Misghina Weldegiorgis1, Dick de Zeeuw1, Liang Li2, Hans-Henrik Parving3, Fan Fan Hou4, Giuseppe Remuzzi5, Tom Greene6, Hiddo J L Heerspink7. 1. Department of Clinical Pharmacy & Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands. 2. MD Anderson Cancer Center, Houston, TX. 3. Department of Medical Endocrinology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 4. Renal Division, Nanfang Hospital, Southern Medical University, Guangzhou, China. 5. IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Centro Anna Maria Astori, Bergamo, Italy. 6. Unit of Nephrology, Dialysis and Transplantation, A.O. Papa Giovanni XXIII, Bergamo, Italy; University of Utah, Salt Lake City, UT. 7. Department of Clinical Pharmacy & Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands. Electronic address: h.j.lambers.heerspink@umcg.nl.
Abstract
BACKGROUND: In clinical practice and clinical trials, changes in serum creatinine concentrations are used to evaluate changes in kidney function. It has been assumed that these changes follow a linear pattern when serum creatinine concentration is converted to estimated glomerular filtration rate (eGFR). However, the paradigm that kidney function declines linearly over time has been questioned by studies showing either linear or nonlinear patterns. To verify how this impacts on kidney end points in intervention trials, we analyzed eGFR trajectories in multiple clinical trials of patients with and without diabetes. STUDY DESIGN: Longitudinal observational study. SETTING & PARTICIPANTS: 6 clinical trials with repeated measurements of serum creatinine. PREDICTOR: Patient demographic and clinical parameters. OUTCOMES: Probability of nonlinear eGFR function trajectory calculated for each patient from a Bayesian model of individual eGFR trajectories. RESULTS: The median probability of a nonlinear eGFR decline in all trials was 0.26 (interquartile range, 0.13-0.48). The median probability was 0.28 in diabetes versus 0.09 in nondiabetes trials (P<0.01). The percentage of patients with a >50% probability of nonlinear eGFR decline was generally low, ranging from 19.3% to 31.7% in the diabetes trials and from 15.1% to 21.2% in the nondiabetes trials. In the pooled data set, multivariable linear regression showed that higher baseline eGFR, male sex, diabetes status, steeper eGFR slope, and non-renin-angiotensin-aldosterone-system antihypertensives were independently associated with a greater probability of a nonlinear eGFR trajectory. LIMITATIONS: Relatively short follow-up and no measured GFR. CONCLUSIONS: In both diabetes and nondiabetes trials, the majority of patients show a more or less linear eGFR decline. These data support the paradigm that in diabetic and nondiabetic kidney disease, eGFR decline progresses linearly over time during a clinical trial period. However, in diabetes, one should take the nonlinearity proportion into account in the design of a clinical trial.
BACKGROUND: In clinical practice and clinical trials, changes in serum creatinine concentrations are used to evaluate changes in kidney function. It has been assumed that these changes follow a linear pattern when serum creatinine concentration is converted to estimated glomerular filtration rate (eGFR). However, the paradigm that kidney function declines linearly over time has been questioned by studies showing either linear or nonlinear patterns. To verify how this impacts on kidney end points in intervention trials, we analyzed eGFR trajectories in multiple clinical trials of patients with and without diabetes. STUDY DESIGN: Longitudinal observational study. SETTING & PARTICIPANTS: 6 clinical trials with repeated measurements of serum creatinine. PREDICTOR: Patient demographic and clinical parameters. OUTCOMES: Probability of nonlinear eGFR function trajectory calculated for each patient from a Bayesian model of individual eGFR trajectories. RESULTS: The median probability of a nonlinear eGFR decline in all trials was 0.26 (interquartile range, 0.13-0.48). The median probability was 0.28 in diabetes versus 0.09 in nondiabetes trials (P<0.01). The percentage of patients with a >50% probability of nonlinear eGFR decline was generally low, ranging from 19.3% to 31.7% in the diabetes trials and from 15.1% to 21.2% in the nondiabetes trials. In the pooled data set, multivariable linear regression showed that higher baseline eGFR, male sex, diabetes status, steeper eGFR slope, and non-renin-angiotensin-aldosterone-system antihypertensives were independently associated with a greater probability of a nonlinear eGFR trajectory. LIMITATIONS: Relatively short follow-up and no measured GFR. CONCLUSIONS: In both diabetes and nondiabetes trials, the majority of patients show a more or less linear eGFR decline. These data support the paradigm that in diabetic and nondiabetic kidney disease, eGFR decline progresses linearly over time during a clinical trial period. However, in diabetes, one should take the nonlinearity proportion into account in the design of a clinical trial.
Authors: Morgan E Grams; Yingying Sang; Shoshana H Ballew; Kunihiro Matsushita; Brad C Astor; Juan Jesus Carrero; Alex R Chang; Lesley A Inker; Timothy Kenealy; Csaba P Kovesdy; Brian J Lee; Adeera Levin; David Naimark; Michelle J Pena; Jesse D Schold; Varda Shalev; Jack F M Wetzels; Mark Woodward; Ron T Gansevoort; Andrew S Levey; Josef Coresh Journal: J Am Soc Nephrol Date: 2019-07-10 Impact factor: 10.121
Authors: Scott G Frodsham; Zhe Yu; Ann M Lyons; Adhish Agarwal; Melissa H Pezzolesi; Li Dong; Titte R Srinivas; Jian Ying; Tom Greene; Kalani L Raphael; Ken R Smith; Marcus G Pezzolesi Journal: Diabetes Date: 2018-11-13 Impact factor: 9.461
Authors: Jon Viljar Norvik; Laura R Harskamp; Viji Nair; Kerby Shedden; Marit D Solbu; Bjørn O Eriksen; Matthias Kretzler; Ron T Gansevoort; Wenjun Ju; Toralf Melsom Journal: Nephrol Dial Transplant Date: 2021-09-27 Impact factor: 5.992
Authors: Glenn M Chertow; Pablo E Pergola; Fang Chen; Brian J Kirby; John S Sundy; Uptal D Patel Journal: J Am Soc Nephrol Date: 2019-09-10 Impact factor: 10.121
Authors: Robert S Brown; Maryellen R M Sun; Isaac E Stillman; Teresa L Russell; Sylvia E Rosas; Jesse L Wei Journal: Nephrol Dial Transplant Date: 2020-06-01 Impact factor: 7.186