mean MDS-UPDRS Part III score was 24.5. Compared with the PASADENA population, PADOVA participants were older (∼5 years), with longer disease duration (∼8 months), and slightly more advanced based on H&Y stage (10 % more in Stage 2) and MDS-UPDRS Part III (∼3 points more). CONCLUSIONS: PADOVA has successfully recruited an early-stage PD population to test the effect of prasinezumab when added to background SOC.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".