Biological Variation of Hemostasis Variables in Thrombosis and Bleeding: Consequences for Performance Specifications.
Biological variation is defined as the variation within individuals when they are measured repeatedly over time. This within-subject biological variation can be influenced by transient environmental and lifestyle factors such as stress (physical exercise), acute phase reactions, circadian rhythm, and seasonal variation (7-11). Other sources of variation in the analysis of hemostasis factors are the between-individual and the analytical variation of the assays.
To determine the criteria for the maximal allowable analytical variation for hemostasis parameters, data on biological variation can be used and this approach has been suggested to be the optimal method available (5, 6, 12). However, information on biological variation in hemostasis variables is still limited and is based on small studies with a limited number of sampling points, a short time period, and/or only specifically selected parameters (10, 13-21). To provide a recommendation based on biological variation, there is a need for a large study over a longer time period with sufficient sampling moments and comprehensive thrombosis and bleeding variables.
The aim of this study was to determine in a prolonged longitudinal study (i.e., 13 repeated blood sampling and measurements across a period of 1 year) the biological variation of hemostasis variables involved in thrombosis and bleeding [prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen, antithrombin (AT), protein C, protein S, factor VIII, factor IX, von Willebrand factor (VWF)]. On the basis of the biological variation obtained from this study we provide recommendations for analytical performance specifications for laboratory tests used for the diagnosis, follow-up, and monitoring of the treatment of thrombosis and bleeding. Additionally, we determine whether the performance of the hemostasis tests used in this study fulfils these new, predefined analytical criteria, based on biological variation.
Study Participants and Methods
Our study included 40 healthy individuals without symptoms of chronic or acute infectious diseases who had not undergone surgical procedures within the 3 months before their inclusion in the study. Blood was collected from each participant, at 13 visits over a 1-year time period. Data on demographics and cardiovascular risk factors were gathered using standardized questionnaires. Before each blood collection, study participants were asked whether they had recently used drugs, or suffered from infections, such as the common cold. The study protocol was in accordance with the Declaration of Helsinki and was approved by the Medical Ethics Committee of Erasmus MC. Written informed consent was obtained from each participant.
BLOOD SAMPLING PROCEDURE AND PLASMA
Blood was collected while the study participants were sitting and resting. They were allowed to have a light breakfast on the morning of blood collection. Blood was drawn by venipuncture using the Vacutainer system (Becton Dickinson) containing sodium citrate (final concentration 0.105 mol/L). Plasma was obtained by centrifugation at 3500g for 15 min at 4 [degrees]C and stored in aliquots at -80 [degrees]C until further analysis. On visual inspection, no plasma samples were lipemic, icteric, or hemolytic. All parameters tested in this study have been reported to be stable for up to 18 months when plasma is stored at -74 [degrees]C (22). To avoid interassay analytical variation, all samples from each participant were analyzed in 1 run.
Routine coagulation tests (APTT, PT, fibrinogen) and coagulation inhibitors (antithrombin, protein C chromogenic and clotting activity, and protein S total and free antigen and clotting activity) were measured on an STA Compact analyzer using STAGO reagents (APTT: STA PTT Automate; PT: STA neoplastin CI; fibrinogen: STA fibrinogen; antithrombin: Stachrom AT; protein C chromogenic: Stachrom protein C; protein C clotting activity: Staclot protein C; protein S clotting activity: Staclot protein S; total protein S antigen: Liatest total protein S; free protein S antigen: Liatest free protein S) (Diagnostica Stago).
Von Willebrand factor antigen (VWF:Ag) concentrations were determined with an in-house ELISA assay, using polyclonal rabbit anti-human VWF antibodies (DakoCytomation) for capturing and detecting (23).
Von Willebrand factor collagen binding (VWF:CB) activity was measured by an in-house ELISA assay using bovine Achilles tendon collagen type I for capturing (Sigma-Aldrich) and polyclonal rabbit anti-human VWF antibodies (DakoCytomation) for detecting.
Von Willebrand factor ristocetin cofactor (VWF: RCo) activity was measured with an in-house assay in a aggregometer (Chronolog Aggregometer 490) that measures the rate of aggregation of platelets in the presence of VWF and ristocetin.
FVIII coagulant activity (FVIII:C) was measured using a 1-stage clotting assay and derived from (the prolongation of) the clotting time (APTT) measured with Triniclot (Kordia) on the Sysmex CA-1500 (Siemens).
Factor IX coagulant activity (FIX:C) was measured using a 1-stage clotting assay and derived from (the prolongation of) the clotting time (APTT) measured with Actin FS on the Sysmex CS2100i (Siemens).
All assays used commercial reference plasma (Unicalibrator, Stago or Normal reference plasma, Precision Biologic, Kordia) that was standardized against the WHO standard by the manufacturer.
All samples of each individual were measured in duplicate in the same analytical run. Since we aimed to analyze analytical variation, no criteria were defined for reanalysis on the basis of bad duplicates. Each analytical run included a normal and abnormal QC sample, evaluated by the Westgard criteria (24). All study participant samples were measured with the same batch of reagents. To access the between-run CVs for the assays used in this study see Table 1 in the Data Supplement that accompanies the online version of this article, at http://www.clinchem.org/content/vol62/issue12.
Data are presented as mean and SD or medians with interquartile range for continuous variables, depending on their distribution, and as counts and percentages for categorical variables. The components of variation are given as CV. All measured values were included in the analysis.
In the present study, sources of variation were calculated using a random-effects model from a completely nested design with 2 factors using the NESTED procedure in version 9.2 of the statistical program SAS (25). In the nested model (proc nested data = "file"; classes individual sampling; var measurement; run), individuals and sampling occasions are entered as classes and duplicate measurements as variable. The output of the procedure then gives between-subject variance, within-subject variance nested within individuals, while the analytical variance is the error term in the model. The variances were assumed to be normally distributed.
We calculated the number of repeated measurements (m) that was needed to estimate with 95% probability a homeostatic setting point, which did not deviate more than 10% and 20% (p%) from its true value (26, 27):
m = [[1.96 X [([CV.sup.2.sub.A] + [CV.sup.2.sub.I]).sup.1/2]/p%].sup.2]. (1)
Here, [CV.sub.A] was the coefficient of analytical variation and [CV.sub.I] was the coefficient of within-subject biological variation. The recommended analytical variation for a diagnostic test was calculated as 58% of total variation of the study population. By this criterion, the analytical variation adds a maximum of 12% variation to the total test variability (12). The recommended analytical imprecision for monitoring was calculated as 50% of the within subject biological variation, according to which an assay adds a maximum of 10% variation to the total test variability (5). In addition, the recommended analytical bias was calculated, which indicated the difference between the expected measurement results and the estimated true value of the measured quantity as a result of assay error (6):
Bias < 0.25 X [([CV.sub.G] + [CV.sub.Iwithin-Subject]).sup.1/2]. (2)
[CV.sub.G] was the coefficient of between-subject biological variation and [CV.sub.I] was the coefficient of within-subject biological variation.
Analyses were performed on the whole group and on subgroups [with and without outliers (values outside the 3-SD range), by sex, excluding oral contraceptive users and excluding smokers]. Statistical analyses were performed with SPSS for Windows version 15 (SPSS Inc), and SAS version 9.2. A 2-sided P value <0.05 was considered statistically significant.
Our study group of 40 healthy volunteers had a median age of 51 years (25%-75% range 26-54 years), 65% were female, of whom 9 (35%) used oral contraceptives (Table 1). The rates of use of aspirin and lipid-lowering medications were low (5% and 2.5%, respectively).
When the different components of the variation (between-, within-subject and analytical) were separated, the between-subject variation varied from 4.1% to 31.2%, the within-subject variation from 2.6% to 25.6% and the assay variation from 1.3% to 12.9% (for details see Table 2). For some of the hemostasis variables the within-subject and between-subject variation were very different, while for other tests these parameters were quite similar (Table 2).
In the diagnostic laboratory, repeated measurements can be used to reduce the influence of within-subject variation on the test result and thus improve the estimate of the real homeostatic value. When we calculated the number of repeated measurements that would be required to reduce the [CV.sub.I] to below 20%, for many of the assays [PT, APTT, protein C chromogenic (PC-chrom), protein S activity (PS-act), protein S total (PS-total), protein S free (PS-free), FIX:C, and AT] a single measurement would be sufficient. For fibrinogen, PC clotting (PC-clot) test, VWF:Ag, VWF:CB and VWF:RCo tests and FVIII:C it was necessary to perform multiple tests to reach this level of precision (Table 3). If we aimed to decrease the within-subject individual variation to below 10%, the number of measurements is still 1 for PT and antithrombin. For the other tests more measurements would be required to achieve this precision, and for VWF:CB, for example, 82 measurements would be needed to obtain an analytical variation below 10% (Table 3), but in daily routine this precision is not needed.
The recommended desired [CV.sub.A] for diagnostic purposes, based on biological variation, (5, 6) varied between 2.8% for the PT and 35.5% for the VWF:CB assay, and for monitoring of treatment or disease severity the recommended desired [CV.sub.A] varied between 1.3% for the PT and 20.7% for the VWF:CB assay (Table 4). In Fig. 1 these recommended [CV.sub.A] are compared with the actual [CV.sub.A] for the tests. All tests were found to satisfy these requirements for use in diagnosis, and most tests also fulfilled the requirements for monitoring. Only PC-clot and PS-act assays had slightly higher analytical variations. When literature data on desirable analytical variation for the hemostasis tests were used for this analysis, our conclusion that the tests fulfilled the criteria were confirmed, although large differences in reported variations were seen between the different studies (Table 5) (10, 12-20). The allowable analytical bias varied between 1.2% for the PT to 15.3% for the VWF:CB test (Table 3).
In this study, we have shown that the analytical variation of routine hemostasis tests that are used in the diagnosis of thrombosis and bleeding problems (PT, APTT, fibrinogen, protein C, protein S, AT, and VWF assays) fulfills the criteria defined by the biological variation approach, both for diagnostic testing and for the monitoring of treatment. Only 2 assays, i.e., PC-clot and PS-act, just missed the criterion for monitoring.
Using biological variation in healthy individuals is currently considered to be the best available method to define analytical performance specifications for tests (4, 28). However, we realize that this approach has some limitations. Importantly, it does not take clinical relevance into consideration (4). Nevertheless, the use of the biological variation of hemostasis variables in healthy individuals provides a helpful tool for the diagnostic laboratory to set performance specifications (5, 6). The Dutch SKML external quality program has recently started to use biological variation in their assessment of quality.
In any laboratory, the central and most important aim is the quality of the measurement procedures and of the outcomes. To determine this quality, it is essential to define criteria. These were first discussed during the Stockholm Consensus Conference on analytical quality specifications (29). Recently, this consensus agreement was revisited during the first Strategic Conference on Analytical Quality Specifications organized by the European Federation for Laboratory Medicine (EFLM) (4, 28). The main outcome of the Conference was agreement on the hierarchy of models that can be used to set analytical quality specifications. In this hierarchy, only "evaluation of the effect of analytical performance on clinical outcomes in specific clinical settings" scores higher than "evaluating the effect of analytical performance using data based on components of biological variation," which makes the biological variation-based approach highly relevant for the clinical laboratory. Of course, evidence-based data on the requirements of different specific settings give the ultimate criteria for a diagnostic test.
The data that have been obtained on biological variation differ between studies. In many previous studies, assays were not performed in duplicate, preventing the differentiation of analytical variation from within- and between-individual variation. However, for most assays, analytical variation is much less than the within- and between-individual variation. Also the duration of the study may affect the data obtained on the biological variation. Several studies only consider the short-term biological variation (13, 20). Differences in study duration may account for differences in the desirable [CV.sub.A] based on these published short-term biological variation data and the data we obtained in our study (Table 4). The strength of our study is that the biological variation of general hemostatic variables (APTT, PT, Fibrinogen), markers for thrombotic (antithrombin, protein C, protein S) and bleeding (FVIII:C, FIX:C and VWF) disorders were measured in 1 study. In addition, the biological variation was established by sampling and measuring over a study period of 1 year thereby encompassing both short-term and long-term variation. A comparison of the findings of this study with those of the studies published in this field is summarized in Table 4. Our long-term study period includes any potential seasonal effects on the biological variation and as such a more reliable estimate of both the within- and between-individual biological variation.
We were able to isolate the analytical variation from the within- and between-variation because we measured our samples in duplicate. A component of analytical variation that is not isolated using this approach is the between-run variation that is part of the between-subject variation. In daily laboratory routine, samples from patients are measured on different days, so this type of variation in present in daily practice. For understanding how much between subject variation can be explained by analytical between-run variation we roughly calculated this component based on the internal QC results of our laboratory (see online Supplemental Table 1). For antithrombin (with relatively the highest internal QC CV) this between-run variation explains about half of the between-subject variation and still fulfils the imprecision criteria. For all other variables, the effect was very small (data not shown). Since we measured all samples of 1 patient in 1 run, this component does not contribute to the within-subject variation.
In the current study, we used only a single reagent on a single coagulation analyzer for each assay. Evaluation of data reported in the ECAT External Quality Assessment (EQA) program shows that variations within commercial diagnostic tests are of the same magnitude throughout different surveys but may differ between commercial diagnostic tests. Further studies on reagents and analyzers other than used in our study need to be performed before it is possible to ascertain whether our criteria are generalizable.
The participants of our study were between 21 and 70 years old and it is uncertain whether the conclusions of our study can be extrapolated to individuals who are younger or older.
The participants were allowed to have a light breakfast. We did not standardize the exact content of the breakfast, but it has been previously reported that a light breakfast either does not influence or only slightly influences laboratory coagulation tests (30). In our opinion, this reflects daily clinical practice in which patients are not always fasting when blood is drawn.
Analytical quality specifications based on the biological variation can also be used to assess whether the longterm analytical quality of laboratory testing based on the results in an EQA is sufficient (31, 32). Data on the biological variation obtained in this study may support the implementation of performance specifications both by laboratories and EQA programs. This may enable further improvement in diagnostic testing and the monitoring of treatment in thrombotic and bleeding disorders.
In conclusion, we have provided in this comprehensive study the analytical performance specifications for laboratory tests relevant in testing for thrombotic and bleeding disorders based on the data on biological variation. In addition, the reagents and analyzers used in this study ensure that the analytical performance of routine hemostasis tests fulfils these criteria.
Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:
Employment or Leadership: C. Kluft, Good Biomarker Sciences; P. Meijer, ECAT Foundation.
Consultant or Advisory Role: C. Kluft, ECAT.
Stock Ownership: None declared.
Honoraria: None declared.
Research Funding: Unconditional gift of reagents from Diagnostica Stago (Ascieres surSeine, France); and the ECAT Foundation (Leiden, the Netherlands). C. Kluft, Good Biomarker Sciences.
Expert Testimony: None declared.
Patents: None declared.
Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, and final approval of manuscript.
Acknowledgments: J. Malfliet, F. van de Reijt, L. Felida, P. van Randwijk, and M. Dieterich (Dept, Hematology, Erasmus MC, Rotterdam, the Netherlands), and K. van Leuven andJ. Neuteboom (GBS, Leiden, the Netherlands) are acknowledged for their excellent laboratory assistance. Roche Diagnostics (Almere, the Netherlands) is acknowledged for their technical support.
(1.) Dix D, Cohen P, Barzegar S. Estimating biological variation in diagnostic tests. Clin Chem 1982; 28:1982.
(2.) Walton RM. Subject-based reference values: biological variation, individuality, and reference change values. Vet Clin Pathol 2012; 41:175- 81.
(3.) Ricos C, Alvarez V, Cava F, Garcia-Lario JV, Hernandez A, Jimenez CV, et al. Integration of data derived from biological variation into the quality management system. Clin Chim Acta 2004; 346:13- 8.
(4.) Sandberg S, Fraser CG, Horvath AR, Jansen R, Jones G, Oosterhuis W, et al. Defining analytical performance specifications: consensus statement from the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2015; 53:833-5.
(5.) Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Lab Sci 1989; 27:409 -37.
(6.) Fraser CG, Hyltoft Petersen P, Libeer JC, Ricos C. Proposals for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997; 34:8 -12.
(7.) Rudez G, Meijer P, Spronk HM, Leebeek FW, ten Cate H, Kluft C, de Maat MP. Biological variation in inflammatory and hemostatic markers. J Thromb Haemost 2009; 7:1247-55.
(8.) Banfi G, Del Fabbro M. Biological variation in tests of hemostasis. Semin Thromb Hemost 2008; 34:635- 41.
(9.) Ricos C, Alvarez V, Cava F, Garcia-Lario JV, Hernandez A, Jimenez CV, et al. Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest 1999; 59:491-500.
(10.) de Maat MP, de Bart AC, Hennis BC, Meijer P, Havelaar AC, Mulder PG, Kluft C. Interindividual and intraindividual variability in plasma fibrinogen, tPA antigen, PAI activity, and CRP in healthy, young volunteers and patients with angina pectoris. Arterioscler Thromb Vasc Biol 1996; 16:1156 - 62.
(11.) Montagnana M, Salvagno GL, Lippi G. Circadian variation within hemostasis: an underrecognized link between biology and disease? Semin Thromb Hemost 2009; 35:23-33.
(12.) Harris EK. Proposed goals for analytical precision and accuracy in single-point diagnostic testing. Theoretical basis and comparison with data from College of American Pathologists proficiency surveys. Arch Pathol Lab Med 1988; 112:416 -20.
(13.) Chen Q, Shou W, Wu W, Guo Y, Zhang Y, Huang C, Cui W. Biological and analytical variations of 16 parameters related to coagulation screening tests and the activity of coagulation factors. Semin Thromb Hemost 2015; 41: 336-41.
(14.) Dot D, Miro J, Fuentes-Arderiu X. Within-subject and between-subject biological variation of prothrombin time and activated partial thromboplastin time. Ann Clin Biochem 1992; 29:422-5.
(15.) Chambless LE, McMahon R, Wu K, Folsom A, Finch A, Shen YL. Short-term intraindividual variability in hemostasis factors the ARIC study. Ann Epi 1992; 2:723-33.
(16.) Salomaa V, Rasi V, Stengard J, Vahtera E, Pekkanen J, Vartiainen E, et al. Intra- and interindividual variability of hemostatic factors and traditional cardiovascular risk factors in a three-year follow-up. Thromb Haemost 1998; 79:969-74.
(17.) Thompson SG, Martin JC, Meade TW. Sources of variability in coagulation factor assays. Thromb Haemost 1987; 58:1073-7.
(18.) Wada Y, Kurihara M, Toyofuku M, Kawamura M, Iida H, Kayamori Y, et al. Analytical goals for coagulation tests based on biological variation. Clin Chem Lab Med 2004; 42:79-83.
(19.) Kilercik M, Coskun A, Serteser M, Inan D, Unsal I. Biological variations of ADAMTS13 and von Willebrand factor in human adults. Biochem Med 2014; 24:138 - 45.
(20.) Nguyen ND, Ghaddar H, Stinson V, Chambless LE, Wu KK. ARIC Hemostasis Study-IV. Intraindividual variability and reliability of hemostatic factors. The Atherosclerosis Risk In Communities (ARIC). Thromb Haemost 1995; 73:256-60.
(21.) Costongs GM, Bas BM, Janson PC, Hermans J, Brombacher PJ, van Wersch JW. Short-term and long-term intra-individual variations and critical differences of coagulation parameters. J ClinChemClin Biochem 1985; 23:405-10.
(22.) Woodhams B, Girardot O, Blanco MJ, Colesse G, Gourmelin Y. Stability of coagulation proteins in frozen plasma. Blood Coagul Fibrinolysis 2001; 12:229-36.
(23.) Wieberdink RG, van Schie MC, Koudstaal PJ, Hofman A, Witteman JC, de Maat MP, et al. High von Willebrand factor levels increase the risk of stroke: the Rotterdam study. Stroke 2010; 41:2151- 6.
(24.) Westgard JO, Barry PL, Hunt MR, Groth T. A multi-rule shewhart chart for quality control in clinical chemistry. Clin Chem 1981; 27:493-501.
(25.) SAS/STAT[R] 9.2 user's guide: the NESTED procedure (book excerpt). https://support.sas.com/documentation/ cdl/en/statugnested/61810/PDF/default/statugnested. pdf (Accessed September 2016).
(26.) Harris EK. Statistical principles underlying analytic goal-setting in clinical chemistry. Am J Clin Pathol 1979; 72:374-82.
(27.) Cotlove E, Harris EK, Williams GZ. Biological and analytic components of variation in long-term studies of serum constituents in normal subjects. 3. Physiological and medical implications. Clin Chem 1970; 16:1028-32.
(28.) Panteghini M, Sandberg S. Defining analytical performance specifications 15 years after the Stockholm conference. Clin Chem Lab Med 2015; 53:829-32.
(29.) Fraser CG. General strategies to set quality specifications for reliability performance characteristics. Scand J Clin Lab Invest 1999; 59:487-90.
(30.) Lima-Oliveira G, Salvagno GL, Lippi G, Danese E, Gelati M, Montagnana M, et al. Could light meal jeopardize laboratory coagulation tests? Biochem Med 2014; 24: 343-9.
(31.) Meijer P, de Maat MP, Kluft C, Haverkate F, van Houwelingen HC. Long-term analytical performance of hemostasis field methods as assessed by evaluation of the results of an external quality assessment program for antithrombin. Clin Chem 2002; 48:1011-5.
(32.) Meijer P, Kluft C, Haverkate F, De Maat MP. The longterm within- and between-laboratory variability for assay of antithrombin, and proteins C and S: results derived from the external quality assessment program for thrombophilia screening of the ECAT Foundation. J Thromb Haemost 2003; 1:748-53.
Moniek P.M. de Maat,  * Marianne van Schie,  Cornelis Kluft,  Frank W.G. Leebeek,  and Piet Meijer 
 Department of Haematology, Erasmus Medical Center, Rotterdam;  ECAT Foundation, Voorschoten, The Netherlands.
* Address correspondence to this author at: Dept. of Hematology (Rm. Nb845a), Erasmus University Medical Centre, PO Box 2040, 3000 CA Rotterdam, The Netherlands. Fax +31-10-4089470; e-mail firstname.lastname@example.org.
Received June 1, 2016; accepted August 17, 2016.
Previously published online at DOI: 10.1373/clinchem.2016.261248
 Nonstandard abbreviations: FVIII, factor VIII; PT, prothrombin time; APTT, activated partial thromboplastin time; AT, antithrombin; VWF, von Willebrand factor; VWF:Ag, VWF antigen; VWF:CB, VWF collagen binding; VWF:RCo, VWF ristocetin cofactor activity; FVIII:C, FVIII coagulant activity; FIX:C, FIX coagulant activity; PC-chrom, protein C chromogenic; PS-act, protein S activity; PS-total, protein S total; PS-free, protein S free; PC-clot, PC clotting; [CV.sub.A], analytical variation; [CV.sub.I], within-individual variation; CVG, between-individual variation; EFLM, European Federation for Laboratory Medicine; EQA, external quality assessment.
Caption: Fig. 1. Des red imprecision (monitoring and diagnostic) vs analytical [CV.sub.A]. Open columns indicate analytical variation; hatched columns, requirement for analytical variation in monitoring; and solid columns, requirement for analytical variation in diagnostictesting.
Table 1. Characteristics of the study population (n = 40). Variable Values Age, years, median (range) 51 (21-70) Females, n (%) 26 (65) Smokers, n (%) 7 (18) Body mass index, kg/[m.sup.2], mean (SD) 22.6 (2.0) Oral contraceptives, n (%) 9 (23) Lipid lowering medication, n (%) 1 (2.5) NSAIDs (aspirin), n (%) 2 (5) Table 2. Components of variation in plasma concentrations of thrombophilia hemostasis variables. CVs (%) Variable Mean (SD) Between-subject Within-subject General assays PT, s 14.2 (0.7) 4.1 2.6 APTT, s 36.1 (3.4) 7.1 6.4 Fibrinogen, g/L 2.97(0.62) 17.0 11.9 Thrombosis factors AT, U/mL 1.10(0.09) 7.8 4.4 PC-clot, U/mL 1.32 (0.29) 22.4 8.9 PC-chrom, U/mL 1.19(0.25) 19.5 7.6 PS-act, U/mL 0.91 (0.23) 23.8 8.1 PS-total, U/mL 0.88 (0.17) 17.8 7.3 PS-free, U/mL 0.94 (0.24) 25.0 7.6 Bleeding factors VWF:Ag, U/mL 1.11 (0.35) 28.6 15.8 VWF:CB, U/mL 1.12 (0.49) 28.0 25.6 VWF:RCo, U/mL 1.27(0.39) 31.2 21.3 FVIII, U/mL 1.03 (0.30) 25.2 15.8 FIX, U/mL 0.99 (0.20) 18.2 9.1 CVs (%) Variable Analytical variation General assays PT, s 1.3 APTT, s 1.4 Fibrinogen, g/L 2.7 Thrombosis factors AT, U/mL 1.4 PC-clot, U/mL 5.5 PC-chrom, U/mL 1.7 PS-act, U/mL 4.1 PS-total, U/mL 1.4 PS-free, U/mL 3.3 Bleeding factors VWF:Ag, U/mL 4.2 VWF:CB, U/mL 12.9 VWF:RCo, U/mL 9.6 FVIII, U/mL 2.3 FIX, U/mL 2.8 Table 3. Recommendations for the number of repeated measurements and analytical bias. Number of repeated Recommended measurements to analytical reduce within-subject bias (%) variation to Variable 10% 20% General assays PT 1 1 1.2 APTT 2 1 2.4 Fibrinogen 6 2 5.2 Thrombosis factors AT 1 1 1.3 PC-clot 5 2 6.0 PC-chrom 3 1 5.2 PS-act 4 1 6.3 PS-total 3 1 4.8 PS-free 3 1 6.5 Bleeding factors VWF:Ag 10 3 8.1 VWF:CB 82 21 15.3 VWF:RCo 21 5 9.4 FVIII:C 10 3 7.4 FIX:C 4 1 5.1 Table 4. [CV.sub.A] as measured in this study in relation to the recommended [CV.sub.A]. Variable [CV.sub.A]: Desirable [CV.sub.A]: this this study study Diagnosis Monitoring General assays PT 1.3 2.8 1.3 APTT 1.4 5.5 3.3 Fibrinogen 2.7 12.0 6.0 Thrombosis factors AT 1.4 5.2 2.2 PC-clot 5.5 14.0 4.5 PC-chrom 1.7 12.1 3.8 PS-act 4.1 14.6 4.0 PS-total 1.4 11.1 3.7 PS-free 3.3 15.2 3.8 Bleeding factors VWF:Ag 4.2 18.9 7.9 VWF:CB 12.9 35.5 20.7 VWF:RCo 9.6 21.8 10.6 FVIII:C 2.3 17.4 7.9 FIX:C 2.8 11.8 4.6 Variable Desirable [CV.sub.A]: literature data [references] Diagnosis Monitoring General assays PT 3.0-4.2 1.2-1.3 [Chen et al. (13), Dot et al. (14)] APTT 5.0-6.4 0.9-2.3 [Chen et al. (13), Dot et al. (14), Chamless et al. (15), Costongs et al. (21 )] Fibrinogen 10.0-13.5 2.6-6.7 [de Maat et al. (10), Chen et al. (13), Chamless et al. (15), Salomaa et al. (16)] Thrombosis factors AT 4.4-6.1 0.6-2.7 [Chamless et al. (15), Thompson et al. (17), Costongs et al. (21 )] PC-clot 7.8-11.1 1.2-4.0 [Chamless et al. (15), Wada et al. (18)] PC-chrom -- -- PS-act 13.7 3.8 [Wada et al. (18)] PS-total 5.4 1.5 [Nguyen et al. (20)] PS-free 8.5 0.0 [Nguyen et al. (20)] Bleeding factors VWF:Ag 15.5 7.2 [Kilercik et al. (19)] VWF:CB -- -- VWF:RCo 11.7 4.1 [Kilercik et al. (19)] FVIII:C 11.4-15.4 2.4-8.0 [Chen et al. (13), Chamless et al. (15), Thompson et al. (17)] FIX:C 7.2 3.0 [Chen et al. (13)] Table 5. Overview of studies on biological variation in coagulation parameters. Reference Number of M/F Study Number of study (a) period sampling participants occasions This study 40 14/26 1 year 13 Chen et al. (13) 31 18/13 5 days 9 Nguyen et al. (20) 39 16/23 3-6 weeks 3 Dot et al. (14) 39 20/19 9 months 9 Chamless et al. (15) 39 16/23 3-6 weeks 3 De Maat et al. (10) 20 10/10 6 months 9 Salomaa et al. (16) 473 3 years 2 Thompson et al. (17) 14 6/8 3 years 20 Wada et al. (18) 17 8/9 1 year 12 Kilercik et al. (19) 19 10/9 5 weeks 15-19 Reference Parameters This study APTT, PT, Fbg, (b) ATIII, protein C clotting and chromogenic activity, protein S activity, total and free antigen, VWF antigen, activity, collagen-binding, FVIII, FIX Chen et al. (13) APTT, PT, INR, Fbg, TT, FDP, FII, FV, FVII, FVIII, FIX, FX, FXI, FXII Nguyen et al. (20) PAI-1, t-PA, D-Dimer, FPA, protein S total and free Dot et al. (14) APTT, PT Chamless et al. (15) APTT, Fbg, ATIII, protein C, VWF:Ag, FVII, FVIII De Maat et al. (10) Fbg, tPA:Ag, PAI-1 activity, CRP Salomaa et al. (16) Fbg, Plg, FVII Thompson et al. (17) Fbg, FII, FVII, FVIII, FX, VWF, ATIII, Wada et al. (18) APTT, PT, Fbg, thrombotest, ATIII, [alpha]2PI, Plg, TAT, PAP, TM, PAI-1/tPA complex, protein C and protein S Kilercik et al. (19) VWF antigen and activity, ADAMTS13 activity and antigen (a) M/F, number of males and females, respectively. (b) Fbg, fibrinogen; ATIII, antithrombin III; INR, international normalized ratio; TT, thrombin time; FDP, fibrin degradation product; FII, factor II; FV, factor V; FVII, factor VII; FX, factor X; FXI, factor XI; FXII, factor XII; PAI-1, plasminogen activator inhibitor- 1; tPA, tissue plasminogen activator; FPA, fibrinopeptide A; tPA:Ag, tPA antigen; CRP, C-reactive protein; Plg, plasminogen; [alpha]2PI, [[alpha].sub.2]-antiplasmin; TAT,thrombin-antithrombin; PAP, plasmin- [alpha] 2-antiplasmin complex; TM,thrombomodulin; ADAMTS13, a disintegrin and metalloproteinase with thrombospondin motifs 13.
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||Hemostasis and Thrombosis|
|Author:||de Maat, Moniek P.M.; van Schie, Marianne; Kluft, Cornelis; Leebeek, Frank W.G.; Meijer, Piet|
|Article Type:||Clinical report|
|Date:||Dec 1, 2016|
|Previous Article:||Generation of Full-Length Class I Human Leukocyte Antigen Gene Consensus Sequences for Novel Allele Characterization.|
|Next Article:||Short-term Variability of Vitamin D-Related Biomarkers.|