University of Groningen

Novel aspects regarding mechanisms and consequences of albuminuriaScheven, Lieneke

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Chapter 2Consequences of the use of albumin to creatinine ratio instead of 24-hour urinary albumin excretion for albuminuria staging

Lieneke SchevenPriya VartHiddo J. Lambers HeerspinkPaul E. de JongDick de ZeeuwRon T. Gansevoort

Submitted

20

Abstract

Introduction

New guidelines advocate the use of albumin to creatinine ratio in a urine sample (ACR) instead

of 24h-urinary albumin excretion (UAE) for staging albuminuria. Concern has been expressed

that this may result in misclassification because of among others interindividual differences in

urinary creatinine excretion. We examined the number of participants that are reclassified when

using ACR instead of UAE, the characteristics of reclassified participants and their outcome.

Methods

Included were 6,047 participants of the PREVEND and RENAAL studies of whom data on UAE

and ACR (in a first morning void urine sample) were available at baseline. For categorization

3 albuminuria classes were used as advocated by KDIGO (<30, 30-300, >300 mg/24h and

mg/g).

Results

When using ACR in the first morning void instead of UAE 89% of participants were classified

in corresponding albuminuria categories. 234 (3.9%) participants were classified to a higher

and 426 (7.0%) to a lower category. Participants that were reclassified upward had in general

a worse cardiovascular risk profile when compared to non-reclassified participants, whereas

the reverse was true for downward reclassified participants. In line, Cox regression analyses

showed that upward reclassification when using first morning void ACR instead of UAE was

associated with a tendency for increased risk for cardiovascular morbidity and mortality and

all-cause mortality, whereas downward reclassification was associated with a tendency for

lower risk. The Net Reclassification index, adjusted for age, gender and duration of follow-up,

when using ACR categories instead of UAE categories was 0.068 (p=0.016) for cardiovascular

events and 0.064 (p=0.015) for all-cause mortality.

Conclusion

Our results indicate that although there is reclassification when using first morning void albumin

to creatinine ratio instead of 24h-urinary albumin excretion, reclassification is often correct and

indicative for prognosis.

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Introduction

Elevated albuminuria has been established as a valuable risk marker for renal and cardiovascular

complications (1-5). Albuminuria can be assessed in several ways, of which measurement

of 24-hour urinary albumin excretion (24h UAE) was for long considered the gold standard.

Recent guidelines, however, advocate the use of the albumin to creatinine ratio (ACR) in a spot

urine sample (6). Opponents of the use of ACR to assess albuminuria argue that sometimes a

subject is called having increased albuminuria based on an ACR, whereas a 24h-urine collection

does not support this.

Reasons for discrepancy between albuminuria staging based on 24h UAE versus ACR can

be, first, that an increased ACR may not only be due to an increase in albuminuria, but also

to a decrease in urinary creatinine concentration. Creatinine, as waste product of muscle

catabolism, is dependent on muscle mass and consequently differs by, among others, age

and gender. Second, albuminuria is subject to a circadian rhythm, whereas urinary creatinine

excretion is fairly stable during the day (7). Assessment of the ACR  in a first morning urine

sample may therefore reveal another value than the ACR in a 24h-urine collection. Third, 24h

UAE is subject to collection errors and reclassification to another risk category based on spot

urine ACR may therefore also be due to incorrect 24h urine collection.

The aim of this study is to analyze  whether misclassification  by expressing albuminuria as

ACR instead of 24h UAE plays an important role. Importance is assessed by calculating the

percentage of participants in which it occurs, as well as by studying whether reclassification

reflects clinical characteristics and prognosis in these participants. For these analyses we

used data of two studies in which sera, and 24h-urine and first morning urine samples were

available and allowed calculation of 24h UAE and ACR.

Patients and Methods

This study is a collaboration between the investigators of the Prevention of REnal and Vascular

ENd-stage Disease (PREVEND) study and the Reduction of Endpoints in NIDDM with the

Angiotensin II Antagonist Losartan (RENAAL) study. This collaboration was established

to ensure sufficient participants in all three albuminuria classes of the present CKD staging

system for analyses.

22

Study design and population

The PREVEND study is a prospective cohort study which investigates the natural course of

albuminuria and its relation to renal and cardiovascular disease. Details of the study protocol

have been published elsewhere (9,10). In brief, the participants of the PREVEND study have

been selected in 1997 from subjects of the general population in Groningen, aged 28–75

years. Pregnancy and insulin usage were exclusion criteria. In total, 8,592 subjects participated

in the first screening (1997–98), of which 6,000 participants had a UAC >10 mg/L in the spot

morning urine sample and 2,592 participants a UAC <10 mg/L. This screening consisted

of two outpatient clinic visits, where baseline measurements were performed. Part of this

screening was that participants collected two 24h urines, of which the first sample was used

for the present analyses.

The RENAAL study is a multinational, double-blind randomised placebo-controlled study that

evaluated the renal protective effects of the angiotensin-II blocker losartan in patients with type

2 diabetes and nephropathy. The study design and results have been reported elsewhere (11-

13). In brief, in- and exclusion criteria for the RENAAL study were: type 2 diabetes (assessed

as age over 30 years old at time of diagnosis, no history of ketoacidosis and not using insulin

therapy within 6 months after diagnosis), a serum creatinine between 1.3 and 3.0 mg/dl (1.5 to

3.0 mg/dl for males more than 60 kg), a urinary ACR from a first-morning specimen of at least

300 mg/g, HbA1c<12% and age between 31 and 70 years. All patients collected at baseline a

first-morning void urine sample for albumin and creatinine assessment. In addition, a random

sample of 701 patients collected 24-hour urine samples for quantification of UAE.

Both studies were approved by medical ethics committees and conducted in accordance with

the International Conference of Harmonization Good Clinical Practice Guidelines and adhere to

the ethical principles that have their origin in the Declaration of Helsinki.

For the present analyses we use data of participants in the two studies of whom sera, 24h-urine

and first morning urine samples were available and allowed calculation of 24h UAE and ACR

in a first morning sample. Furthermore, participants with errors in their 24h-urine sampling

were excluded, leaving 6,047 participants for the present study (5,366 of 8,592 PREVEND

participants and 681 of 1,513 RENAAL participants).

Measurements and Definitions

At the baseline visit anthropometrical measurements were performed, blood pressure was

measured and fasting blood and urine samples were taken in which analytes were measured

using routine methodology. Urinary albumin concentration was measured by nephelometry

(PREVEND: BNII, Dade Behring Diagnostic, Marburg, Germany; RENAAL: Beckman Array,

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Beckman, Fullerton, California, USA).

Participants that smoked in the year prior to the baseline screening were regarded smokers.

Cardiovascular disease history was defined by self-report. Hypertension was defined in

accordance with the JNC-7 criteria as systolic blood pressure (SBP) of ≥140 mmHg or diastolic

blood pressure (DBP) ≥90 mmHg or use of antihypertensive medication. Diabetes was defined

in accordance with the ADA criteria as a fasting glucose level of >7.0 mmol/L or non-fasting

glucose level of >11.1 mmol/L or use of anti-diabetic medication. Body mass index (BMI) was

calculated as the ratio between weight and the square of height (weight/height2). Errors in

24h-urine collections were defined as the upper and lower 2.5% of the difference between the

estimated creatinine excretion rate and the actually measured creatinine excretion rate. The

estimated creatinine excretion rate was calculated by: eCER = 879.89 + 12.51 * weight (kg) -

6.19 * age + (34.51 if black) - (379.42 if female) (14).

Albuminuria measures

24h UAE (mg/24h) is given as urinary albumin concentration times volume of one 24h-urine

collection. ACR (mg/g) was calculated by dividing urinary albumin concentration (mg/L) by

urinary creatinine concentration (g/L). Cut-off values indicating normoalbuminuria, and

moderately and severely increased albuminuria were defined in accordance with the prevailing

KDIGO CKD guideline (6): for 24h UAE <30, 30-300 and >300 mg/24h, and for ACR <30, 30-

300 and >300 mg/g, respectively.

Outcome

The outcomes assessed were cardiovascular morbidity and mortality and all-cause mortality

during follow-up. In PREVEND information on date and cause of death was obtained by

record linkage with the Dutch Central Bureau of Statistics. Information on hospitalization for

cardiovascular morbidity was obtained from PRISMANT, the Dutch national registry of hospital

discharge diagnoses. In RENAAL information on cardiovascular morbidity and mortality was

collected prospectively. For this study, incident cardiovascular morbidity was defined according

the Major Adverse Cardiovascular Events (MACE) criteria (11)

Statistical analysis

Baseline characteristics were calculated for the overall population and for participants stratified

according to the three UAE categories. Continuous data are reported as mean ± standard

deviation (SD). In case of non-parametric data distribution, medians with interquartile ranges

(IQR) are presented. Differences in baseline characteristics between the three UAE subgroups

were calculated with a Chi-square test for categorical data and for continuous data with a one-

24

way ANOVA (in case of non-parametric data a Kruskal–Wallis ANOVA by ranks test).

To assess reclassification, we created 3x3 cross-tabulations using the aforementioned clinically

relevant cut-off values for 24h UAE and ACR. In these tables the proportion of reclassified

participants was calculated. The McNemar test, a nonparametric test for comparing two

related samples, was used to test the significance of the ratios of up and down classification

between 24h UAE versus ACR. Differences in characteristics between non-reclassified and

reclassified pariticpants in table 2 were calculated with a Chi-square test for categorical data,

and for continuous data with Student’s t-test (in case of normally distributed data) or Mann

Whitney test (in case of non-parametric data).

In addition, we assessed whether risk of cardiovascular morbidity and mortality, and all-

cause mortality differed between participants reclassified and those not reclassified. For risk

assessment Cox regression analyses were used, first crude, second adjusted for age and

gender, and subsequently also for baseline UAE and strata for participation in the PREVEND or

RENAAL study. Follow-up time was defined as the period to the first outcome or loss to follow-

up. Individuals who were free of these outcomes by December 31, 2000 in the RENAAL study

and by January 1, 2009 in the PREVEND study, were subject to administrative censoring.

To assess reclassification we calculated net reclassification improvement (NRI) for cardiovascular

morbidity and mortality and all-cause mortality (15). Net reclassification improvement (NRI)

is a statistic that allows calculation of the effect of reclassification of individuals from one

disease category to the other. It is a difference of two ratios; clinically correct reclassification

minus clinically incorrect classification. The range of this difference is from −1 to +1 with a

negative number reflecting incorrect reclassification and a positive number indicating correct

reclassification. Given the difference in follow-up duration in PREVEND and RENAAL, we

calculated NRI adjusted for age, gender as well as for duration of follow-up. NRI was also

calculated per subgroup of age (above and below the median age in event cases), gender, BMI

(<30 and ≥30 kg/m2), and hypertension and diabetes mellitus status.

All calculations were performed with SPSS (version 18.0) and STATA (version 12.0) software. A

p-value of less than 0.05 was considered to indicate statistical significance.

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Results

Baseline characteristics

Table 1 shows the baseline characteristics of the 6,047 participants. Mean age of the total

cohort was 50.8 ±12.9 years and half of the participants were female. When albuminuria was

assessed as 24h UAE (mg/24h) or as ACR (mg/g), the prevalence of moderately increased

albuminuria was 11.9% and 11.2%, respectively, and the prevalence of severely increased

albuminuria 11.7% and 10.5%, respectively. Table 1 also shows that when participants had

higher UAE their cardiovascular risk profile was higher, i.e. these participants were older,

more often male, more obese, and had a higher prevalence of hypertension and diabetes.

Differences in characteristics between in- and excluded PREVEND participants, and between

in- and excluded RENAAL participants, are shown in Supplementary Table 1. These differences

were in general numerically very small, although because of the large number of participants

they sometimes reached statistical significance.

Reclassification when using ACR instead of 24h UAE

When using ACR instead of 24h UAE 89% of participants were classified in corresponding

albuminuria categories (Table 2). 234 (3.9%) participants were classified to a higher and 426

(7.0%) to a lower category (Table 2). Participants who were reclassified upward to a higher

albuminuria category when using ACR instead of 24h UAE (for example when comparing 24h

UAE <30mg/24h and reclassification to a higher ACR category) were older in comparison to

participants that were not reclassified (52.6 ±13.0 vs. 48.1 ±12.5 yrs, p<0.001), and more often

of female gender (74.4 vs. 53.0%, p<0.001), diabetic (4.0 vs 1.7, p=0.004) and hypertensive

(35.5% vs 28.4%, p=0.017). Furthermore, they had a higher body mass index (26.4 vs. 25.7

kg/m2, p=0.014), and tended to have more often a cardiovascular disease history (6.2% vs.

4.3%, p=0.068). In contrast, the participants reclassified downward to a lower albuminuria

stage (for example when comparing 24h UAE >300mg/24h and reclassification to a lower

ACR category) were less often of female gender (26.8 vs. 37.7%, p=0.041), diabetic (66.7

vs. 92.6%, p<0.001) and hypertensive (94.2 vs. 98.2%, p=0.013). Furthermore, they had less

often a cardiovascular disease history (42.9 vs. 75.0% p<0.001) (Table 2).

Clinical consequences of reclassification

The 6,047 participants had a median follow-up time of 10.5 [6.2-10.8] years (a total of 51,509

person years), during which 732 events of cardiovascular morbidity and mortality and 1,082

events of all-cause mortality occurred. Participants that were reclassified upward had higher

event rates and participants that were reclassified downward had lower event rates when

compared to non-reclassified participants. Cox regression analyses showed that upward

26

Tab

le 1

. Bas

elin

e ch

arac

teris

tics

of s

tudy

pop

ulat

ion

over

all a

nd a

ccor

ding

to 2

4h a

lbum

inur

ia s

tage

s

Uri

nary

Alb

umin

Exc

reti

on

(mg

/24h

)

Ove

rall

<30

30-3

00>

300

(N=

6,04

7)(n

=4,

619)

(n=

720)

(n=

708)

p-v

alue

Age

(yrs

)50

.8 ±

12.9

48.3

±12

.657

.6 ±

12.1

59.8

±8.

1<

0.00

1

Mal

e ge

nder

(%)

49.9

45.7

63.5

63.8

0.00

7

Bod

y m

ass

inde

x (k

g/m

2 )26

.4 ±

4.6

25.7

±3.

927

.9 ±

4.7

29.9

±6.

2<

0.00

1

Sm

okin

g (%

)35

.537

.439

.319

.5<

0.00

1

His

tory

of c

ardi

ovas

cula

r di

seas

e (%

)8.

04.

415

.723

.7<

0.00

1

Ser

um g

luco

se (m

g/dL

)84

.7 (7

7.5-

95.5

)82

.9 (7

7.5-

90.1

)90

.1 (8

1.1-

106.

3)15

1.0

(111

.0-2

08.0

)<

0.00

1

Use

of g

luco

se lo

wer

ing

med

icat

ion

(%)

7.3

0.9

8.5

47.6

<0.

001

Dia

bete

s m

ellit

us (%

)13

.91.

817

.988

.4<

0.00

1

Sys

tolic

blo

od p

ress

ure

(mm

Hg)

131.

6 ±

21.8

126.

4 ±

18.7

145.

1 ±

23.9

151.

9 ±

20.8

<0.

001

Use

of a

ntih

yper

tens

ive

med

icat

ion

(%)

21.9

12.1

31.3

76.3

<0.

001

Hyp

erte

nsio

n (%

)40

.928

.768

.592

.5<

0.00

1

Ser

um c

hole

ster

ol (m

g/dL

)21

9.0

±45

.321

2.4

(185

.3-2

43.2

)22

3.9

(196

.9-2

51.9

)22

2.0

(194

.0-2

60.0

)0.

019

Ser

um c

reat

inin

e (m

g/dL

)1.

05 ±

0.4

0.93

±0.

161.

09 ±

0.39

1.78

±0.

67<

0.00

1

Ser

um a

lbum

in (g

/dL)

4.5

±0.

44.

6 ±

0.3

4.5

±0.

33.

8 ±

0.5

0.00

2

24-h

our

urin

e

- U

rine

albu

min

con

cent

ratio

n (m

g/L)

7.4

(4.2

-19.

9)5.

6 (3

.4-9

.1)

42.5

(28.

3-73

.9)

707.

5 (3

56.0

-147

0.0)

<0.

001

- U

rinar

y al

bum

in e

xcre

tion

(mg/

24h)

9.8

(6.3

-27.

1)7.

9 (5

.8-1

1.7)

63.4

(41.

7-11

0.6)

1378

.0 (6

79.5

-285

4.0)

<0.

001

- U

rine

crea

tinin

e co

ncen

trat

ion

(g/L

)0.

98 ±

0.4

0.98

±0.

51.

00 ±

0.4

0.84

±0.

40.

001

- A

lbum

in-c

reat

inin

e ra

tio (m

g/g)

7.6

(4.9

-20.

5)6.

1 (4

.5-9

.0)

46.3

(29.

2-89

.3)

1068

.9 (5

23.7

-242

1.8)

<0.

001

Firs

t-m

orni

ng v

oid

- U

rine

albu

min

con

cent

ratio

n (m

g/L)

12.6

(7.4

-25.

9)11

.1 (5

.6-1

4.7)

34.7

(19.

5-61

.1)

665.

0 (3

06.5

-137

2.5)

<0.

001

- U

rine

crea

tinin

e co

ncen

trat

ion

(g/L

)1.

37 ±

0.7

1.51

±0.

71.

16 ±

0.6

0.71

±0.

4<

0.00

1

- A

lbum

in-c

reat

inin

e ra

tio (m

g/g)

8.3

(5.0

-22.

2)6.

5 (4

.4-1

0.4)

33.5

(18.

5-68

.6)

996.

5 (4

48.4

-230

2.3)

<0.

001

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Table 2. Characteristics of study participants by urinary albumin categories using the 24h urinary albumin

excretion

(mg/24h) and the albumin to creatinine ratio (mg/g)

ACR (mg/g)

<30 30-300 >300

UAE (mg/24h) (n=4,734) (n=678) (n=635)

<30 (n=4,619)

No. 4416 198 5

Age (years) 48.1 ± 12.5 52.6 ± 13.0 NR

Male (%) 46.6 25.8 NR

Body mass index (kg/m2) 25.7 ± 3.9 26.4 ± 4.7 NR

Smoking (%) 37.9 31.3 NR

CVD history (%) 4.3 6.2 NR

Diabetes mellitus (%) 1.7 4.0 NR

Hypertension (%) 28.4 35.5 NR

30-300 (n=720)

No. 317 372 31

Age (years) 54.6 ± 12.8 59.7 ± 11.2 63.6 ± 7.4

Male (%) 67.8 60.8 51.6

Body mass index (kg/m2) 27.5 ± 4.7 28.1 ± 4.6 29.3 ± 6.5

Smoking (%) 42.6 38.7 12.9

CVD history (%) 11.7 19.5 69.2

Diabetes mellitus (%) 6.4 22.9 77.4

Hypertension (%) 59.3 75.3 100

>300 (n=708)

No. 1 108 599

Age (years) NR 60.3 ± 8.3 59.7 ± 8.1

Male (%) NR 73.2 62.3

Body mass index (kg/m2) NR 30.5 ± 4.8 29.8 ± 6.4

Smoking (%) NR 23.4 18.9

CVD history (%) NR 42.9 75.0

Diabetes mellitus (%) NR 66.7 92.6

Hypertension (%) NR 94.2 98.2

UAE= urinary albumin excretion, ACR=albumin creatinine concentration, CVD=cardiovascular disease,

NR=not reliable because of low numbers

28

reclassification when using ACR instead of 24h UAE was associated with a significantly

increased risk of cardiovascular morbidity and mortality, and all-cause mortality (Table 3). For

instance, for cardiovascular morbidity and mortality, upward reclassification from 24h UAE

moderately increased albuminuria (30-300 mg/24h) to an ACR severely increased albuminuria

(>300 mg/g) was associated with a crude Hazard Ratio of 2.83 (95% CI 1.46- 5.48) and

when adjusted for age, gender, baseline 24h UAE and cohort of 2.86 (95% CI 1.32- 6.16).

Downward reclassification was associated with a tendency to lower risk in crude analyses,

but not after adjustment for age and gender (Table 3). Similar results were obtained for all-

cause mortality. When using the NRI to analyze whether participants were reclassified upward

correctly to a higher cardiovascular risk category based on their ACR (i.e. that more of these

participants had a cardiovascular event during follow-up), it showed that the NRI adjusted

for age, gender and duration of follow-up was significantly positive i.e. 0.068 (0.013- 0.123),

p=0.016. NRI for all-cause mortality was 0.064 (0.013- 0.114), p=0.015. Figures 1 and 2

show NRIs for cardiovascular events and for all-cause mortality, respectively, across various

subgroups. NRIs for risk categorization using ACR instead of 24h UAE were positive or similar

in all subgroups, with lower values obtained in subgroups characterized by lower muscle

mass. For cardiovascular events the NRI was significantly lower for females when compared

to males (Figure 1), and for all-cause mortality again for females when compared to males, as

well as for age 60 or more when compared to less than 60 years (Figure 2).

Discussion

For practical reasons the ACR has been advocated as the standard method to assess

albuminuria for chronic kidney disease (CKD) staging instead of 24h UAE, which was

traditionally regarded to be the gold standard to assess albuminuria. This advice has led to

concern whether it may lead to misclassification and especially overdiagnosis of CKD, because

of the creatinine component in the ACR, and that upward reclassification by using ACR may

not reflect patient prognosis. We investigated these issues in the present study.

Various studies have previously compared timed urinary albumin excretion rates (in 24h or

overnight samples) and ACR, and investigated which ACR values correspond with the

traditionally used cut-off values for timed urinary albumin excretion rates to define CKD (16,17).

In general these studies are difficult to interpret because of the methodological shortcoming

that ACR was determined in the same urine sample as the timed urinary albumin excretion

rate (18). It is generally acknowledged that urinary albumin excretion follows a circadian rhythm

(19,20). This rhythm is dependent on among others posture, exercise and dietary factors (such

29

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Tab

le 3

. C

linic

al o

utco

mes

acc

ordi

ng to

recl

assi

ficat

ion

stat

us b

y al

bum

in to

cre

atin

ine

ratio

(AC

R, m

g/g)

com

pare

d w

ith 2

4h u

rinar

y al

bum

in e

xcre

tion

(UA

E, m

g/24

h)

Car

dio

vasc

ular

mo

rbid

ity

and

mo

rtal

ity

All-

caus

e m

ort

alit

y

By

AC

R (m

g/g

) rec

lass

ifica

tio

nB

y A

CR

(mg

/g) r

ecla

ssifi

cati

on

Do

wnw

ard

No

neU

pw

ard

Do

wnw

ard

No

neU

pw

ard

24h

UA

E (m

g/2

4h)

(n=

89)

(n=

608)

(n=

35)

(n=

127)

(n=

905)

(n=

50)

<30

Num

ber

of e

vent

sN

A34

125

NA

528

34

Cru

de in

cide

nce

rate

NA

8.2

13.8

NA

12.7

18.8

Cru

de h

azar

d ra

tioN

AR

efer

ence

1.71

(1.1

4 –

2.57

)N

AR

efer

ence

1.49

(1.0

6 –

2.11

)

Adj

uste

d ha

zard

rat

ioa

NA

Ref

eren

ce1.

61 (1

.07

– 2.

43)

NA

Ref

eren

ce1.

37 (0

.97

– 1.

95)

Adj

uste

d ha

zard

rat

iob

NA

Ref

eren

ce1.

44 (0

.96

– 2.

18)

NA

Ref

eren

ce1.

24 (0

.87

– 1.

76)

30-3

00

Num

ber

of e

vent

s58

9110

9213

816

Cru

de in

cide

nce

rate

21.6

31.9

98.9

34.2

48.3

157.

8

Cru

de h

azar

d ra

tio0.

68 (0

.49

– 0.

95)

Ref

eren

ce2.

83 (1

.46

– 5.

48)

0.71

(0.5

5 –

0.93

)R

efer

ence

3.14

(1.8

6 –

5.31

)

Adj

uste

d ha

zard

rat

ioa

0.85

(0.6

1 –

1.19

)R

efer

ence

2.78

(1.4

2 –

5.43

)0.

87 (0

.67

– 1.

14)

Ref

eren

ce3.

03 (1

.78

– 5.

15)

Adj

uste

d ha

zard

rat

iob

0.84

(0.5

8 –

1.21

)R

efer

ence

2.86

(1.3

2 –

6.16

)0.

89 (0

.67

– 1.

20)

Ref

eren

ce2.

85 (1

.55

– 5.

25)

>30

0

Num

ber

of e

vent

s31

176

NA

3523

9N

A

Cru

de in

cide

nce

rate

55.9

90.9

NA

63.2

123.

4N

A

Cru

de h

azar

d ra

tio0.

72 (0

.49

– 1.

07)

Ref

eren

ceN

A0.

58 (0

.40

– 0.

83)

Ref

eren

ceN

A

Adj

uste

d ha

zard

rat

ioa

0.70

(0.4

7 –

1.04

)R

efer

ence

NA

0.56

(0.3

9 –

0.80

)R

efer

ence

NA

Adj

uste

d ha

zard

rat

iob

0.85

(0.5

6 –

1.28

)R

efer

ence

NA

0.70

(0.4

8 –

1.03

)R

efer

ence

NA

a =

adj

uste

d fo

r ag

e an

d ge

nder

; b =

as

a+ a

dditi

onal

adj

ustm

ent f

or b

asel

ine

UA

E a

nd c

ohor

t

30

 

Figure 1. Net Reclassification Improvements (NRIs) for Cardiovascular Morbidity and Mortality for various

subgroups (*p<0.05 for difference in NRIs).

 

Figure 2. Net Reclassification Improvements (NRIs) for All-Cause Mortality for various subgroups (*p<0.05

for difference in NRIs).

31

Con

sequ

ence

s of

the

use

of a

lbum

in to

cre

atin

ine

ratio

inst

ead

of 2

4-ho

ur u

rinar

y

albu

min

exc

retio

n fo

r al

bum

inur

ia s

tagi

ngC

hapt

er 2

as protein and fluid intake), with lower values during nighttime than during daytime. It is therefore

to be expected that the cut-off values of ACR indicating microalbuminuria will be different when

these variables are measured in a spot morning sample instead of a 24-hour urine collection.

Consequently, ACR should be measured in a specifically collected spot or first morning void

urine sample and compared with a timed urinary albumin excretion sample. Only few studies

followed such a design, but these studies did not investigate what the consequences are for

CKD staging or risk classification when spot ACR is used instead of timed urinary albumin

excretion rates (21,22). Our study adds therefore novelty to existing literature.

Our findings indicate that using ACR instead of 24h UAE does not lead to more participants

being labeled as having CKD. Only a limited percentage of participants is reclassified (10.9%),

especially to a lower albuminuria stage (7.0%). The participants that were reclassified to a higher

albuminuria stage (3.9%) had in general a higher cardiovascular and renal risk profile, and an

increased risk for cardiovascular events as well as all-cause mortality when compared to non-

reclassified participants. The NRI when using ACR instead of 24h UAE for risk categorization

was also found to be significantly positive for cardiovascular events as well as for all-cause

mortality. In stratified analyses NRIs tended to be lower in subgroups characterized by lower

muscle mass, but were positive or similar in all subgroups. One may argue therefore that

participants have been correctly reclassified using ACR instead of 24h UAE. This assumption

is supported by our finding that reclassification seems for a part the result of errors in 24h urine

collection and therefore in errors in 24h UAE assessment. In participants reclassified upward

from the 24h UAE albuminuria stage 30-300 mg/24h to ACR stage >300 mg/g expected 24h

creatinine excretion was 13.8 (8.6- 15.9) mmol, whereas actually measured creatinine excretion

was only 7.8 (5.1- 10.9) mmol (p<0.05), suggesting that 24h urine collection was incomplete.

Our data thus do not provide evidence for overdiagnosis of CKD, nor for inadequate risk

stratification in reclassified subjects when using ACR instead of 24h UAE. As such these data

support the prevailing KDIGO guidelines that advise to use an ACR in a first morning void or

spot urine sample to assess albuminuria for CKD staging.

This study has limitations that should be acknowledged. First, this analysis comprises

participants of two separate studies, PREVEND and RENAAL, that differ in design. PREVEND

is a prospective, observational, general population based cohort study, whereas RENAAL is a

double-blind, randomized, placebo-controlled trial investigating the effect of the angiotensin-2

blocker losartan versus placebo in patients with type 2 diabetes and nephropathy. We

accounted therefore in our Cox regression analyses for differences in design and participant

characteristics using strata for cohort. Second, despite the combination of the two studies, still

some cells in the cross-tabulation tables included a relatively low number of participants, which

32

consequently leads to limited power when analyzing differences between non-recategorized

and recategorized participants. Third, we used for our analyses first morning void urine samples,

whereas in clinical practice often spot urine samples are used. It has been suggested that first

morning void urine samples may be more reliable than a spot urine sample to diagnose and

monitor increased albuminuria (21). Whether our results will be similar when using spot urine

samples instead of first morning voids needs therefore additional study.

Strengths of this study are the availability of a large number of participants with higher levels

of albuminuria, and that in participants both 24 UAE as well as ACR in a first morning void

were assessed. Only very few other epidemiological studies, if any, collected these data

simultaneously. Furthermore, albuminuria was measured in fresh urine samples like in clinical

practice, and not in samples that have been stored frozen. It has previously been shown that

frozen storage of urine samples leads to a decrease in average urinary albumin concentration,

with more variability, which negatively affects the prognostic value of albuminuria (23).

Furthermore, in study participants data on incident cardiovascular events and mortality were

collected prospectively. Lastly, by design we excluded subjects in whom it was likely that

24h urine collection was inadequate. Even in this scenario using ACR was as strong, or even

stronger, for risk categorization when compared to using 24h UAE, which makes our findings

robust.

In conclusion, our results indicate that reclassification when using ACR instead of 24h UAE

is limited, that reclassification is more often downward than upward, leading to a smaller

number of subjects being labelled as having CKD, and that upward reclassified subjects

have a worse prognosis with respect to incident cardiovascular events and mortality and

downward reclassified subjects have a lower risk. These data thus do not provide evidence for

overdiagnosis of CKD or to misclassification with respect to prognosis in reclassified subjects

when using ACR instead of 24h UAE. Consequently our findings support the advice of the

prevailing KDIGO guidelines to use ACR in a first morning void or spot urine sample to stage

CKD.

Disclosures

The PREVEND study was financially supported by several grants from the Dutch Kidney

Foundation. In this study measurement of urinary albumin concentration was sponsored by

Dade Behring Diagnostica, Marburg, Germany and Roche Diagnostics, Mannheim, Germany.

The RENAAL study was sponsored by Merck & Co, Inc, USA.

33

Con

sequ

ence

s of

the

use

of a

lbum

in to

cre

atin

ine

ratio

inst

ead

of 2

4-ho

ur u

rinar

y

albu

min

exc

retio

n fo

r al

bum

inur

ia s

tagi

ngC

hapt

er 2

References

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M, Levey AS, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause

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2. Gansevoort RT, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, et al. Lower

estimated GFR and higher albuminuria are associated with adverse kidney outcomes in both general

and high-risk populations. A collaborative meta-analysis of general and high-risk population cohorts.

Kidney Int 2011 Feb 2.

3. Astor BC, Matsushita K, Gansevoort RT, van der Velde M, Woodward M, Levey AS, et al. Lower

estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-

stage renal disease. A collaborative meta-analysis of kidney disease population cohorts. Kidney Int

2011 Feb 2.

4. van der Velde M, Matsushita K, Coresh J, Astor BC, Woodward M, Levey A, et al. Lower estimated

glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular

mortality. A collaborative meta-analysis of high-risk population cohorts. Kidney Int 2011 Feb 9.

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classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report.

Kidney Int 2011 Jul;80(1):17-28.

6. http://www.kdigo.org/clinical_practice_guidelines/pdf/CKD/KDIGO_2012_CKD_GL.pdf.KDIGO

Guidelines 2013.

7. Koopman MG, Krediet RT, Koomen GC, Strackee J, Arisz L. Circadian rhythm of proteinuria:

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8. Ellam TJ, El Nahas M. Proteinuria thresholds are irrational: a call for proteinuria indexing. Nephron Clin

Pract 2011;118(3):c217-24.

9. Mahmoodi BK, Gansevoort RT, Veeger NJ, Matthews AG, Navis G, Hillege HL, et al. Microalbuminuria

and risk of venous thromboembolism. JAMA 2009 May 6;301(17):1790-1797.

10. Lambers Heerspink HJ, Brantsma AH, de Zeeuw D, Bakker SJ, de Jong PE, Gansevoort RT, et al.

Albuminuria assessed from first-morning-void urine samples versus 24-hour urine collections as a

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11. Brenner BM, Cooper ME, de Zeeuw D, Grunfeld JP, Keane WF, Kurokawa K, et al. The losartan

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Syst 2000 Dec;1(4):328-335.

12. Brenner BM, Cooper ME, de Zeeuw D, Keane WF, Mitch WE, Parving HH, et al. Effects of losartan on

renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med

2001 Sep 20;345(12):861-869.

13. Bakris GL, Weir MR, Shanifar S, Zhang Z, Douglas J, van Dijk DJ, et al. Effects of blood pressure

level on progression of diabetic nephropathy: results from the RENAAL study. Arch Intern Med 2003

Jul 14;163(13):1555-1565.

34

14. Ix JH, Wassel CL, Stevens LA, Beck GJ, Froissart M, Navis G, et al. Equations to estimate creatinine

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16. Dyer AR, Greenland P, Elliott P, Daviglus ML, Claeys G, Kesteloot H, et al. Evaluation of measures of

urinary albumin excretion in epidemiologic studies. Am J Epidemiol 2004 Dec 1;160(11):1122-1131.

17. Lambers Heerspink HJ, Gansevoort RT, Brenner BM, Cooper ME, Parving HH, Shahinfar S, et al.

Comparison of different measures of urinary protein excretion for prediction of renal events. J Am Soc

Nephrol 2010 Aug;21(8):1355-1360.

18. Gansevoort RT, Brinkman J, Bakker SJL, de Jong PE, de Zeeuw D: Evaluation of Measures of Urinary

Albumin Excretion. American Journal of Epidemiology 2006, 164: 725-727.

19. Hansen HP1, Tauber-Lassen E, Jensen BR, Parving HH: Effect of dietary protein restriction on

prognosis in patients with diabetic nephropathy. Kidney Int. 2002 Jul;62(1):220-8.

20. van Acker BA1, Stroomer MK, Gosselink MA, Koomen GC, Koopman MG, Arisz L: Urinary protein

excretion in normal individuals: diurnal changes, influence of orthostasis and relationship to the renin-

angiotensin system. Contrib Nephrol. 1993;101:143-50.

21. Witte EC, Lambers Heerspink HJ, de Zeeuw D, Bakker SJL, de Jong PE, Gansevoort R: First

Morning Voids Are More Reliable Than Spot Urine Samples to Assess Microalbuminuria. Journal of

the American Society of Nephrology 2009, 20: 436-443.

22. Chavan VU, Durgawale PP, Sayyed AK, Sontakke AV, Attar NR, Patel SB, Patil SR, Nilakhe SD.: A

Comparative Study of Clinical Utility of Spot Urine Samples with 24-h Urine Albumin Excretion for

Screening of Microalbuminuria in Type 2 Diabetic Patients. Indian J Clin Biochem. 2011 Jul;26(3):283-

9.

23. Brinkman JW, de Zeeuw D, Gansevoort RT, Duker JJ, Kema IP, de Jong PE, Bakker SJ: Prolonged

Frozen Storage of Urine Reduces the Value of Albuminuria for Mortality Prediction. Clin Chem. 2007

Jan;53(1):153-4.

35

Con

sequ

ence

s of

the

use

of a

lbum

in to

cre

atin

ine

ratio

inst

ead

of 2

4-ho

ur u

rinar

y

albu

min

exc

retio

n fo

r al

bum

inur

ia s

tagi

ngC

hapt

er 2

Sup

ple

men

tary

Tab

le 1

. Bas

elin

e ch

arac

teris

tics

of in

clud

ed a

nd e

xclu

ded

PR

EV

EN

D a

nd R

EN

AA

L st

udy

part

icip

ants

PR

EV

EN

DR

EN

AA

L

Incl

uded

(n=

5,36

6)E

xclu

ded

(n=

3,22

6)p

-val

ueIn

clud

ed(n

=68

1)E

xclu

ded

(n=

832)

p-v

alue

Age

(yea

rs)

49.5

± 1

2.9

48.7

± 1

2.2

0.00

159

.9 ±

7.4

60.0

± 7

.50.

342

Mal

e (%

)48

53<

0.00

162

640.

182

Bod

y M

ass

Inde

x (k

g/m

2 )25

.9 ±

4.1

26.3

± 4

.40.

001

30.0

± 6

.329

.4 ±

6.2

0.04

1

Sm

okin

g (%

)38

380.

5717

190.

24

Ser

um g

luco

se (m

g/dL

)85

(77

– 92

)86

(79

– 95

)0.

0716

2 (1

23-2

14)

158

(120

-213

)0.

54

Use

of g

luco

se lo

wer

ing

med

icat

ion

(%)

1.5

1.5

0.47

100

100

1.00

Dia

bete

s m

ellit

us (%

)3

40.

014

100

100

1.00

Sys

tolic

blo

od p

ress

ure

(mm

Hg)

129

± 2

112

9 ±

20

0.68

151

± 2

015

4 ±

19

0.00

3

Use

of a

ntih

yper

tens

ive

med

icat

ion

(%)

1513

0.03

610

010

01.

00

Hyp

erte

nsio

n (%

)34

330.

1310

010

01.

00

Ser

um c

hole

ster

ol (m

g/dL

)21

8 ±

44

218

± 4

20.

6222

5 ±

53

230

± 5

70.

035

Ser

um c

reat

inin

e (m

g/dL

)0.

95 ±

0.2

50.

95 ±

0.1

70.

511.

83 ±

0.5

1.89

± 0

.50.

18

Urin

ary

albu

min

exc

retio

n (m

g/24

hrs)

8.9

(6.2

-15.

9)10

.6 (6

.5-2

0.2)

0.46

1362

(596

-290

2)13

58 (5

92-2

900)

0.56