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Please note that you are viewing an archived section from 2019 and some content may be unavailable. To unlock all content for 2019, please visit the archives.

Abstract: TH-PO440

Implications of Different Methods for Calculating Time to Percentage in eGFR Decline Outcomes

Session Information

Category: CKD (Non-Dialysis)

  • 2102 CKD (Non-Dialysis): Clinical, Outcomes, and Trials

Authors

  • Zee, Jarcy, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Liu, Qian, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Larkina, Maria, University of Michigan, Ann Arbor, Michigan, United States
  • Smith, Abigail R., Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Troost, Jonathan P., University of Michigan, Ann Arbor, Michigan, United States
  • Bagnasco, S.M., The Johns Hopkins School of Medicine, Baltimore, Maryland, United States
  • Sampson, Matt G., University of Michigan, Ann Arbor, Michigan, United States
  • Barisoni, Laura, Duke University, Durham, North Carolina, United States
  • Beck, Laurence H., Boston University Medical Center, Boston, Massachusetts, United States
  • Gillespie, Brenda W., University of Michigan, Ann Arbor, Michigan, United States
  • Gipson, Debbie S., University of Michigan Mott Children's Hospital, Ann Arbor, Michigan, United States
  • Mariani, Laura H., University of Michigan, Ann Arbor, Michigan, United States
  • Ju, Wenjun, University of Michigan, Ann Arbor, Michigan, United States
  • Nair, Viji, University of Michigan, Ann Arbor, Michigan, United States
Background

Multiple methods for calculating time to 40% eGFR decline outcomes may differentially characterize kidney disease progression. We compared the traditional “two-point method” (using baseline eGFR to determine the decline threshold and first subsequent eGFR lower than the threshold for the event time) to a “regression method” (fit a regression line to all eGFRs to calculate the threshold and event time), with and without an additional restriction that eGFR<90 at the event time.

Methods

NEPTUNE is a multi-site observational cohort study of patients with glomerular disease. Based on subsets of N=605 patients with available data, we used Cox models to estimate effects of morphologic damage (interstitial fibrosis, tubular atrophy, global sclerosis), urine biomarkers (epidermal growth factor [EGF], urine protein creatinine ratio [UPCR]), serum anti-Phospholipase A2 receptor (PLA2R), and apolipoprotein L1 (APOL1) genotype on time to 40% eGFR decline (or end-stage renal disease) across different methods, adjusted for patient demographic and clinical characteristics.

Results

The regression method and additional restriction of eGFR<90 yielded lower event rates, the latter especially for patients with high eGFR at study enrollment. Effect estimates using the regression method were similar or greater in magnitude (i.e., away from the null) for most predictors [Fig]. Effect estimates with and without the eGFR<90 restriction were similar.

Conclusion

The regression method can facilitate detection of smaller exposure effects. Given a previous study showing increased accuracy of the regression method over the two-point method, we recommend the regression method for calculating time to percent eGFR decline to increase accuracy of effect estimates. The eGFR<90 restriction can capture at least mild loss of kidney function at the event time, which may be needed when hyperfiltration at baseline is a concern.

Funding

  • NIDDK Support