Biological and analytical variation of commonly determined blood constituents in healthy blood donors

179

Clinica Chimica Acta, ‘70 (1976) 179-189 0 Elsevier Scientific Publishing Company,

Amsterdam

- Printed in The Netherlands

CCA 7934

BIOLOGICAL AND ANALYTICAL V~IAT~ON OF COMMONLY DETERMINED BLOOD CONSTITUENTS IN HEALTHY BLOOD DONORS

F.V. FLYNN w, K.A.J. PIPER “, P. GARCIA-WEBB and M.J.R. HEALY b

G**, K. MCPHERSON b

a Department of Chemical Pathology, University College Hospital, Gower Street WC1 E 6AlJ and b Division of Compu ting and Statistics, Medical Research Council Clinical Research Centre, Northwick Park Hospital, Harrow, Middlesex (U.K.) (Received

January 23,1976)

Summary The relative ~ont~butions of analytical error and non-systematic biological variation to the reference range for 19 commonly-determined blood chemistry values have been estimated during the course of studying 1000 healthy blood donors. Estimates of non-sys~matic biological variations are arrived at by dete~~ing the variation found in donors matched for factors known to affect blood chemistry such as age and sex, and deducting the within-batch analytical error which applied. Comparison of the within-bath and between-batch analytical precision with the biological variation showed that the percentage increases in the normal range attributable to between-batch analytical error varies between 1 and 29%. This contribution is particularly large in the case of the electrolytes and amounts to no less than 29% in the case of calcium. Apart from wed-know relationships arem~kable lack of correlation between the concentration of the different constituents in health is demonstrated.

Introduction -A study of a thousand blood donors was undertaken with the primary objective of assessing the effeits of age, sex and other factors upon the levels of bio-, chemical constituents of the blood in healthy individuals. Seventeen constituents were measured and their statistical distributions within age/sex groupings have been described in an earlier paper [ 1 f . The present paper is concerned with the * To whom correspondence should be addressed. * * Present address: Department of Clinical Biochemistry, Australia. 6006. Australia.

Perth Medical Centre. Shenton Park, Western

180

“random” variability of the seventeen constituents, i.e. that which is not associated with systematic factors such as sex and age. The variation among values of a given biochemical constituent relating to a number of different individuals can be ascribed to two groups of causes: “analytical”, in that the values recorded in the laboratory will differ to some extent from those which would theoretically be obtained with perfect instrumentation and technique, and “biological”, in that those “true” values for the constituent would differ from one individual to another. Both groups of causes are complex in nature. The biological causes of variation can be divided into systematic factors such as sex, age, blood group and time of day, and random causes which cannot be individually identified. The first of these sets of causes of biological variations will not be considered further in this paper but will be the subject of another report. The second will include that part of the within-subject variability [2,3] not associated with systematic effects such as those of time of day and time since last meal. We are unable to study this within-subject variability separately since we have only a single value for each subject. The analytical variability will usually be smaller between specimens analysed on the same occasion than between specimens analysed on different occasions. An important distinction between the two sources of variability dealt with here is that it is at least in principle possible to reduce analytical variability by careful attention to laboratory technique, whereas random biological variability is an inherent property of the population studied and could only be reduced by recognising and allowing for some further systematic cause of variation. Materials and Methods Details of the blood donors, the collection and handling of the samples,the chemical analyses and the initial statistical screening of the results will be found in the previous paper [l] . There were approximately 50 donors of each sex in each of 10 age-groups between 18 and 65 years of age. The samples were analysed as part of the routine laboratory procedure in the Department of Chemical Pathology, University College Hospital. Donor samples were analysed in batches of 15, together with three samples from a serum pool and a single sample from a commercial lyophilized quality control serum (Hyland Division, Travenol Laboratories Ltd.) so that analytical performance could be monitored. The routine laboratory results were additionally subject to quality control based on an “average-of-normals” system [ 4,5] . For statistical analysis, certain of the readings were subjected to the logarithmic transformations which were shown earlier [l] to stabilise the variances and to bring the distributions closer to Gaussian form. The full list of constituents, with the units and transformations used, is given in Table I. Results Analytical

variability

The specimens were analysed in 81 batches, and thus 81 trios of serum pool values were available for estimating the within-batch variability for each constituent. The 81 ranges for each constituent were plotted on a set of control

181 TABLE I THE VARIABLES

ANALYSED

AND THEIR UNITS

Albumin (g/l00 ml) log (allsallne phosphatase (KA units) -2) Calcium (mg/lOO ml) CO2 capacity (mmol/l) Chloride (mmol/l) log (cholesterol (mg/lOO ml)) log (creatinine (mgf100 ml)) Globulin (g/100 ml) log (glucose (mg/lOO ml)) log (glutamic oxaloacetic transamlnase (1.U.R 26’C) -4) Ions difference * (mmol/l) log (iron (fig/100 ml) +30) Phosphate (inorganic) (mg/lOO ml) Potassium (mmolfl) log (protein-bound iodine &g/100 ml) -2) Sodium (mmol/l) Total protein (g/100 ml) log (urea (mg/lOO ml) +lO) log (urate (mg/lOO ml) +4) * Ions difference = sodium + potassium -chloride

- CO2 capacity. All iogarlthms are to base 10.

charts. These showed that no substantial trends in within-batch precision occurred during the study period, and that this precision can be adequately described by the standard deviations given in Table II. The single sample of commercial quality control serum that was included in each batch provided 81 readings for each constituent from which the betweenbatch precision could be assessed. Plotting consecutive values on control charts showed that the 81 readings were in general by no means randomly distributed. TABLE II WITHIN-BATCH

PRECISION

(STANDARD

DEVIATIONS

WITH 162 d.f.)

Items marked * have been transformed to logarithms. Constituent

l

Albumin Allmllne phosphatase Calcium CO2 capacity Chloride Cholesterol Creatinine Globulin Glucose Glutamic oxaloacetic transaminase Ions difference IrOll

* * *

Phosphate (inorganic) POtaSsium Protein-bound iodine Sodium Total protein Urea Urate

S.D. 0.047 0.0193 0.078 0.302 0.626 0.0096 0.0076 0.064 0.0063 0.0286 0.89 0.0099 0.091 0.047 0.022 0.649 0.044 0.0092 0.0029

Q

-1

-2 CiSURl -3

-4

-5

Phosphorus kvsl

5.0

*

_ .

a.0

0

t

10

I

2u

1 30

1 40

1 50

I

1

60

70

1

80

Batch Fig_ l.(a) Cumulative sum &art for 81 consecutive determinations of phosphate on the commercial quality coutml serum Sneluded w&h each batch of donor specimens. &b) Rot of the IeveS of phosahste found on the commercial quality control serum included with eauh batch of donor specfmens.

183

A cumulative sum chart [6] for the 81 phosphate values is shown in Fig. la as an example, and the abrupt changes in slope make it apparent that there was a noticeable change in the value ascribed to the control serum about halfway through the study. The actual values are plotted in Fig. lb with the mean levels corresponding to the line segments on the cusum chart. The apparent jump amounts to an increase of 0.23 mg/lOO ml. A computer programme was used to scan the cusum charts for changes in slope by a moving average technique. At each point on the cusum, sufficiently away from the start and finish, the average of the 10 preceding and the 10 following points was calculated. As long as these averages continually increased or continually decreased, the cusum was assumed to have a steady slope; if the trend of the averages changed, the cusum was assumed to have changed slope, and the point of change was located at the highest or lowest point on the cusum within 5 points on either side of the current point. The indicated trends on the cusum in Fig. 1 were arrived at by joining points found in this way. The results of this analysis are shown in Table III. This gives the standard deviations of the 81 readings treated as if they were a random sample, the number of indicated jumps and the range they covered, and a second standard deviation for each constituent, based on the apparently random sections between the jumps. The reduction in standard deviation varies from 0% to about 15%. These “inter-jump” between-batch standard deviations are also expressed in the table as multiples of the within-batch standard deviations from Table II. As

TABLE III BETWEEN-BATCH Items marked

l

PRECISION

have been transformed to logarithms.

Constituent

l

l

* l

*

*

l

* l

S.D. of Sl values

No. of jumps

Range of means

S.D. between

S.D. between jumps

jumps

S.D. within batches

Albumin Alkaline phosphatase Calcium CO2 capacity Chloride Cholesterol Creatinine Globulin Glucose Glutamic oxsloacetic

0.086 0.038 0.262 1.01 1.18 0.021 0.0178 0.134 0.022

2 4 4 2 7 3 4 3 4

3.803.89 1.171.24 9.129.43 27.05-27.95 97.8 -99.5 2.232.26 0.011-0.028 2.422.65 2.312.35

0.079 0.036 0.233 0.928 1.11 0.018 0.0164 0.123 0.019

1.68 1.87 2.98 3.07 1.11 1.82 2.16 1.92 3.02

transaminase Ions difference Iron Phosphate (inorganic) Potassium Protein-bound iodine Sodium Total protein Urea Urate

0.033 1.48 0.016 0.235 0.101 0.036 0.976 0.097 0.0093 0.0071

6 6 3 1 6 2 1 4 1 4

1.711.76 12.9 -14.5 2.072.09 5.535.76 4.604.79 0.620.64 134.4-135.1 6.336.42 2.182.19 1.023-1.029

0.029 1.48 0.014 0.206 0.097 0.034 0.926 0.091 0.0079 0.0067

1.01 1.66 1.41 2.25 2.06 1.66 1.68 2.06 0.869 2.31

184 TABLE IV VARIABILITY COLLECTION,

AMONG DONORS MATCHED FOR AGE, SEX, MENSTRUAL STATUS, DATE OF TIME OF DAY AND ABO BLOOD GROUP (STANDARD DEVIATIONS WITH 132 cl.f.1

Items marked * have been transformed to logarithms Constituent

*

* * * *

*

*

* *

IncIuding withinbatch variability

Excluding witbinbatch variability

Albumin Alkaline phosphatase Calcium CO2 capacity Chloride Cholesterol Creatinhxe GIobulin Glucose

0.20 0.136 0.25 1.52 1.48 0.077 0.039 0.26 0.064

0.19 0.135 0.24 1.49 1.34 0.016 0.038 0.25 0.064

Glutamic oxaloacetic transaminase Ions difference Iron Phosphate (inorganic) Potassium Protein-bound iodine Sodium Total protein Urea Urate

0.118 1.05 0.101 0.47 0.22 0.096 1.16 0.33 0.059 0.041

0.114 0.56 0.101 0.46 0.22 0.093 1.01 0.33 0.058 0.041

is commonly constituents.

found, the ratios are rather consistent, averaging 1.96 over alithe

The systematic factors that were expected to influence the results most were age, sex, time of day, ABO blood group and, for females, menopausal status. In the total sample it was possible to find 92 pairs, 14 groups of 3, and 4 groups of 4, which agreed in these aspects (age matched to within a decade) and whose samples were analysed in the same batch. F’rom these could be calculated a variance estimate with 132 degrees of freedom which is due entirely to nonsystematic biological factors includes wit~n-subject variation and withinbatch laboratory error. By using the results from Table II, estimates of true random biological variability are obtained. The corresponding standard deviations are shown in Table IV. We also give, in Table V, the correlation coefficients based on the same matched subjects. Discussion The principal objective of the survey was to improve the assessment of normal ranges and the results are best discussed in this context. In particular, the standard deviations in Table IV indicate the irreducible minimum width of the normal ranges; these could only be further reduced if additional systematic factors influencing serum levels were to be discovered. These figures should also

1.00

1.00 -0.04 -0.06 -0.22 -&OS 0.00 -0.30 4.10 -0.12 -0.02 -0.05 1.00 0.02 1.00 -0.02-0.06 1.00 0.02 0.16 0.14 0.04 0.13 0.15 0.14 0.04 0.02 0.03 0.18 0.02 -0.07 -0.02 -0.08 0.03 0.03-0.18 0.02 0.03 0.06

* Correlationereganiedaeeignificant. ** Con-eletionecelculatedafterlogerithmictranaformation of results.

0.06-0.01 1.00 -0.07 0.12--o-16 1.00 0.07-0.08 0.130.00 1.00 --Q.lO 0.00 0.020.18 0.09 1.00

1.00 -0.12 1.00 0.15 0.02 1.00 0.05 0.15-0.09 1.00 -0.05-0.10 0.13-0.06 1.00 -0.09-0.13 0.01 0.09 0.31* 1.00 0.02 0.07 0.15-0.14-0.12 -0.02 1.00

DATEOFCOLLECTION.TIMEOFDAYANDABOBLOODGROUP

-0.20-0.04 0.05 0.04-0.02 0.40' -0.10-0.11~.13 0.35* 0.16 0.17 0.16 0.08 0.01 0.03-0.07 0.80* 0.04 -0.30 0.22_ 0.13 0.09 0.02 -0.07 -0.02-0.05-0.04 0.05 -0.08 0.08 0.23 0.12 0.16 0.01 0.05 -0.04 0.11 0.12 0.05

1.00 [email protected]* -0.14 -0.06 0.07 -0.19 0.06 -0.36* 0.17 0.06 0.20 -0.06

MATCHEDFORAGE.SEX,MENSTRUALSTATUS,

-0.08 1.00 0.11 1.00 0.34* -Q.o2 0.03 0.16 0.14-0.23 Chloride -0.22 Cholesterol** 0.08 0.03 0.14 Creatinine** --II.06 0.02-0.06 Globulin 0.02 -0.09 0.24 0.06 0.03-0.11 Glucoee'* GOT** 0.08 0.06 0.11 Ionsdifference 0.26 -0.16 0.17 Iron** -0.01 0.07 0.01 0.13 0.03 0.05 PhOSPbate 0.08 0.02 0.12 Potaeeium Protein-bound -0.01 -0.13 0.01 iodine** 0.09 0.05 0.05 Sodium 0.61* -0.13 0.39* Totalprotein 0.08 0.04 -0.03 Urea** 0.23 -0.01 0.21 K&ate*+

Albumin AlkalbIe phoephataee*; Calcium co2 CaPacitY

CORRELATIONSAMONGDONORS

TABLEV

186 TABLE

VI

PERCENTAGE VARIATION Items marked

INCREASE

* have been transformed

Constituent

*

l

* * *

l

l

l l

IN NORMAL

Albumin AIkaIine phosphatase Calcium CO2 capacity Chloride Cholesterol Creatinine Globulin Glucose Glutamic oxaloacetic transaminase Ions difference Iron Phosphate (inorganic) Potassium Protein-bound iodine Sodium Total protein Urea Urate

RANGE

DUE

TO WITHIN-BATCH

AND BETWEEN-BATCH

to logarithms.

Within-batch

Between-batch

(96)

(%)

3 1 3 1 6 1 2 3 0

6 3 29 16 17 3 8 9 5

3 17 0 2 2 2 8 1 1 0

1 34 1 9 8 4 18 3 0 1

be fairly independent of the particular analytical methods used. To arrive at practical normal ranges, both within- and between-batch analytical variability must be allowed for. The importance of these two kinds of variability in the present context can be assessed from Table VI, which shows the percentage increase in the normal range due to allowing first for withinbatch and then for between-batch variation. It will be seen that the first of these is quite small; apart from ions difference, in which four analyses are combined, the worst case is sodium with an increase of 8%. It is therefore apparent that there is little scope for narrowing the normal range by refining the withinbatch precision by better laboratory technique. The position is different where between-batch variability is concerned. This contributes noticeably to the width of the normal range of several constituents, in the worst case, calcium, to the extent of 29%. These figures seem to us to be a cause for concern. The whole purpose of including a set of calibration standards in each batch is to eliminate between-batch variability, and it appears that this purpose is not being adequately fulfilled by the routine methods commonly in use. It is also disturbing to find that detectable changes of level seem to have occurred in several constituents despite the imposition of careful quality control. We cannot ascribe these jumps with certainty to a specific cause, but we have noted that constituents sharing the same calibration standards often showed jumps on or near the same date. This suggests that some of the jumps at least were associated with the introduction of new batches of calibration standard material. The correlations in Table V deserve comment. Even in the absence of any

real correlation, several‘significant’ coefficients are to be expected by chance in a table of this size. A ~apbic~ method 171 suggeststhat only c~fficien~ numerically greater than 0.30 need to be treated as real; there are only 9 of these and the highest of them reflect known functional relationshipsin the proteins. The remaining seven relate to the “biological” correlations between CO2 capacity, chloride and sodium and between total protein and albuminwith calcium. The remarkable feature of Table V is thus the general absence of correlation between serum constituents. It seems to fallow that the known tendency of certain constituents such as urea and creatinine tu rise and fall together during the course of disease must be an effect of the disease process and not merely an exaggerationof a tendency present in a state of health. It should be noted that the correlationsin Table V relate to subjects matched TABLE VII COMPARISON WITH RESULTS OF OTHER WORKERS fi) Within-batch precisfon fS.D.) Gilbert f31 Albumin Calcium CO2 capacity

0.33

ChiOIiCk

Phosphate Potaszdum So&urn Total protein

0.12 2,45

WiUiams et al. [91

Authors Table II

0.07 0.18 0.6 0.7 0.06 0.07 0.9 0.11

0.047 0.078 0.302 0,626 0.091 0.047 0,549 0.044

(ii) Between-batch precision (S.D.)

Albumin Calcium CO2 capacity Chloride Phosphate Potassium Sodium Total prokin

Harris et al. f.~Ol

Authors, OW?Ydl

Authors, between jumps

0.14 0.264 O&6 1.0 0,x7 0.059 I.4 0.21

0.072 0.240 0.964 1.0 0.217 0.089 0.806 0.086

0.063 0.220 0.877 0.917 0.184 0.085 0.744 0.079

(iii) Biological variability-non-systematic

Albumin Calcium CO2 capacity chloride Phosphate Potassium Sodium Total protein

(S.D.)

Ha&s et al. ilO& Table 3

Authors, Table IV

fIarris et aL flOl, Table IV

0.160 0.172 1.14 3.44 0.259 0.208 0 0.196

0.19 0.24 1.49 1.34 0.46 0.22 X.01 0.33

0.264 0.284 1.20 1.21 a._&78 1.12 0.396

for age, sex and other factors. This matching is important; if, for example, two co~~ituents tend to be higher in men than in women, ar in older than in younger subjects, correlations calculated from samples containing both sexes or a range of ages can be quite misleading. Finally, Table VII shows a comparison between our results and those of other workers, For those constituent where ~~sformations were used by US, direct comparison of standard deviations even when appropriately converted is not reliable. Hence attention is confined to those constituents not transformed. The results of other workers have been chosen as conforming most closely to our analytical methods although exact correspondence is not to be expected. It can be seen that our within-batch precisions are mostly smaller than others reported and in some cases, particularly calcium and total protein, markedly so. The results from [S] are average figures from over 4000 laborato~es and those from f93 and f 10 J from a single laboratory. The between-batch standard deviations are on the whole comp~ble with [ fOf . The comparison of biological variation is a little less straightforward for the figures are strictly withinperson (with samples taken at the same time of day) in Table III of [lo] and between unmatched subjects in Table IV of [lo). Hence our biological variations of matched subjects, like people analysed in the same batch, would be expected to be roughly between the two which in most cases they are.

We wish to thank the Director, Dr. T.E. Clegborn, and the staff of the North London Centre of the National Blood Transfusion Service for enabling us to undertake this investigation. We also wish to thank the blood donors whose collaboration made this work possible and the Department of Health and Social Security for financial support Appendix S.I. units

This work was done before the general introductive of S.I. units, and in particular the constants in the logarithmic transformations {Table I) were chosen to be convenient whole numbers when expressed in traditional units. If necessary results can be t~sfo~ed to S.I. units as follows: 1. The standard deviations of untransformed variables are m~tipli~ by the appropriate conversion factors. 2. The standard deviations of transformed variables remain unchanged. However, any additive constants in the transformation formulae are multiplied by the appropriate conversion factors before logarithms are taken. 3. The correlation coefficients remain unchanged. References X Flynn, F.V., Piper, K.A.J.. (&u&-Webb, P.. McPherson, K. and He&y, MJ.R. 62.163-171 2 Cotlove, E., Harris, E.K. md Williams, G.Z. (1970) Clin. Chem. 16,102~1032

(1974) Cfin. Chim. Acta

189 3 Statlend. B.E.. Winkel. P. and Bokelund. I-I. (1973) Clin. Chem. 19.1374-1379 4 6 6 7 8 9 10

Hoffmann. R.G. end Weid. M.E. (1966) Am. J. Clin. Pathol. 43,134-141 Whitby, L.G.. Mitchell, F.L. end Moss. D.W. (1967) Adv. Clin. Chem. 10.66-166 Woodward. R.H. end Go1drmith.P.L. (1964) Cumulative sum techniques. Oliver end Boyd. Edinburgh Hills, M. (1969) Biometrike 66,24Q-263 Gilbert, R.K. (1974) Am. J. Clin. Pathol. 61.904-Qll Williams. G.Z.. Young, D.S.. Stein, M.R. end Cotlove. E. (1970) Clin. Chem. 16.1016-1021 Harris. E.K.. Kanofekv. P., Shake& G. end Cotlove, E. (1970) Clin. Chem. 16.1022-1027