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Abstract: TH-PO1053

The Clinical Implications of Acute and Chronic GFR Slope in Clinical Trials of CKD

Session Information

Category: CKD (Non-Dialysis)

  • 2302 CKD (Non-Dialysis): Clinical, Outcomes, and Trials


  • Greene, Tom, University of Utah Health, Salt Lake City, Utah, United States
  • Inker, Lesley Ann, Tufts Medical Center, Boston, Massachusetts, United States
  • Heerspink, Hiddo Jan L., Universiteit Groningen Afdeling Gezondheidswetenschappen, Groningen, Groningen, Netherlands

Group or Team Name

  • CKD-EPI(CT).

Randomized trials for CKD traditionally use the established clinical endpoint (CE) of kidney failure or doubling of serum creatinine as the primary outcome. These are late events in CKD, thus requiring trials with long follow-up or restriction to patients with rapidly progressive or advanced disease. GFR slope has been proposed to circumvent these limitations, but acute effects often complicate interpretation. We use a multivariable model to resolve ambiguities from acute effects.


Using individual patient data from 66 randomized treatment comparisons (RTCs), we used mixed effects models to estimate treatment effects on the acute (baseline to 3 months) and chronic GFR slopes (after 3 months), and Cox regression to estimate treatment effects on the CE (hazard ratios (HRs)). We used a multivariable Bayesian meta-regression to relate the treatment effects on the CE jointly to the treatment effects on the acute and chronic slopes.


Across the 66 RTCs, the multivariable model showed that optimally weighting the acute and chronic slopes accurately predicted the treatment effects on the CE, with a trial-level R2 (95% Bayesian credible interval) of 0.95 (0.78,1.00). For a fixed treatment effect on the chronic slope, each 1 ml/min/1.73m2 greater acute GFR decline for the treatment vs. the control increased the HR for the CE by 11.3%, in the direction against the treatment. For a fixed acute effect, each 0.75 ml/min/1.73m2/year greater treatment effect on the chronic slope reduced the HR for the CE by 22.8%, in favor of the treatment. The Figure shows the model’s decomposition of the estimated treatment effects on the CE into separate components due to the acute and chronic slopes for each RTC.


Treatment effects on both the acute and chronic slopes are strong, independent determinants of the treatment effect on the CE. Optimal weighting of the acute and chronic slopes accurately predicts treatment effects on the CE.


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