Literature DB >> 27683447

Between-Subject Variation of the Within-Subject Biological Variation.

Xavier Fuentes-Arderiu1.   

Abstract

Entities:  

Keywords:  biological variation; interval estimation; point estimation; statistics; within-subject biological variation

Year:  2013        PMID: 27683447      PMCID: PMC4975186     

Source DB:  PubMed          Journal:  EJIFCC        ISSN: 1650-3414


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Recently, the European Federation of Clinical Chemistry Laboratory Medicine (1), within the frame of its Science Committee, has created a working group (WG) on biological variation. In its website (2), this WG describes its structure and its purpose (“Terms for reference”). Some members of this WG and other authors published a very interesting systematic review of data on biological variation for the catalytic concentrations of three enzymes in serum (3). Among other conclusions, the authors stated that published biological variation data for the three enzymes studies demonstrate a wide range of values derived from inconsistent protocols, and also stated that the findings in their review raise concerns around the utility of the data currently available. Examples of publications with these biological variation data are given in references (4) and (5). I agree absolutely with the conclusions raised by the authors of the systematic review. Nevertheless, may I add some opinion and some objective data that can reinforce the information given by the authors of the systematic review. In my opinion, the main factor that hampers the use of data of within-subject biological variation for the proposed (by the review’s authors) purposes is the between-subject variation affecting these kind of data. And consequently, a doubt must be cast upon the general application of the usual point estimations of within-subject biological variation, usually expressed as a single value of coefficient of variation. This opinion is based in my own experience. Some years ago I was doctoral supervisor (dissertation director), working on within-subject biological variation observed during one year (6, 9). These dissertations generated seven articles of different types published in well recognized international scientific journals (10-16). The information shown in Table 1 comes from these dissertations and articles.
Table 1

Biological quantities and references, number of volunteers involved in each study (n), median, lowest and highest values of the coefficients of variation corresponding to the within-subject biological variation (CVBw) (6-9, 10-16). [Biological quantities are described according to the IFCC and IUPAC recommendations (17)]

Biological quantity (and references)nMedian of CVBwLowest CVBwHighest CVBw
P—Alanine aminotransferase; cat.c. (6)2027.7< 0.168.8
Prot.(S)—Albumin; mass fr. (6, 10)204.1< 0.16.9
P—Alkaline phosphatase; c.con. (6)208.22.524.1
P—α-Amylase; cat.c. (6)208.4< 0.117.0
P—Aspartate aminotransferase; cat.c. (6)2016.0< 0.131.6
P—Bilirubin; subst.c. (6)2028.98.743.9
P—Calcium(II); subst.c. (6)202.0< 0.14.1
P—Chloride; subst.c. (6)201.6< 0.13.6
P—Creatine kinase; cat.c. (6)2020.012.049.6
P—Creatininium; subst.c. (6)206.71.515.7
Prot.(S)—α1-Globulin; mass fr. (6, 10)209.6< 0.135.4
Prot.(S)—α2-Globulin; mass fr. (6, 10)2010.43.417.2
Prot.(S)—β-Globulin; mass fr. (6, 10)209.65.319.9
Prot.(S)—γ-Globulin; mass fr. (6, 10)2011.2< 0.128.3
P—Glucose; subst.c. (6)205.02.17.0
P—γ-Glutamyltransferase; cat.c. (6)2030.111.763.4
P—Iron(II+III); subst.c. (6)2021.613.536.6
P—Lactate dehydrogenase; cat.c. (6)20< 0.111.3
P—Phosphate(inorganic); subst.c. (6)208.619.31.3
P—Potassium ion; subst.c. (6)205.01.07.7
P—Protein; mass c. (6)203.11.68.0
P—Sodium ion; subst.c. (6)200.1< 0.11.6
P—Thyrotropin; arb.subst.c. (6)2029.69.946.9
P—Thyroxine; subst.c. (6, 11)208.2< 0.114.4
P—Triiodothyronine; subst.c. (6, 11)209.8< 0.116.6
P—Urate; subst.c. (6)2010.26.423.8
P—Urea; subst.c. (6)2013.55.022.7
P—Cholesterol; subst.c. (7, 15)406.92.211.0
P—HDL-Cholesterol; subst.c. (7, 15)407.13.113.5
P—LDL-Cholesterol; subst.c. (7, 15)4013.36.729.0
P—Triglyceride; subst.c. (7, 15)4016.79.936.3
P—Apolipoprotein A-I; mass c. (7, 15)406.4< 0.122.9
P—Apolipoprotein B; mass c. (7, 15)4013.56.027.3
P—Coagulation, tissue factor-induced; rel.time (8, 12)391.7< 0.111.7
P—Coagulation, surface-induced; rel.time (8, 12)39< 0.1< 0.18.4
B—Erythrocytes; entitic vol. (8, 13)391.10.21.8
B—Erythrocytes; num.c. (8, 13)392.81.65.7
B—Erythrocytes; vol.fr. (8, 13)392.71.36.0
B—Haemoglobin; mass c. (8, 13)392.71.25.5
B—Leukocytes; num.c. (8, 13)3912.23.532.3
Lkcs(B)—Lymphocytes; num.fr. (8, 14)39< 0.1< 0.123.1
Lkcs(B)—Neutrophils; num.fr. (8, 14)398.6< 0.124.6
B—Thrombocytes; num.c. (8, 13)397.5< 0.116.7
P—Follitropin; arb.subst.c. (9, 16)2017.36.142.9
P—Lutropin; arb.subst.c. (9, 16)2024.08.947.3
P—Testosterone; subst.c. (9, 16)2010.90.021.8
Table 1 shows the number of healthy adult volunteers involved in each study. In all these studies, blood was collected once a month for one year, and only one measurement per sample was performed. Measurements were done the same day of blood collection. For each volunteer, no outliers were detected (simply Dixon statistical test) after pooling the twelve measured values. For each biological quantity, variance corresponding to day-to-day imprecision of the corresponding measuring system, used according a given measurement procedure, was subtracted to the total within-subject variance to obtain the within-subject biological variance (plus the pre-metrological variance, when it is not zero). Bearing in mind that in each study all the volunteers were treated in the same way, lowest and highest individual coefficients of variation corresponding to the within-subject biological variances shown in Table 1 indicate that standardization of all processes concerned with the estimation on the within-subject biological variance is not sufficient to obtain point estimates (single values) of within-subject biological coefficients of variation which could be useful for the purposes proposed elsewhere. Furthermore, for each biological quantity, when the highest coefficient of variation is greater than 33 %, we can admit that the probability distribution function of the individual coefficients of variation is asymmetric.
  9 in total

1.  Properties and units in the clinical laboratory sciences, Part XXIII. The NPU terminology, principles and implementation -a user's guide (Technical Report 2011) (IFCC-IUPAC).

Authors:  Ulla Magdal; René Dybkaer; Henrik Olesen
Journal:  Clin Chem Lab Med       Date:  2012-11-18       Impact factor: 3.694

2.  Within-subject and between-subject biological variation of prothrombin time and activated partial thromboplastin time.

Authors:  D Dot; J Miró; X Fuentes-Arderiu
Journal:  Ann Clin Biochem       Date:  1992-07       Impact factor: 2.057

Review 3.  Intra- and inter-individual biological variability data bank.

Authors:  M A Sebastián-Gámbaro; F J Lirón-Hernández; X Fuentes-Arderiu
Journal:  Eur J Clin Chem Clin Biochem       Date:  1997-11

4.  Intra-individual variation of the electrophoretic serum protein fractions.

Authors:  L Juan-Pereira; X Fuentes-Arderiu
Journal:  Clin Chem       Date:  1989-07       Impact factor: 8.327

5.  Within- and between-subject biological variations of follitropin, lutropin, testosterone, and sex-hormone-binding globulin in men.

Authors:  J Valero-Politi; X Fuentes-Arderiu
Journal:  Clin Chem       Date:  1993-08       Impact factor: 8.327

Review 6.  A systematic review of data on biological variation for alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase.

Authors:  Anna Carobene; Federica Braga; Thomas Roraas; Sverre Sandberg; William A Bartlett
Journal:  Clin Chem Lab Med       Date:  2013-10       Impact factor: 3.694

7.  Biological variation of the leukocyte differential count quantities.

Authors:  D Dot; J Miró; X Fuentes-Arderiu
Journal:  Scand J Clin Lab Invest       Date:  1992-11       Impact factor: 1.713

8.  Biological variation data applied to the selection of serum lipid ratios used as risk markers of coronary heart disease.

Authors:  J Ortolá; M J Castiñeiras; X Fuentes-Arderiu
Journal:  Clin Chem       Date:  1992-01       Impact factor: 8.327

9.  Within-subject biological variation of hematological quantities and analytical goals.

Authors:  D Dot; J Miró; X Fuentes-Arderiu
Journal:  Arch Pathol Lab Med       Date:  1992-08       Impact factor: 5.534

  9 in total

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