Conversion between bromcresol green- and bromcresol purple-measured albumin in renal disease

Catherine M. Clase,1, Michael W. St Pierre2 and David N. Churchill3

1 Division of Nephrology, Dalhousie University, Halifax, NS, 2 Department of Clinical Chemistry, St Joseph's Hospital, Hamilton, ON, and 3 Division of Nephrology, McMaster University, Hamilton, ON, Canada

Abstract

Background. Albumin measured by a bromcresol purple dye-binding assay (AlbBCP) agrees more closely with the gold standard of immunonephelometry than does bromcresol green (AlbBCG) measurement. Both tests are in current clinical use. A method for converting between the two would be useful.

Methods. We measured albumin by bromcresol green and bromcresol purple in 535 patients, 155 of whom had renal disease. We randomly divided data from the patients with renal disease into two equal-sized sets, and used one set to derive, and the remaining set to validate, a regression equation relating the two values.

Results. The relationship AlbBCG=5.5+AlbBCP performed very well in both the renal patient validation set and in the data from 380 unselected in-patients and out-patients. Intraclass correlations for agreement between measured AlbBCG and predicted AlbBCG was 0.98 in both analyses.

Conclusions. The ability to convert between these measurements will be of use in clinical situations where the absolute value of the serum albumin is important, when data from laboratories using different methodologies must be combined, and in the application of the Modification of Diet in Renal Disease formula to estimate glomerular filtration rate in patients whose albumin has been measured by bromcresol purple.

Keywords: albumin; bromcresol green; bromcresol purple; conversion; immunonephelometry; measurements

Introduction

Albumin has been shown to be predictive of survival [15] and hospitalization [68] both in dialysis and in renal transplant patients. In clinical practice, albumin is measured by automated techniques employing one of two dye-binding assays: bromcresol green (BCG) and bromcresol purple (BCP). Systematic differences between these methods have long been recognized [9] and recently confirmed [10,11]. Albumin was measured by BCG in both of the studies of prognosis that specified the method [1,8]. While BCG remains the dominant methodology, a significant number of laboratories now use BCP: 18% of patients in a 1997 US national random sample of peritoneal dialysis patients had albumin measured by BCP [12].

In the management of an individual patient with longitudinal data from the same laboratory, which albumin assay is used may be of little importance. However, when the absolute value of the serum albumin matters, appreciation of the methodology used and the ability to convert between methods will be helpful. Such situations include clinical and quality assurance investigations in which data from more than one laboratory must be combined (albumin is a Health Care Financing Administration quality assurance criterion [12]), and consideration of an individual patient's nutritional status when deciding whether to recommend initiation of dialysis or whether dialysis is adequate [13].

To determine whether interconversion between results derived from the different methodologies is feasible and, if so, to derive and validate a conversion formula, we investigated the relationship between BCG- and BCP-measured albumin in patients with a variety of renal problems.

Subjects and methods

Patients
Patients were in-patients and out-patients managed at a tertiary-care institution (St Joseph's Hospital, Hamilton) in June 1994. Patients were unselected out-patients, unselected in-patients, haemodialysis (HD) patients, peritoneal dialysis (PD) patients, renal transplant recipients, and renal out-patients. Consecutive samples were analysed in duplicate by BCG (1.5 min reaction) and BCP methodology (both Boehringer Mannheim, Indianapolis, IN). Both methods were run on a Hitachi 717 autoanalyser. The calibration standard for both methods was Precical human serum (Hoffman-La Roche, Ont): both assays were calibrated to the same numerical value (39 g/l) from the same standard.

Statistical analysis
Continuous variables were compared by unpaired t-tests and one-way analysis of variance (ANOVA). Linear regression and Pearson correlation were used to examine the relationship between albumin measured by BCG (AlbBCG) with albumin measured by BCG (AlbBCP) (Statistica, Statsoft Inc., Tulsa, OK). Data from renal patients were divided randomly into a derivation set and a validation set. Using the derivation set, a linear regression equation describing the relationship between the two methods was developed, and tested against the renal validation set, and against the data from non-renal patients. In the assessment of validity, the intraclass correlation coefficient (ICC) was used to express agreement between calculated and measured AlbBCG. ICC resembles the R2 value derived from Pearson correlation: it is a measure on a 0–1 scale of the proportion of variation in one quantity explained by differences in a second quantity. Unlike the Pearson correlation, it refers to goodness-of-fit to the line of identity (y=x), rather than to the best linear fit through the data, and is therefore preferred in situations where absolute values are of importance and the two variables being compared are expressed in the same units (i.e. when the question is one of agreement, rather than simply correlation). ANOVA components for ICC was performed with BMDP 8V (SPSS Inc., Chicago, IL).

Results

Table 1Go summarizes the data distributions for the 535 samples in six clinical categories. As expected, values of in-patients were lower than those of out-patients (AlbBCG 33 g/l vs 40 g/l, P<0.001) and values for peritoneal dialysis patients lower than haemodialysis patients (AlbBCG 31 g/l vs 38 g/l, P<0.001). The difference in serum albumin between the two methods was 5.5±1.4 g/l overall. This value did not differ across the six clinical categories (ANOVA, P=0.79) and was also similar when renal (HD, PD, transplant and renal clinic) were compared with non-renal patients (t-test, P=0.47).


View this table:
[in this window]
[in a new window]
 
Table 1. Serum albumin by methodology and clinical group

 
Linear regression with AlbBCG as dependent and AlbBCP as independent variables was performed. A very close linear relationship was observed (Table 2Go), with 96% of variance in AlbBCG being accounted for by AlbBCP overall (R2 of 0.96). There was little difference between the clinical groups: R2 varied between 0.87 and 0.97.


View this table:
[in this window]
[in a new window]
 
Table 2. Linear regression: relationship between BCG- and BCP-measured albumin, renal patients only

 
For the prediction equation, we developed a regression equation for the interconversion of AlbBCG and AlbBCP by dividing the data from the 155 patients with renal disease randomly into two groups (a derivation set and a validation set). The least-squares regression for the relationship from the derivation set (n=68) was AlbBCG=7.2+0.98 (AlbBCP) (P<0.001).

In the validation set, two interconversion approaches were evaluated: the use of the formula above; and (since the observed slope of the line was close to unity) simple addition of the mean difference in values obtained by each method (5.5 g/l in the derivation set) to AlbBCP (i.e. the line AlbBCG=5.5+AlbBCP). Agreement for AlbBCG predicted by each method with the true measured AlbBCG was assessed by ICC. In the validation set, agreement for both methods was excellent, at ICC of 0.95 for the regression approach, and 0.98 for the simple method.

Because the mean difference and the linear relationship between the variables did not differ greatly for renal and non-renal patients, we also examined the performance of both the regression formula and the simple method in the non-renal population and found agreement in the same range as that observed with renal patients at 0.96 and 0.98 respectively. Figure 1Go shows the extent of agreement for the simple method (AlbBCG=5.5+AlbBCP) for renal and non-renal patients.



View larger version (16K):
[in this window]
[in a new window]
 
Fig 1. Relationship between measured AlbuminBCG and predicted AlbuminBCG (5.5+AlbuminBCP).

 

Discussion

BCG methods are subject to non-specific interference from binding to non-albumin proteins [14], whereas BCP is more specific [15]. These differences may be minimized, but not eliminated, by the use of a rapid-reaction technique in which absorbance readings are made after short incubation times, as in our data [16]. Using a long-reaction-time BCG method, a difference of 11 g/l was noted in normal healthy subjects between BCG-measured and BCP-measured albumin, though no comparison with a gold standard was provided [10]. With a short-reaction-time methodology, mean overestimations of 7 g/l for non-renal patients and 8 g/l in renal patients were noted for BCG-measured albumin compared with the criterion measure of electroimmunoassay (EIA) [9].

BCP is not subject to cross-reactivity with other non-albumin proteins. In non-dialysis patients, the mean difference between BCP albumin and that measured by EIA was 0.6 g/l [9]. However, this assay is not without problems. Interference by bilirubin was noted in one in vitro study [17]. In dialysis patients, BCP underestimated EIA-measured albumin by 7 g/l [9] and immunonephelometric-measured albumin by 3 g/l [18]. In renal transplant recipients, BCP underestimated albumin measured by immunoturbidimetry by 6 g/l [19]. Competitive binding by a non-dialysable ligand was thought to explain these results [18]. However, Beyer et al. [20] suggested that the underestimation by BCP may be confined to patients on haemodialysis (3 g/l, BCP cf. immunoturbidimetry), since it was not observed in undialysed patients with chronic renal failure and those treated with peritoneal dialysis.

Joseph et al. [11] compared BCG and BCP methods against the gold standard of nephelometry in 53 haemodialysis and 23 peritoneal dialysis patients. With a short-reaction time BCG method, BCG showed good agreement with nephelometry for both groups. BCP, however, underestimated nephelometry consistently, a difference that was more marked in patients on haemodialysis than peritoneal dialysis, as in the study by Beyer et al. [20].

Where Joseph found similar values for BCG and nephelometry, a mean underestimation of 5.2 g/l (weighted mean, HD and PD combined) by BCP compared with nephelometry, and a mean underestimation of 6.5 g/l for BCP compared with BCG, Blagg et al. [10] (in 235 PD and HD patients) found that BCP results (mean 33 g/l) corresponded well with nephelometry (mean 33 g/l): agreement between methods was measured by Pearson correlation coefficient with r2=0.84. A difference between BCG and BCP methods of 5 g/l was observed (mean BCG-measured albumin 38 g/l).

A more recent study compared both BCG and BCP methods with the gold standard of immunoturbidimetry in 143 haemodialysis patients and 49 non-renal patients [21]. In this work, BCG tended to overestimate albumin, especially in hypoalbuminaemia, and BCP gave unbiased results in renal patients (though some overestimation by BCP in non-renal patients was noted). In renal patients, BCG-measured albumin was higher than BCP-measured albumin by 3.5 g/l. This value is slightly lower than our observation, but in the same range. Direct graphical comparison of BCG with BCP were not provided in this study.

Whether BCG results in overestimation, BCP in underestimation, or both, cannot be determined from our work because of lack of a gold standard, and the studies cited above provide conflicting results, with Joseph et al. [11] suggesting that BCG is closer to the gold standard in dialysis patients, and Blagg et al. [10] and Carfray et al. [21] suggesting that BCP is superior. Differences in the gold standard measurement in these studies probably account for the differences between these results. It is not likely that a single albumin methodology will be accepted as the ultimate criterion method in the near future, and even less likely that such a method will soon be in clinical use. The practical question for clinicians and researchers is generally the comparison of results from patients whose albumin has been determined by BCG with those measured by BCP methods.

In addressing this question, our study and the studies cited above find a consistent difference between BCG and BCP methodologies of similar magnitude across studies: 5.5 g/l (this work), 6.5 g/l (Joseph et al. [11]), 5 g/l (Blagg et al. [10]), 3.5 g/l (Carfray et al. [21]). This suggests that the practical question of interconversion between the two methodologies in current clinical use may be answerable. Joseph provides regression equations to permit interconversion between the three different methods. However, this work did not use a split-sample derivation and validation methodology. Graphical data from this study show that in the clinically-important range, a simple additive correction to BCP-measured albumin may have been an alternative reasonable approach; but this approach was not tested or compared with the regression correction in this study [11]. We considered a regression approach and a simpler formula. We validated this formula in renal patients and found it performed equally well in the non-renal population. In both these validation sets, the addition of 5.5 g/l to the BCP-measured albumin to predict BCG-measured albumin performs slightly better than the more complicated regression approach. Because both derivation and validation sets compared albumin measured by exactly the same two methodologies, one would expect a slight reduction in agreement with the approximation, in applying this approach to other populations, if the details of either assay differed from those described above. In particular, BCG assays with a long reaction time may have different properties.

We did not observe any differences between haemodialysis and other renal patients, or between renal and unselected patients, in either the mean difference between BCG- and BCP-measured values (Table 1Go), or the linear relationship between these variables (Table 2Go). Nor did we notice any bias at low levels of albumin, though patients with hypoalbuminaemia were well represented in this work (see Figure 1Go). This led to our decision to pool data for the different renal patients in deriving an interconversion formula. We are unable to account for the difference between our findings and those of Joseph, who found that the differences between methods were more marked in HD patients than in PD patients [11].

We recognize that the lack of a criterion measure is a limitation of our study. However, our purpose was to derive a means of converting between the two values, rather than to assist clinicians or laboratory scientists in the selection of one methodology over another. Both these methods are in widespread clinical use, and though recommendations for the abandonment of BCG have been made [22], this opinion is not universal [23]. The technical difficulties of conversion and the need for human control sera for BCP will probably mean that for some years at least we will be faced in clinical and research situations with data from both sources.

One application of this interconversion would be in the calculation of glomerular filtration rate (GFR) by the Modification of Diet in Renal Disease Study Group (MDRD) formula [24] in data sets containing albumin measured by different methodologies. The contribution of this approximation in increasing the error associated with the MDRD formula should be minimal. A numerical example illustrates this point: for a 70-year-old white female whose creatinine is 250 µmol/l, urea 20 mmol/l and albumin by BCP is 25 g/l, application of the MDRD formula without albumin correction would estimate GFR at 14.7 ml/ min/1.73 m2, whereas application of the 5.5 g/l correction would yield a more accurate 15.6 ml/min/1.73 m2. The magnitude of this 6% difference is small in absolute terms (0.9 ml/min/1.73 m2), and is not clinically significant. In clinical care it is therefore reasonable to ignore the method of albumin measurement when applying the MDRD formula, whereas researchers may be concerned to reduce error as far as possible by using the albumin correction factor suggested above.

In summary, we feel that awareness of systematic differences that occur when patients are evaluated by different methodologies is important [1012,21,25] and hope that the ability to convert between the two results will be helpful when data derived by the two different methods must be combined or compared.

Acknowledgments

We would like to thank Ms T. Coffey for secretarial assistance. Our colleagues and anonymous reviewers provided much helpful feedback on this work.

Notes

Correspondence and offprint requests to: Dr Catherine M. Clase, Assistant Professor, Room 5088, Dickson Building, 5820 University Avenue, Halifax, Nova Scotia, B3H 1V8, Canada. Back

References

  1. Churchill DN, Taylor DW, Keshaviah PR, for the Canada–USA (CANUSA) Peritoneal Dialysis Study Group. Adequacy of dialysis and nutrition in continuous peritoneal dialysis: association with clinical outcomes. J Am Soc Nephrol1996; 7: 198–207[Abstract]
  2. Guijarro C, Massy ZA, Wiederkehr MR, Ma JZ, Kasiske BL. Serum albumin and mortality after renal transplantation. Am J Kidney Dis1996; 27: 117–123[ISI][Medline]
  3. Foley RN, Parfrey PS, Harnett JD et al. Hypoalbuminaemia, cardiac morbidity and mortality in end-stage renal disease. J Am Soc Nephrol1996; 7: 728–736[Abstract]
  4. Lowrie EG, Lew NL. Death risk in hemodialysis patients: the predictive value of commonly measured variables and an evaluation of death rate differences between facilities. Am J Kidney Dis1990; 15: 458–482[ISI][Medline]
  5. Owen WF Jr, Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio and serum albumin concentration as predictors of mortality in patients undergoing hemodialysis. N Engl J Med1993; 329: 1001–1006[Abstract/Free Full Text]
  6. Blake PG, Flowerdew RM, Blake RM, Oreopoulos DG. Serum albumin in patients on continuous ambulatory peritoneal dialysis—predictors and correlations with outcomes. J Am Soc Nephrol1993; 3: 1501–1507[Abstract]
  7. Churchill DN, Taylor DW, Cook RJ et al. Canadian hemodialysis morbidity study. Am J Kidney Dis1992; 19: 214–234[ISI][Medline]
  8. Ikizler TA, Wingard RL, Harvell J, Shyr Y, Hakim RM. Association of morbidity with markers of nutrition and inflammation in chronic hemodialysis patients. Kidney Int1999; 55: 1945–1951[ISI][Medline]
  9. Wells FE, Addison GM, Postlethwaite RJ. Albumin analysis in serum of haemodialysis patients: discrepancies between bromocresol purple, bromocresol green and electroimmunoassay. Ann Clin Biochem1985; 22: 304–309[ISI][Medline]
  10. Blagg CR, Liedtke RJ, Batjer JD et al. Serum albumin concentration-related Health Care Financing Administration quality assurance criterion is method-dependent: revision is necessary. Am J Kidney Dis1993; 21: 138–144[ISI][Medline]
  11. Joseph R, Tria L, Mossey RT et al. Comparison of methods for measuring albumin in peritoneal dialysis and hemodialysis patients. Am J Kidney Dis1996; 27: 566–572[ISI][Medline]
  12. Frankenfeld DL, Prowant BF, Flanigan MJ et al. Trends in clinical indicators of care for adult peritoneal dialysis patients in the United States from 1995 to 1997. Kidney Int1999; 55: 1998–2010[ISI][Medline]
  13. NKF DOQI Clinical Practice Guidelines for Peritoneal Dialysis Adequacy. National Kidney Foundation, New York, 1997
  14. Webster D, Bignell AH, Attwood EC. An assessment of the suitability of bromcresol green for the determination of serum albumin. Clin Chim Acta1974; 53: 101–108[ISI][Medline]
  15. Gustafsson JE. Improved specificity of serum albumin determination and estimation of ‘acute phase reactants’ by use of the bromcresol green reaction. Clin Chem1976; 22: 616–622[Abstract/Free Full Text]
  16. Corcoran RM, Durnan SM. Albumin determination by a modified bromcresol green method. Clin Chem1977; 23: 765–766[ISI][Medline]
  17. Bush V, Reed RG. Bromcresol purple dye-binding methods underestimate albumin that is carrying covalently bound bilirubin. Clin Chem1987; 33: 821–823[Abstract/Free Full Text]
  18. Mabuchi H, Nakahashi H. Underestimation of serum albumin by the bromcresol purple method and a major endogenous ligand in uremia. Clin Chim Acta1987; 167: 89–96[ISI][Medline]
  19. Maguire GA, Price CP. Bromcresol purple method for serum albumin gives falsely low values in patients with renal insufficiency. Clin Chim Acta1986; 155: 83–87[ISI][Medline]
  20. Beyer C, Boekhout M, van Iperen H. Bromcresol purple dye-binding and immunoturbidimetry for albumin measurement in plasma or serum of patients with renal failure. Clin Chem1994; 40: 844–845[Free Full Text]
  21. Carfray A, Patel K, Whitaker P et al. Albumin as an outcome measure in haemodialysis in patients: the effect of variation in assay method. Nephrol Dial Transplant2000; 15: 1819–1822[Abstract/Free Full Text]
  22. Duggan J, Duggan PF. Albumin by bromcresol green—a case of laboratory conservatism. Clin Chem1982; 28: 1407–1408[Free Full Text]
  23. McGinlay JM, Payne RB. Serum albumin by dye-binding: bromcresol green or bromcresol purple? The case for conservatism. Ann Clin Biochem1988; 25: 417–421[ISI][Medline]
  24. Levey AS, Bosch JP, Lewis JB et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med1999; 130: 461–470[Abstract/Free Full Text]
  25. Wick MJ, Wilkens K, Moritz J. Albumin testing methods differ: implications for the dialysis patient. Dial Transplant1994; 23: 282[ISI]
Received for publication: 9. 9.00
Revision received 18. 4.01.