STAGED-PKD: An Enriched, Seamless, Two-Stage Study for Venglustat Assessment in ADPKD
Bibliographic record
Abstract
Background: Autosomal dominant polycystic kidney disease (ADPKD) occurs due to cyst formation and growth, resulting in increased total kidney volume (TKV) preceding kidney function decline by decades. The natural history of ADPKD complicates testing of new therapies. Venglustat, a glucosylceramide synthase inhibitor, inhibits cyst growth and reduces kidney failure in PKD mouse models. STAGED-PKD determines venglustat safety and efficacy and was designed using enrichment for progression to ESRD and extensive modeling from prior ADPKD trials. Methods: STAGED-PKD is a two-stage (Phase 2/3), international, double-blind, randomized controlled trial in adults with ADPKD with increased TKV (Mayo Imaging Class 1C-1E) and eGFR 45-90 mL/min/1.73 m2. Target enrollment in Stages 1 and 2 is 240 and 320 patients, respectively. Stage 1 randomizes patients 1:1:1 to venglustat dose 1, dose 2 or placebo. Stage 2 randomizes patients 1:1 to placebo or venglustat preferred dose based on Stage 1 safety data. Primary endpoints are TKV growth rate over 18 months in Stage 1 and eGFRCKD-EPI slope over 24 months in Stages 1 and 2 (n=560). Results: Baseline characteristics for Stage 1 are shown (Table; n=225). Mean patient age is 42.7 years; mean eGFRCKD-EPI is 65.5 mL/min/1.73 m2. Overall, 55.1%, 30.7% and 14.2% are of Mayo Imaging Class 1C, 1D and 1E, respectively. Conclusions: STAGED-PKD enables optimal dose selection and evaluation of venglustat safety and impact on TKV growth and eGFR slope in ADPKD. Stage 1 TKV assessment via a nested approach allows early efficacy evaluation, increasing trial design efficiency. Funding: Commercial Support - Sanofi GenzymeStage 1 Baseline Characteristics
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".