An official website of the United States government
Publication Information
Affiliation
Population Health Sciences, University of Utah School of Medicine, UT, USA
Division of Nephrology, Tufts Medical Center, Boston, MA USA
Division of Nephrology, Columbia University Medical Center and the New York Presbyterian Hospital, New York, NY, USA
Renal and Metabolic Division, the George Institute for Global Health, NSW, Australia
Instituto de Investigación Hospital 12 de octubre (i+12), Madrid, Spain
The George Institute for Global Health, University of New South Wales, Sydney, Australia
Division of Nephrology, RWTH Aachen University, Aachen, Germany
Department of Nephrology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
Medical Research Council Population Health Research Unit at the University of Oxford, Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Oxford, UK
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
Renal, Dialysis and Transplant Unit, Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy
Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
Division of Nephrology, University Hospital of Würzburg, Würzburg, Germany
Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, China
Authors
Appel GB, Badve S, Caravaca-Fontán F, Chalmers J, Collier W, Floege J, Goicoechea M, Greene T, Haaland B, Haynes R, Imai E, Inker LA, Jafar TH, Lewis JB, Li PKT, Locatelli F, Maes B, Neuen BL, Perrone RD, Remuzzi G, Schena FP, Toto RD, Wanner C, Xie D
Abstract
Background and objectives:
The slope of the glomerular filtration rate (GFR) has been evaluated as a surrogate endpoint for predicting treatment effects on kidney failure endpoints across a broad collection of randomized controlled trials (RCTs) for chronic kidney disease (CKD). We hypothesized that measures of disease severity may modify the predictive performance of GFR slope.
Design, setting, participants, and measurements:
We conducted meta-regression analyses of 66 CKD RCTs to assess relationships between treatment effects on the clinical endpoint (CE) (doubling of serum creatinine, GFR < 15 mL/min per 1.73 m2 or kidney failure) and treatment effects on chronic or 3-year total GFR slopes. We fit Bayesian hierarchical models with interaction terms to determine if three measures of severity (baseline GFR, baseline albumin to creatinine ratio (ACR), or the control arm GFR slope) modify relationships between treatment effects on GFR slope and that of the CE. We defined strong evidence as 95% credible intervals (CrIs) for the interaction terms excluding zero.
Results:
There was no evidence for effect modification in analyses involving the total slope. For the chronic slope, there was strong evidence for effect modification using any of the three severity variables (GFR (95% CrI: -0.16, -0.003), ACR (95% CrI: 0.05, 0.21) and control arm slope (95% CrI: -0.18, -0.03). Using the chronic as opposed to total slope resulted in substantially greater variation in predicted hazard ratios for treatment effects on CE by changes in disease severity.
Conclusions:
Across levels of disease severity, our data indicated a stable relationship between treatment effects on the total slope and the clinical endpoint. On the other hand, our analyses indicated the severity of CKD in the patient population explains differences in predicted treatment effects on CE from the chronic slope.