Change in Albuminuria and GFR Slope as Joint Surrogate End Points for Kidney Failure: Implications for Phase 2 Clinical Trials in CKD

Abstract

Significance Statement Changes in albuminuria and GFR slope are individually used as surrogate end points in clinical trials of CKD progression, and studies have demonstrated that each is associated with treatment effects on clinical end points. In this study, the authors sought to develop a conceptual framework that combines both surrogate end points to better predict treatment effects on clinical end points in Phase 2 trials. The results demonstrate that information from the combined treatment effects on albuminuria and GFR slope improves the prediction of treatment effects on the clinical end point for Phase 2 trials with sample sizes between 100 and 200 patients and duration of follow-up ranging from 1 to 2 years. These findings may help inform design of clinical trials for interventions aimed at slowing CKD progression. Background Changes in log urinary albumin-to-creatinine ratio (UACR) and GFR slope are individually used as surrogate end points in clinical trials of CKD progression. Whether combining these surrogate end points might strengthen inferences about clinical benefit is unknown. Methods Using Bayesian meta-regressions across 41 randomized trials of CKD progression, we characterized the combined relationship between the treatment effects on the clinical end point (sustained doubling of serum creatinine, GFR <15 ml/min per 1.73 m2, or kidney failure) and treatment effects on UACR change and chronic GFR slope after 3 months. We applied the results to the design of Phase 2 trials on the basis of UACR change and chronic GFR slope in combination. Results Treatment effects on the clinical end point were strongly associated with the combination of treatment effects on UACR change and chronic slope. The posterior median meta-regression coefficients for treatment effects were −0.41 (95% Bayesian Credible Interval, −0.64 to −0.17) per 1 ml/min per 1.73 m2 per year for the treatment effect on GFR slope and −0.06 (95% Bayesian Credible Interval, −0.90 to 0.77) for the treatment effect on UACR change. The predicted probability of clinical benefit when considering both surrogates was determined primarily by estimated treatment effects on UACR when sample size was small (approximately 60 patients per treatment arm) and follow-up brief (approximately 1 year), with the importance of GFR slope increasing for larger sample sizes and longer follow-up. Conclusions In Phase 2 trials of CKD with sample sizes of 100–200 patients per arm and follow-up between 1 and 2 years, combining information from treatment effects on UACR change and GFR slope improved the prediction of treatment effects on clinical end points.