Use of Protein Creatinine Ratio Measurements on.pdf

Clinical Chemistry 51:9

1577–1586 (2005)

Review

Use of Protein:Creatinine Ratio Measurements on

Random Urine Samples for Prediction of

Significant Proteinuria: A Systematic Review

CHRISTOPHER P. PRICE, 1†* RONALD G. NEWALL, 1 and JAMES C. BOYD 2

Background: Proteinuria is recognized as an indepen-

dent risk factor for cardiovascular and renal disease and

as a predictor of end organ damage. The reference test, a

24-h urine protein estimation, is known to be unreliable.

A random urine protein:creatinine ratio has been shown

to correlate with a 24-h estimation, but it is not clear

whether it can be used to reliably predict the presence of

significant proteinuria.

Methods: We performed a systematic review of the

literature on measurement of the protein:creatinine ratio

on a random urine compared with the respective 24-h

protein excretion. Likelihood ratios were used to deter-

mine the ability of a random urine protein:creatinine

ratio to predict the presence or absence of proteinuria.

Results: Data were extracted from 16 studies investigat-

ing proteinuria in several settings; patient groups stud-

ied were primarily those with preeclampsia or renal

disease. Sensitivities and specificities for the tests

ranged between 69% and 96% and 41% and 97%, respec-

tively, whereas the positive and negative predictive

values ranged between 46% and 95% and 45% and 98%,

respectively. The positive likelihood ratios ranged be-

tween 1.8 and 16.5, and the negative likelihood ratios

between 0.06 and 0.35. The cumulative negative likeli-

hood ratio for 10 studies on proteinuria in preeclampsia

was 0.14 (95% confidence interval, 0.09–0.24).

Conclusion: The protein:creatinine ratio on a random

urine specimen provides evidence to “rule out” the

presence of significant proteinuria as defined by a 24-h

urine excretion measurement.

Proteinuria is recognized as an independent risk factor for

cardiovascular and renal disease and as a predictor of end

organ damage (1 ) . In particular, detection of an increase

in protein excretion is known to have both diagnostic and

prognostic value in the initial detection and confirmation

of renal disease (2 ) , and the quantification of proteinuria

can be of considerable value in assessing the effectiveness

of therapy and the progression of the disease (3–5 ) .

Although some investigators advocate the use of albumin

as an alternative to the total protein measurement (6–8)

and others have suggested that the profile of proteins

excreted has differential diagnostic and prognostic value

(9 ) , the National Kidney Foundation has recommended

that an increase in protein excretion be used as a screening

tool in patients at risk of developing renal disease (10 ) .An

increase in protein or albumin excretion has been used in

the early detection of several specific conditions, e.g.,

preeclampsia, diabetic nephropathy, and nephrotoxicity

attributable to drugs. In all of these clinical scenarios, it is

acknowledged that the definitive measurement of protein

or albumin excretion is based on a timed urine collection

over 24 h.

It is also recognized, however, that there are problems

associated with the collection of a 24-h urine, with several

reports identifying poor compliance. This further adds to

the cost of what can already be an expensive procedure

(11–13 ) . The use of a 24-h collection is necessitated by the

variation in protein excretion throughout the day, which

negates the use of concentration measurements in random

urine collections (14 , 15 ) .

Because the excretion of creatinine and protein is

reasonably constant throughout the day when the glomer-

ular filtration rate is stable (16 ) , some have proposed the

use of a ratio measurement of protein to creatinine in

urine samples collected over shorter time periods, or even

random (or “spot”) urine samples. Others have proposed

1 Diagnostics Division, Bayer Healthcare, Newbury, United Kingdom.

2 University of Virginia Health System, Department of Pathology, Char-

lottesville, VA.

†Visiting Professor in Clinical Biochemistry, University of Oxford, Oxford,

United Kingdom.

*Address correspondence to this author at: Diagnostics Division, Bayer

Healthcare, Bayer House, Strawberry Hill, Newbury, Berkshire, RG14 1JA,

United Kingdom.

Received February 17, 2005; accepted June 15, 2005.

Previously published online at DOI: 10.1373/clinchem.2005.049742

1577

1578

Price et al.: Urine Protein:Creatinine Ratio to Predict Proteinuria

the use of urine specific gravity or osmolality in the

denominator of the ratio (17 ) . Newman et al. (18 ) recently

showed that variations in protein and albumin excretion

in urine samples collected throughout the day are much

less when their concentrations are expressed as a ratio to

creatinine or specific gravity.

Several authors have studied the relationship between

the protein (or albumin):creatinine ratio and 24-h excre-

tion (16 , 19–41) . In some of these studies, the predictive

value for detecting significant proteinuria was calculated.

However, although the correlation statistics indicated a

close relationship between the ratio measurements and

24-h protein excretion, the data did not indicate the

confidence with which a random or spot urine ratio

measurement might be used to “rule in” or, alternatively,

“rule out” significant proteinuria.

We therefore conducted a systematic review of the

literature to evaluate the utility of the protein:creatinine

ratio in a random urine to rule in or rule out proteinuria.

We also extended the search to include data on the ratio to

osmolality. The measurement of 24-h protein excretion

was used as the reference (gold standard) method.

STATISTICAL ANALYSIS

Data from the studies examined were summarized by

graphical analysis and metaanalysis. Forest plots of test

sensitivities and specificities were constructed to allow

graphical comparisons among studies. Heterogeneity

among the studies for these measures was assessed by

)],

and diagnostic odds ratio (DOR) across the 10 preeclamp-

sia studies were calculated by random-effects ANOVA.

Cumulative metaanalysis of LR(

) was used

to characterize the progressive narrowing of confidence

intervals for their summary measures as information was

added from successive studies. Such information is useful

in assessing the need for further studies. The SAS proce-

dure GENMOD was used to carry out these calculations,

incorporating the restricted maximum likelihood estima-

tion method. Likelihood ratios were computed for each

study and used in constructing a summary ROC curve by

the method of Moses et al. (45 ) . The statistical significance

of the slope estimate,

) and LR(

, in the Moses analysis was used to

assess whether factors beyond variation in the test thresh-

old contributed to heterogeneity among the studies.

Materials and Methodology

We performed an electronic search of the Medline and

EMBASE databases, using the MeSH terms “urine protein

creatinine ratio”, “proteinuria”, “sensitivity”, and “speci-

ficity”. Only full papers and letters were included in the

search. After identifying potentially relevant papers, us-

ing the inclusion criteria described below, we also

searched the reference lists of the papers included for

additional relevant papers.

All titles and abstracts generated by the search were

reviewed and relevant full papers obtained. Each of the

papers was read by 2 authors (C.P.P. and R.G.N.). Inclu-

sion of papers in the data extraction stage was based on

the following criteria: ( a ) the main objective of the paper

was to assess use of a ratio measure for detection of

proteinuria; ( b ) the patient population was defined, in-

cluding age and pathology; ( c ) the number of patients and

any exclusion criteria were identified; ( d ) the timing of

collection of random urines was identified; ( e ) analytical

methods were defined; ( f ) cutoff values were defined for

the ratio and reference method; ( g ) 24-h urine protein

reference data were available for each urine sample; and

( h ) data were available to enable calculation of sensitivi-

ties, specificities, and positive and negative likelihood

ratios.

The 2

Results

2 contingency tables derived from the data

presented in the papers were used to calculate sensitivi-

ties, specificities, and positive and negative predictive

values. In some cases these values were not provided in

the original publications and had to be calculated from

the raw data. Positive and negative likelihood ratios were

determined by the “score” method as recommended by

Altman et al. (42 ) .

OVERVIEW OF SEARCH

The initial electronic search covering the period 1984–

2004 yielded a total of 276 titles. After a review of titles

and abstracts for relevance, 46 papers were selected and

full copies obtained; hand searching generated 2 addi-

tional papers. A total of 16 papers were subsequently

found to meet the inclusion criteria; these papers were

carried through to the data extraction stage. A summary

of the selection of studies to include in the review is

illustrated in Fig. 1. It was apparent that several of the

papers did not include the raw data on true- and false-

positive and -negative rates, and these rates had to be

calculated or extrapolated from the information given in

the publication.

The basic descriptions of the patient cohorts are docu-

mented in Table 1. A total of 10 studies included pregnant

women, either in the general population or as those

specifically considered to be at risk of preeclampsia, and 4

included patients attending renal clinics, including 2

cohorts of patients who had received kidney transplants.

One study focused specifically on proteinuria in the

elderly and another on patients attending a rheumatology

clinic.

Although the usual definition of significant proteinuria

is a protein excretion

300 mg/24 h, not all of the studies

used this threshold. The relationship between the sensi-

), positive and negative

likelihood ratios, respectively; DOR, diagnostic odds ratio; 95% CI, 95%

confidence interval.

) and LR(

testing according to the Cochran method (43 , 44 ) . Sum-

mary measures for sensitivity, specificity, positive likeli-

hood ratio [LR(

)], 3 negative likelihood ratio [LR(

3 Nonstandard abbreviations: LR(

Clinical Chemistry 51, No. 9, 2005

1579

10 5 ), deriving primarily

from the much lower DORs (6.1 and 5.2) observed in the

studies of Young et al. (20 ) and Durnwald and Mercer

(26 ) , respectively.

A summary ROC plot including all of the studies is

shown in Fig. 4. It should be noted that these data are

based on the cutoff values chosen by the investigators,

some of which were determined by ROC curve analysis.

In view of the nonsignificant

-coefficient in a Moses-type

0.09),

no significant heterogeneity was seen in odds ratios across

the 16 studies that was not accounted for by variation in

test threshold among studies. Although the summary

ROC plot indicated that ratio measures have high value in

predicting proteinuria, it did not enable the quality of

these tests in either the rule-in or rule-out modes to be

easily judged. We therefore focused further analysis on

likelihood ratios.

Forest plots of the LR(

coefficient

0.50; P

) for the 16 studies

are shown in Fig. 5. As with the specificities, there was

significant heterogeneity in the LR(

) and LR(

) across

the 10 preeclampsia studies ( P

0.0001 and P

0.015,

) stemmed pri-

marily from the unusually high value (0.34) noted in the

study of Durnwald and Mercer (26 ) . Summary estimates

of the LR(

Fig. 1. Details of the selection process for papers identified from the

initial electronic search and journal hand-searching routines.

) across the 10 preeclampsia

studies were 4.2 (95% CI, 2.6–6.9) and 0.14 (0.09–0.24),

respectively.

To determine the reliability of the data and whether

there is a need for more data to be produced, we per-

formed a cumulative metaanalysis of the likelihood ratios

in the 10 preeclampsia studies after placing the studies in

chronologic order. The cumulative data for the LR(

tivities, specificities, and the cutoff values chosen by the

researchers is plotted in Fig. 2; it should be noted that all

concentrations have been expressed in SI units to make

comparison across studies possible.

CORRELATION STATISTICS

A majority of the studies calculated correlation coeffi-

cients between the protein ratio and 24-h urinary protein

excretion, in some cases with no further analysis. These

data are summarized in Table 2 and indicate that the r

value was

)in

these studies are shown in Fig. 6. The first data point in

the cumulative values (i.e., first study) is therefore that

from the study of Quadri et al. (19 ) , whereas the last data

point in the cumulative values (bottommost value) repre-

sents the summary estimate (with 95% CI) of the LR(

0.9 in most cases. The data include additional

studies that did not furnish sufficient information for the

full analysis outlined above.

)

from all 10 studies. The upper limit of the 95% CI for the

cumulative LR(

) is 0.24, suggesting that based on cur-

rent evidence, the ratio of protein to creatinine in a

random urine sample can provide some evidence to rule

out the presence of proteinuria as judged by measurement

of protein in a 24-h urine sample.

POOLED ESTIMATES OF SENSITIVITY AND SPECIFICITY

Forest plots of the sensitivities and specificities from the

16 studies are shown in Fig. 3. Because of dissimilarities in

the underlying patient populations across the studies,

summary estimates of sensitivity, specificity, DOR,

LR(

) were computed only for the 10 studies

performed in preeclamptic women. The pooled estimate

of mean sensitivity for the protein:creatinine ratio from

the 10 preeclampsia studies was 0.90 [95% confidence

interval (95% CI), 0.86–0.93]. Similarly, the pooled esti-

mate of mean specificity was 0.78 (0.68–0.88). There was

apparent heterogeneity among the specificities of the

studies ( P

Discussion

An increase in urinary protein excretion is a widely

accepted tool in the detection, diagnosis, and manage-

ment of people considered to be at risk of developing

renal disease and has been advocated as part of a regular

check-up in such individuals (10 ) . The origins of this

recommendation lie in the fact that it is widely believed

that there will be a change in the amount of protein

excreted before any demonstrable change in glomerular

filtration, for example, as reflected in the creatinine

clearance (1 ) . Despite these recommendations, there re-

mains considerable variation in the use of methods for

0.0001), but no statistically significant heter-

ogeneity was detected among the sensitivities ( P

0.15).

The summary estimate of the DOR was 32 (95% CI,

14–75). There was significant heterogeneity in the DORs

among the studies ( P

summary ROC analysis (

respectively). Heterogeneity in the LR(

) and the LR(

), and LR(

Table 1. Details of patient cohort, study design, and cutoff values.

Authors, year (Ref.)

Patient group

Study design

No. of

patients

Reference

method cutoff,

mg/day

Ratio cutoff

value,

mg/mmol

Quadri et al., 1994 (19)

Pregnant; high-risk obstetrics clinic

Prospective cross-sectional

300

33.9 a

Young et al., 1996 (20)

Pregnant; suspected hypertension

Consecutive recruitment

300

17.0

Robert et al., 1997 (21)

Pregnant; gestational age 22–41 weeks;

hypertension

Consecutive recruitment

300

19.3

Saudan et al., 1997 (22)

Pregnant; hypertension

Consecutive recruitment

100

300

30.0

Ramos et al., 1999 (23)

Pregnant; gestational age 20 weeks; hypertension Prospective cross-sectional

300

56.5

Evans et al., 2000 (24)

Pregnant; investigation for renal disease

Prospective longitudinal

300

33.9

Rodriguez-Thompson et al., 2001 (25) Pregnant; 84% in third trimester

Observational

138

300

21.5

Durnwald and Mercer, 2003 (26)

Pregnant; gestational age 24 weeks; suspected

preeclampsia

Prospective recruitment

220

300

33.9

Al et al., 2004 (27)

Pregnant; new-onset mild hypertension

Retrospective consecutive review 185

300

21.5

Yamasmit et al., 2004 (28)

Pregnant; gestational age 26–42 weeks;

hypertension

Prospective recruitment

300

21.5

Ginsberg et al., 1983 (16)

Adult ambulatory renal clinic

Recruitment not clear

200

22.8

Dyson et al., 1992 (32)

Adult renal transplant clinic

Prospective cross-sectional

148

500

40.0

Chitalia et al., 2001 (34)

Renal clinic; some proteinuria

Prospective cross-sectional

170

250

29.4

Torng et al., 2001 (35)

Adult renal transplant clinic

Consecutive recruitment

289

500

40.0

Ralston et al., 1988 (36)

Adult rheumatology clinic

Consecutive recruitment

102

300

40.0

Mitchell et al., 1993 (37)

Elderly attending outpatient clinic

Recruitment not clear

150

17.1

a All values were converted to SI units.

Clinical Chemistry 51, No. 9, 2005

1581

Fig. 2. Plots of the sensitivities ( A ) and specificities ( B ) reported in

each of the studies compared with the cutoff values used for the

protein:creatinine ratio measurement in each of the patient cohorts

studied.

several factors, including ( a ) variation in water intake and

excretion, ( b ) rate of diuresis, ( c ) exercise, ( d ) recumbency,

and ( e ) diet. The variation may be further exacerbated by

pathologic changes in blood pressure and renal architec-

ture.

An alternative approach that has been proposed, and

used in some clinical situations for many years, is that of

expressing the protein excretion in a random urine collec-

tion as a ratio to the creatinine concentration. It is as-

sumed that both the protein and creatinine excretion rates

are fairly constant during the day, as long as the glomer-

ular filtration rate remains constant, and that the major

reason for changes in the protein concentration in indi-

vidual samples during the day is variation in the amount

of water excreted. To support this proposal, several inves-

tigators have demonstrated a smaller variation in the

protein:creatinine ratio compared with the protein con-

centration alone in urine samples collected throughout

the day. Thus, Newman et al. (17 ) found that the mean

intraindividual variation in the protein:creatinine ratio

was 38.6%, whereas that of the protein excretion was

96.5%. Koopman et al. (14 ) had made a similar observa-

tion.

Several investigators studied the relationship between

the protein:creatinine ratio and 24-h protein excretion.

Ginsberg et al. (16 ) reported a correlation coefficient of

0.972; these authors also studied the variation of this

relationship during the course of 24 h by studying the

ratio and absolute amount of protein excreted in urine

samples from 46 patients collected over timed periods

throughout the day. They found that the relationship

varied by as much as 30% but that during normal daylight

activity—when most random samples are likely to be

collected—the variation was minimal. The greatest differ-

ences were seen during the times when the patients were

most likely to be recumbent. These authors concluded on

the basis of these data that the protein:creatinine ratio of a

spot urine could be used as a reliable indicator of the 24-h

protein excretion. Several investigators have made similar

observations and drawn similar conclusions (30 ) , whereas

others have stated a preference for the first sample

collected after the first morning void (14 , 32 ) . However,

some authors have pointed out that regression analysis

and the reporting of a correlation coefficient indicate the

degree of linear association between the two variables but

do not enable a reliable decision to be made to replace one

with the other (34 ) . Thus, the high degree of association

between the protein:creatinine ratio and the 24-h protein

excretion does not necessarily give reliable information on

whether use of the ratio in a random sample will enable

clinicians to reduce their dependence on the 24-h urine

collection.

The reliability of a test result to enable a clinician to

make a decision and take appropriate action depends on

the context in which the test is used, the additional and

complementary information available, and on the addi-

tional tests that might be required. Thus, a screening test

20% of the samples returned because they were consid-

ered to be incomplete; Chitalia et al. (34 ) in their study

had to discard 10% of the samples received for similar

reasons.

The need for a 24-h collection is a result of the high

degree of variation in the urinary protein concentration

during the course of the day. This precludes the use of a

shorter collection period or the use of a random urine

sample for protein concentration measurements, the latter

of which would be the most practicable. Several authors

have investigated the variation in protein excretion dur-

ing the day and found that values can vary from 100% to

500%. This variation is thought to be attributable to

assessing the amount of protein excretion as well as

doubts about many of the techniques used. However, it is

acknowledged that estimation of urinary protein excre-

tion over a 24-h period is the reference, or gold standard,

method. This approach, however, is considered by many

to be impractical in some circumstances, particularly

in the outpatient setting, because of the difficulties asso-

ciated with obtaining a complete collection. In a study

of elderly patients, Mitchell et al. (37 ) had to discard

Plik z chomika:

Inne pliki z tego folderu:

Inne foldery tego chomika: