Feasibility of Simon Two‐Stage Futility Trials in People with Early, Symptomatically Treated Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Disease-modifying treatments are a critical unmet need in Parkinson's disease (PD). Phase 2 futility trials using the Simon two-stage design offer an efficient strategy to evaluate candidate treatments in an early PD population. OBJECTIVE: The aim was to assess the feasibility of Simon two-stage futility trials in early, levodopa-treated PD subjects using historical patient-level clinical trial datasets. METHODS: We analyzed patient-level data from two completed trials, that is, STEADY-PD 3 (n = 336, untreated at baseline) and NET-PD LS1 (n = 1741, treated at baseline). We defined disability progression as a ≥5-point worsening on the motor (Part III) subscore of the Unified Parkinson's Disease Rating Scale at 12 and 24 months. We tested multiple scenarios, including the reanalysis of STEADY-PD 3 participant data after starting dopaminergic treatment. We assessed predictors of progression using logistic regression analysis and calculated sample size estimates. RESULTS: Both trials showed similar progression rates at 12 months (~26%) and 24 months (~35%). In NET-PD LS1, older age and lower baseline motor scores were associated with worsening; no predictors were significant in STEADY-PD 3. We estimate that in futility trials that use OFF-state scores to assess motor performance, 39 early PD participants are required to detect significant disability worsening over an observation period of 12 months. CONCLUSIONS: Phase 2 futility trials using the Simon two-stage methodology are feasible in early PD, including in treated and untreated patients. OFF-state scores are preferable to ON-state scores as the primary outcome measure. Futility trials offer a smaller-scale, faster, and cost-effective approach to assessing new candidate treatments in PD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.171 | 0.179 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".