Estimating GFR:From Physiology to Public Health

• Tufts: Andy Levey, Lesley (Stevens) Inker, Chris Schmid , Lucy Zhang, Hocine Tighiouart, Aghogho Okparavero, Cassandra Becker, Li Fan

• Hopkins: Josef Coresh, Jane Manzi, Morgan Grams

• Utah/Cleveland Clinic: Tom Greene, Liang Li, Fred Van Lente• UMN: John Eckfeldt, Cathie

Leiendecker Foster• Penn: Harv Feldman, Marshall

Joffe, Dick Landis• NIDDK: Paul Eggers, John Kusek

No conflicts to declareGrant Support:

NIH UO1 DK 053869NIH UO1 DK 067651NIH UO1 DK 035073

National Kidney Foundation

Outline of Presentation

• Current applications

• GFR measurement

• Principles of GFR estimating equations

• Performance of CKD-EPI creatinineand cystatin C equations

• Associations of eGFR with outcomes

• New KDIGO guidelines

• Summary and conclusions

GFR is one of many kidney functions– Excretory (filtration, reabsorption, secretion)– Endocrine (renin, erythropoeitin, vitamin D)– Metabolic (degradation of low molecular weight

proteins and drugs)Serum creatinine as a filtration marker

– Measured 280 millions times per year in US– Estimated GFR reported more than 80% of clinical

laboratories– Substantial impact on clinical practice, research and

public health“Current methods of study of renal function may be too

elaborate for general clinical application, but no method is to be disdained if it can aid significantly in deciding the issue between life and death.” Smith HW. The Kidney: Structure and Function in Health and Disease. Oxford University Press, NY 1951

Applications of GFR Estimations

• Routine estimation for clinical care– Interpreting the symptoms, signs, and

laboratory abnormalities that may indicate kidney disease

– drug dosing

– detecting and managing chronic kidney disease and assessing the prognosis

• GFR <60 ml/min/1.73 m2 for >3 months– diagnostic criterion for CKD

– associated with an increased risk of adverse outcomes, including death

Prognosis of CKD by GFRand Albuminuria

Categories:KDIGO 2012

Albuminuria Categories,Description and Range

A1 A2 A3

normal to mildly increased

moderately increased

severely increased

<30 mg/g

<3 mg/mmol

30-299 mg/g3-29 mg/mmol

>300 mg/g>30 mg/mmol

GFRCategories,Description and Range

(mL/min/1.73 m2)

G1normal or

high >90

G2mildly

decreased 60-89

G3amildly to

moderately decreased

45-59

G3bmoderately to severely decreased

30-44

G4severely

decreased 15-29

G5kidney failure <15

Classification of CKD• Cause (C)• GFR (G)

• Albuminuria (A)KDIGO 2012

Percentage of US Population by eGFR and Albuminuria Category:

KDIGO 2012 and NHANES 1999-2006

Persistent Albuminuria Categories,Description and Range

A1 A2 A3

normal to mildly increased

moderately increased

severely increased

<30 mg/g

<3 mg/mmol

30-299 mg/g3-29 mg/mmol

>300 mg/g>30 mg/mmol

GFRCategories,Description and Range

(mL/min/1.73 m2)

G1normal or

high >90 55.6 1.9 0.4 57.9

G2mildly

decreased 60-89 32.9 2.2 0.3 35.4

G3amildly to

moderately decreased

45-59 3.6 0.8 0.2 4.6

G3bmoderately to severely decreased

30-44 1.0 0.4 0.2 1.6

G4severely

decreased 15-29 0.2 0.1 0.1 0.4

G5kidney failure <15 0.0 0.0 0.1 0.1

93.2 5.4 1.3 100.0

CKD Stage 3:6.2%

Stage G3a, A1: 3.6%

CKD11.5%

Risk CategoriesModerate 73%

High 18%Very High 9%

Premises

• GFR is the measure of kidney function we wish to assess.

• eGFR from serum levels of filtration markers is more practical than mGFR for routine clinical assessment.

• We want clinical laboratories to report eGFR when we measure the filtration marker.

• We need to recommend a single equation for laboratories for each filtration marker for routine eGFR reporting. www.probelog.com/20071005_glomerulus_sm.jpg

mGFR eGFR outcomes

Relationship of Measured and Estimated GFR to Clinical Outcomes

mGFR eGFR outcomes

CKD-EPI

Performancecreatinine

CGMDRD StudyCKD-EPI

cystatin CCKD-EPI

panel

CKD-PC

Associationsdrug dosingdisease definitionprevalenceprognosis

“True GFR”• GFR is a physiological property. It is variable,

influenced by body size, time of day, feeding.

• It cannot be measured directly. It is assessed from clearance measurements or serum levels of “filtration markers.”

• Measured and estimated GFR are associated with error (bias and imprecision).– Filtration marker handling (non-GFR determinants)

– Clearance procedures

– Assays

• “True GFR” is a hypothetical concept. Operational definition – average value over 1-2 days.

Filtration Markers• Substances that are

filtered by the glomeruliwhich can be used to measure or estimate the GFR

• Exogenous or endogenous

• Ideal properties– Freely filtered

• MW <20,000 d• MR <1.5 nm• not protein bound

– Not reabsorbed or secreted by the tubule

– Easy to measureStokes Einstein radius (nm)

Haraldsson, Nystroöm, Deen. Physiol Rev 88: 451–487, 2008

Inulin (5200)

Clearance Measures andFiltration Markers

Clearance Method Filtration Marker

Type Name Comments

Urinary

Continuous IV

Exogenous

Inulin Gold standard

Urinary

Bolus IV or SC

125I-Iothalamate Secreted

Urinary or Plasma Bolus IV

51Cr-EDTA Not available in the US

99mTC-DTPA Quality Control

Iohexol Assay

Urinary Endogenous CreatinineSecreted

Collection errors

Relationship of Plasma Level of Endogenous Filtration Markers to GFR

G(cells)

G(diet)

U x V(kidney)

GFRTRTS

P

E(gut, liver)

U x V = GFR x P – TR + TS

G – E = GFR x P – TR + TS

GFR = (G + TR – TS – E) / P

Reciprocalrelationship

between GFR and P, modified by non-GFR

determinants

Relationship of Plasma Level of Endogenous Filtration Markers to GFR

G(cells)

G(diet)

U x V(kidney)

GFRTRTS

P

E(gut, liver)

U x V = GFR x P – TR + TS

G – E = GFR x P – TR + TS

GFR = (G + TR – TS – E) / P

Estimating equationsuse regression to relate

measured GFR to P using surrogates for non-GFR

determinants

Relationship of Plasma Level of Endogenous Filtration Markers to GFR

G(cells)

G(diet)

U x V(kidney)

GFRTRTS

P

E(gut, liver)

U x V = GFR x P – TR + TS

G – E = GFR x P – TR + TS

GFR = (G + TR – TS – E) / P

P

Assaystandardizationand calibration

Development and Validation of Estimating Equations

• Separate datasets for development and validation populations

• Study populations with a wide range of clinical characteristics and GFR, representative of the clinical populations in which equations are to be applied.

• Reference methods for mGFR and serum concentrations

• Surrogates with a priori relationship to non-GFR determinants

• Linear regression of log mGFR on log P• Standard metrics for evaluation: bias, precision,

accuracy, and classification-reclassification.

Creatinine

G(muscle)

G(diet)

U x V(kidney)

GFRTS

S

E(gut)

U x V = GFR x S + TS

G - E = GFR x S + TS

GFR =(G - E - TS) / S

Age, sex, race,weight

Stevens and Levey. JASN 2009 20:2305-13

Creatinine-Based GFR Estimating Equations

Cockcroft-Gault formula

Ccr (ml/min) = (140-age) x weight *0.85 if female

72 Scr

MDRD Study equation

GFR (ml/min/1.73 m2) = 175 x (Scr)-1.154 x (age)-0.203

x (0.742 if female) x (1.212 if African American)

CKD-EPI equation

GFR = 141 x [min(Scr/κ),1)α x max(Scr/κ),1)-1.209 ] x -0.993Age x 1.018 [if female] x [1.157 if AA]

α is 0.329 for females and 0.411 for males; min indicates minimum of Scr/ or 1, and max indicates maximum of Scr/ or 1

Performance of the MDRD Study and Cockcroft-Gault (CG) equations before and after calibration of serum creatinine assays

After CalibrationBefore Calibrated

MDRD Before After

%∆ 9.0 5.8

1-P30 20 17

CG Before After

%∆ -2.0 11.4

1-P30 26 31

N=5504 Stevens et al AJKD 2007

Performance of the CKD-EPI and MDRD Study Equations

N=3896, Levey et al. Ann Intern Med 2009: 150: 604-612

All 60-89

∆ 5.5 11.9

1-P30 19.4 17.7

All 60-89

∆ 2.5 4.2

1-P30 15.9 13.2

N = 940,366 in 25 cohorts, Matsushita JAMA 2012

GFR Distribution and Risk Relationships in GP

Mean GFR <60 82 7.5% 89 5.3%

threshold6777

threshold6982

threshold5962

ACM CVM ESRD

↑ ↓ ↑ ↓ ↑ ↓

- 1.02 - 1.24 - 1.54

1.05 0.97 0.92 1.11 0.52 5.18

0.80 1.14 0.72 1.22 0.42 2.47

0.73 1.02 0.77 1.35 1.22 1.35

1.04 - 1.66 - 1.06 -

NRI: ACM = 0.11 (0.09-0.13); CVM = 0.12 (0.12-0.16); ESRD = 0.07 (0.2-0.12)

Reclassification of eGFR Categoriesby CKD-EPI and Risk Implications in GP Cohorts

HR adjusted for age, sex, race, smoking, SBP,total chol, diabetes, history of CVD and BMI.

Net reclassification improvement (NRI)by CKD‐EPI (GP)

Favoring CKD‐EPI

Favoring MDRD

Favoring CKD‐EPI

Favoring MDRD

Favoring CKD‐EPI

Favoring MDRD

Cystatin C

G(all cells,factors ?)

G(diet)

U x V(kidney)

GFRTR

S

E(?)

U X V = GFR x S - TR

G - E = GFR x S – TR

GFR =(G – E + TR) / S

Age, sex, ?

Coefficients for Variablesin the CKD-EPI Equations

Equations

Variable Creatinine* Cystatin C# Creatinine and Cystatin C#

Creatinine(above the knot)

Scr-1.209 - Scr-0.601

Cystatin C(above the knot)

- Scys-1.328 Scys-0.711

Age(linear)

0.993Age 0.996Age 0.995Age

Female Sex(above the knots)

0.75 0.93 0.83

Black Race 1.159 - 1.08*Equation development in 8254 subjects (Inker, NEJM 2012).

#Equation development in 5352 subjects (Levey, Ann Intern Med 2009).

Performance of Equationsin the Validation Dataset (N=1119)

Equations BiasPrecision

(IQR)Accuracy

(P30)

Creatinine alone (CKD-EPI) 3.7 15.4 87.2

Cystatin C alone 3.4 16.4 85.9

Creatinine-cystatin C 3.9 13.4* 91.5*

Average of creatinine alone and cystatin C alone

3.5 13.9 91.8

*P <0.001 compared to creatinine alone or cystatin C alone

Inker, NEJM 2012

Bias (Median Difference) by SubgroupGFR Distribution and Risk Relationships in GP

threshold598883

threshold698683

Mean GFR <60 85 9.7% 85 13.7%84 10.0%

N = 90,750 participants in 11 cohorts, Shlipak NEJM 2013

ACM CVM ESRD

↑ ↓ ↑ ↓ ↑ ↓

- 1.37 - 1.50 - 5.42

0.83 1.54 0.92 1.48 0.83 3.68

0.67 1.64 0.83 1.72 0.31 2.29

0.76 1.93 0.69 1.18 0.30 1.86

0.86 - 0.74 - 0.69 -

NRI: ACM = 0.13 (0.09-0.18); CVM = 0.10 (0.06-0.14); ESRD = -0.02 (-0.16-0.13)

Reclassification of eGFR Categories by eGFRcr-cysvs. eGFRcr and Risk Implications in GP Cohorts

HR adjusted for age, sex, race, smoking, SBP, totalchol, diabetes, history of CVD, BMI and albuminuria.

2012 KDIGO Guidelines Related to GFR Estimation

• 1.4.3.1 and 1.4.3.2 General recommendations

• 1.4.3.3 and 1.4.3.4 Recommendations regarding eGFRcreat

• 1.4.3.5 Confirmation of eGFRcreat <60 using cystatin C

• 1.4.3.6 and 1.4.3.7 Recommendations regarding eGFRcys

Next steps

• New cohorts

• Novel filtration markers– BTP

– B2M

– others

• Panel eGFR

Summary and Conclusions (1)• CKD-EPI creatinine equation compared to MDRD Study

equation– More accurate for estimating measured GFR– Lower CKD prevalence– More accurate risk predictions

• CKD-EPI cystatin C equation compared to creatinineequation– Not more accurate for estimating measured GFR– May be more accurate for low BMI– May be useful when race cannot be specified– More accurate risk predictions

• CKD-EPI combined creatinine and cystatin C equation compared to equations using either marker alone– More accurate for estimating measured GFR– May be useful for confirmation of eGFR <60

• They should be the standards for comparison to new equations.– They should be evaluated outside North America and Europe.

Summary and Conclusions (2)

GFR estimating equations are here to stay.• They are based on principles of physiology and have been

developed in large and diverse populations using standardized assays and rigorous statistical methods.

• They are useful in clinical practice, research and public health.

• Their appropriate use requires understanding of assays and non-GFR determinants of filtration markers and principles of diagnostic testing.

• They can be improved by development in representative populations and use of new filtration markers.

• New filtration markers should be expressed as eGFR.• The goal should be routine availability of an estimated GFR

from a panel of markers as accurate as measured GFR.

Conceptual Model for CKDCVD

Drug toxicityMetabolic/hormonal

Other (Infection, cognitive impairment,

frailty, etc)

Kidney Outcomes ProgressionRemission

Conceptual Model for CKD

BiopsyMarkers

Transplant

urinealb/creat

>30 mg/g

eGFR<60

eGFR<15 or dialysis

>3 mos

Conceptual Model for CKD

9.7 m4.8%

7.7 m13.5 m6.7%

0.4 m0.2%

NHANES 1999-2004, Levey et al, Ann Intern Med 2009

23.6 m11.7%