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Abstract: PO2323

Non-GFR Determinants of Serum Creatinine and Race in GFR Estimating Equations: Findings from the CRIC Study

Session Information

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Hsu, Chi-yuan, University of California San Francisco, San Francisco, California, United States
  • Yang, Wei, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Parikh, Rishi V., Kaiser Permanente Northern California, Oakland, California, United States
  • Anderson, Amanda Hyre, Tulane University, New Orleans, Louisiana, United States
  • Chen, Teresa K., Johns Hopkins University, Baltimore, Maryland, United States
  • Cohen, Debbie L., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • He, Jiang, Tulane University, New Orleans, Louisiana, United States
  • Mohanty, Madhumita J., Wayne State University, Detroit, Michigan, United States
  • Lash, James P., University of Illinois at Chicago, Chicago, Illinois, United States
  • Mills, Katherine T., Tulane University, New Orleans, Louisiana, United States
  • Muiru, Anthony N., University of California San Francisco, San Francisco, California, United States
  • Parsa, Afshin, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States
  • Saunders, Milda Renne, University of Chicago Department of Medicine, Chicago, Illinois, United States
  • Shafi, Tariq, The University of Mississippi Medical Center, Jackson, Mississippi, United States
  • Townsend, Raymond R., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Waikar, Sushrut S., Boston University School of Medicine, Boston, Massachusetts, United States
  • Wang, Jianqiao, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Wolf, Myles, Duke University School of Medicine, Durham, North Carolina, United States
  • Tan, Thida C., Kaiser Permanente Northern California, Oakland, California, United States
  • Feldman, Harold I., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Go, Alan S., Kaiser Permanente Northern California, Oakland, California, United States

Group or Team Name

  • CRIC
Background

Understanding and controlling for the non-GFR determinants of serum creatinine (SCr) that correlate with race may facilitate development of GFR estimating equations without a race term.

Methods

This is a cross-sectional study of 1248 Chronic Renal Insufficiency Cohort (CRIC) participants who underwent urinary 125I-iothalamate clearance GFR (iGFR) and 24-hour urine creatinine clearance measurement at study entry. We first evaluated if Black (vs. non-Black) race was independently associated with different components of creatinine production, secretion and excretion that may contribute to variations in SCr independent of measured GFR (i.e. non-GFR determinants of SCr). We then assessed whether any of these potential explanatory variables could independently or jointly replace the term for Black race in GFR estimating equations using SCr.

Results

Mean±SD age of the study population was 55.9±12.1 yrs; iGFR 48±20 ml/min/1.73m2; median [IQR] SCr 1.5 [1.3-2.0] mg/dL; 43% were female and 37% self-identified as Black.

Black race was associated with greater height, weight, BMI, BSA, bioelectrical impedance analysis (BIA)-phase angle and fat-free mass, and 24-hour urine creatinine excretion. Black race was not associated with higher dietary protein intake (assessed by either self-report or 24-hour urine urea nitrogen) or less tubular secretion of creatinine (quantified as difference between creatinine clearance and iGFR).

In a model regressing iGFR on SCr, age, sex, and race (Black vs. non-Black), there were modest attenuations for the race terms when factors were considered individually (Table). A multivariable model maximized attenuation, but there remained a 8.7% higher iGFR in Black participants (vs. 12.8% in base model)(Table).

Conclusion

Modeling non-GFR determinants of SCr, which varied by race, did not eliminate the incremental value of including race in SCr-based GFR estimating equations.

Association between Black race and iGFR after controlled for non-GFR determinants of serum creatinine which vary by self-report Black race
  Self reported Black race (vs. non-Black race)
  % Higher iGFR (95% CI)
Base Model:
ln(iGFR) = [Race or African ancestry] + ln(SCr) + Age + Sex		 12.8 (9.7 -15.9) %
Base model with potential explanatory variables considered individually:

ln(iGFR) =
[Race or African ancestry]
+ ln(SCr) + Age + Sex +		Body mass index13.8 (10.7-17.0) %
Body surface area13.1 (9.9-16.3) %
Height12.0 (9.0-15.1) %
Weight13.4 (10.3-6.6) %
ln(BIA phase angle)10.5 (7.5-13.6) %
BIA estimated fat-free mass12.4 (9.2-15.6) %
24-hr urine creatinine10.7 (7.7-13.7) %
Base model with several potential explanatory variables considered simultaneously:
ln(iGFR) = [Race or African ancestry] + ln(SCr) + Age + Sex + Height + Fat-free mass + ln(BIA phase angle) + 24-hr urine creatinine		8.7 (5.8-11.7) %
 

Funding

  • NIDDK Support