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Abstract: PO1578

STAGED-PKD: Patient Enrichment and Modeling-Driven Efficient ADPKD Trial Design

Session Information

Category: Genetic Diseases of the Kidneys

  • 1001 Genetic Diseases of the Kidneys: Cystic

Authors

  • Perrone, Ronald D., Division of Nephrology, Tufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts, United States
  • Hariri, Ali, Sanofi Genzyme, Cambridge, Massachusetts, United States
  • Minini, Pascal, Sanofi, Chilly Mazarin, France
  • Chapman, Arlene B., Department of Medicine, University of Chicago, Chicago, Illinois, United States
  • Horie, Shigeo, Department of Urology, Juntendo University Graduate School of Medicine, Tokyo, Japan
  • Knebelmann, Bertrand, Université Paris-Descartes, Faculté de Médecine, AP-HP, Service de Néphrologie, Hôpital Necker-Enfants Malades, Paris, France
  • Mrug, Michal, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
  • Ong, Albert C., Department of Infection Immunity & Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
  • Pei, York P., Division of Nephrology, University of Toronto, Toronto, Ontario, Canada
  • Torres, Vicente E., Mayo Translational Polycystic Kidney Disease Center, Mayo Clinic, Rochester, Minnesota, United States
  • Modur, Vijay, Sanofi Genzyme, Cambridge, Massachusetts, United States
  • Gansevoort, Ron T., Department of Nephrology, University Medical Center Groningen, Groningen, Netherlands
Background

Total kidney volume (TKV) and eGFR slope are key endpoints in autosomal dominant polycystic kidney disease (ADPKD) trials, indicative of cyst growth and kidney function decline. To date, unequivocal demonstration of drug effect on these endpoints required two trials. STAGED-PKD assesses the effect of glucosylceramide synthase inhibition with venglustat on both endpoints in one efficient, short-duration trial.

Methods

Retrospective analysis of TKV and eGFR slope data from CRISP (3-yr) and HALT-A combined identified rapidly progressing patients for enrichment. A statistical relationship between TKV growth vs eGFR slope was derived by modeling. Meta-analysis was conducted of randomized clinical trials assessing treatment impact on both TKV and eGFR. These analyses enabled study powering for both endpoints. Comparison of design efficiency was performed vs prior trials.

Results

Retrospective analysis of CRISP and HALT-A confirmed a significant correlation between TKV growth and eGFR slope (correlation 0.346, p<0.0001; Figure). Different statistical approaches showed that in rapidly progressing ADPKD patients, 50% reduction in TKV growth is associated with a ~30% reduction in eGFR slope. Thus, STAGED-PKD is powered to detect 50% reduction in TKV growth and 30% reduction in eGFR slope. STAGED-PKD is highly efficient vs HALT-A and -B, TEMPO 3:4, and REPRISE.

Conclusion

Modeling allowed the design and powering of a two-stage study to assess venglustat impact on TKV growth and eGFR slope. STAGED-PKD improves study efficiency via modeling and patient enrichment to reduce patient number and trial duration.

Modeling of the Relationship Between TKV Growth Rate and eGFR Decline

Funding

  • Commercial Support