Abstract
For biological variation (BV) data to be safely used, data must be reliable and relevant to the population in which they are applied. We used samples from the European Biological Variation Study (EuBIVAS) to determine BV of coagulation markers by a Bayesian model robust to extreme observations and used the derived within-participant BV estimates [CVP(i)] to assess the applicability of the BV estimates in clinical practice. Plasma samples were drawn from 92 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate for activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen, D-dimer, antithrombin (AT), protein C, protein S free, and factor VIII (FVIII). A Bayesian model with Student t likelihoods for samples and replicates was applied to derive CVP(i) and predicted BV estimates with 95% credibility intervals. For all markers except D-dimer, CVP(i) were homogeneously distributed in the overall study population or in subgroups. Mean within-subject estimates (CVI) were <5% for APTT, PT, AT, and protein S free, <10% for protein C and FVIII, and <12% for fibrinogen. For APTT, protein C, and protein S free, estimates were significantly lower in men than in women ≤50 years. For most coagulation markers, a common CVI estimate for men and women is applicable, whereas for APTT, protein C, and protein S free, sex-specific reference change values should be applied. The use of a Bayesian model to deliver individual CVP(i) allows for improved interpretation and application of the data.
Highlights
Coagulation markers play a central role in a variety of clinical settings, such as evaluation of a patient presenting with suspected thromboembolism or increased bleeding tendency, monitoring anticoagulant therapies, evaluation of liver function, and as risk assessment markers
Our work has shown that a Bayesian model applying an adaptive Student t distribution is robust to extreme observations and does not require variance homogeneity to provide relevant results [8]
For activated partial thromboplastin time (APTT) (Fig. 1) and protein C (Fig. 3), the Harris– Brown ratio indicated homogeneous data, but CVI estimates were lower in men than in women below 50 years (Table 1, Fig. 5)
Summary
Coagulation markers play a central role in a variety of clinical settings, such as evaluation of a patient presenting with suspected thromboembolism or increased bleeding tendency, monitoring anticoagulant therapies, evaluation of liver function, and as risk assessment markers. BV data are used to set analytical quality specifications (APS), to assess changes in a measurement series within an individual by the reference change value (RCV) [1], to examine the use of population-based reference intervals [2], and to derive personalized reference intervals [3]. For these applications, BV estimates must be reliable and representative for the populations to which they are applied. We used samples from the European Biological Variation Study (EuBIVAS) to determine BV of coagulation markers by a Bayesian model robust to extreme observations and used the derived within-participant BV estimates [CVP(i)] to assess the applicability of the BV estimates in clinical practice
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