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Publication Information
Affiliation
Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
Division of Nephrology, Tufts Medical Center, Boston, MA, USA
Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
Tufts Clinical and Translational Science Institute, Tufts University, Boston, MA, USA
Division of Biostatistics, Department of Population Health Sciences, University of Utah Health, Salt Lake City, UT, USA
Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA.
Division of Biostatistics and Bioinformatics, University of California San Diego, La Jolla, CA, USA
Division of Nephrology, Columbia University Medical Center and the New York Presbyterian Hospital, New York, NY USA
Department of Medicine, University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong
Denver Health, Denver, CO, USA
Division of Nephrology and Hypertension and Department of Medicine, Mayo Clinic Rochester, MN, USA
Division of Nephrology, RWTH Aachen University, Aachen, Germany
Nakayamadera Imai Clinic, Takarazuka, Japan
Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore
Division of Nephrology, Vanderbilt University, Nashville, TN, USA
Division of Nephrology, Prince of Wales Hospital, Chinese University of Hong Kong, Shatin, Hong Kong
Department of Nephrology, Alessandro Manzoni Hospital ( past Director), ASST Lecco, Italy
Department of Nephrology, AZ Delta, Roeselare, Belgium
Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy
Nephrology Department, Hospital Universitario 12 de Octubre, Madrid, Spain
Renal, Dialysis and Transplant Unit, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
Authors
Appel GB, Chan T, Collier WH, Estacio RO, Fervenza F, Floege J, Greene T, Haaland B, Heerspink HJL, Imai E, Inker LA, Jafar TH, Kam-Tao Li P, Lewis JB, Locatelli F, Luo J, Maes BD, Perna A, Perrone RD, Praga M, Schena FP, Tighiouart H, Wanner C, Xie D
Studies
Abstract
Background: Change in urinary albumin to creatinine ratio (UACR) and GFR slope are individually used as surrogate endpoints in clinical trials of CKD progression. We develop a strategy that combined both surrogate endpoints to improve prediction of drug effects on clinical outcomes.
Methods: We used data from 43 randomized controlled trials of CKD progression, and fitted trial-level Bayesian meta-regression models to characterize the joint relationship between the treatment effects on the clinical endpoint (sustained doubling of serum creatinine, GFR < 15 ml/min per 1.73m2, or kidney failure with replacement therapy) and treatment effects on UACR change and chronic GFR slope. We subsequently applied the results of the meta-regression to the design of a new phase 2 trial to assess design implications, including sample size and follow-up time, for using UACR change and GFR slope individually or in combination.
Results: The relationship between the joint treatment effects on UACR change and GFR slope with treatment effects on the clinical endpoint showed a posterior median intercept of -0.028 (2.5th to 97.5th percentile [P] -0.192 to 0.127). The posterior median meta-regression coefficients were -0.429 (2.5th-97.5th P -0.660 to -0.192) for the treatment effect on the GFR slope and -0.113 (2.5th-97.5th P -0.839 to 0.631) for the treatment effect on log UACR. The median R2 of the model was 0.894. The predicted probability of both surrogates on the clinical endpoint was almost exclusively determined by estimated treatment effects on UACR when the sample size was small (~60 patients per treatment arm) and the follow-up short (~1 year), with the importance of GFR slope increasing when the sample size and follow-up time increased. At large sample sizes (>600 per group) or long follow-up (? 2 year), clinical benefit was solely determined by GFR slope.
Conclusion: In phase 2 clinical trials of CKD progression with sample sizes between 100 to 200 patients per group or follow-up times ranging between 1 and 2 years combining the information from treatment effects on UACR change and GFR slope improved prediction of treatment effects on clinical endpoints.