A model for calculating the within-subject biological variation and likelihood ratios for analytes with a time-dependent change in concentrations; exemplified with the use of D-dimer in suspected venous thromboembolism in healthy pregnant women

Abstract

Background: Within-subject biological variation and reference change value (RCV) are difficult to calculate for an analyte with a changing concentration. The aim of this study was to develop a model to examine if it was possible to transform an analyte with a time-dependent change in concentration into a 'steady-state' situation by the use of 'multiples of the median' (MoM) and its natural logarithm (lnMoM). In addition, we wanted to extend the RCV concept, using likelihood and odds ratios, to calculate the post-test probabilities for disease. D-dimer in pregnancy is used as an example. Methods: Blood samples from 18 healthy pregnant and 18 healthy non-pregnant women were collected every fourth week. MoM of the D-dimer concentrations was calculated for each four-week interval to obtain a 'steady-state' situation for the D-dimer concentrations. The 'normalized' values were then transformed to the lnMoM to obtain a Gaussian distribution, used for the estimation of biological variation. Results: Median D-dimer concentrations increased six-fold during pregnancy. Within-subject variation (SD) of lnMoM D-dimer was 0.27 during pregnancy and 0.23 in non-pregnant women, with RCVs of 0.72 and 0.90, respectively. Conclusions: By using the lnMoM model, an increasing concentration of an analyte can be transformed to a steady-state situation and the within-subject biological variation and its derived parameters can be calculated.

Biological Variation: The Effect of Different Distributions on Estimated Within-Person Variation and Reference Change Values

“…This assumption is covered by the independence of observations assumption: i.e., there is no autocorrelation between observations. If data from all individuals are not in a steady state but can be transformed to have a homoscedastic trend, adjustment for the trend is achievable by use of a suitable ANOVA model (analysis of covariance or generalized linear models) or by transforming data or adjusting the interpretation of the results (5,6 ).…”

Concentration of fibrin monomer in pregnancy and during the postpartum period

“…Other characteristics of the participating women and their health status during pregnancy can be found in earlier papers. 19–21 Study participants were recruited by an advertisement in the local newspaper and on the webpage of Haukeland University Hospital. The Regional Committee of Medical Ethics of Western Norway approved the study (Project number 3.2006.1869/REK Vest 2010/221), and the women gave informed consent to participate.…”

“…24,25 Confidence intervals (95%) were calculated according to Burdick and Graybill. 26 Testing for variance homogeneity was performed as described in detail in earlier publications 19–21 and was performed by Bartlett’s test (statistical significance, P < 0.01). 27 Variance homogeneity was illustrated on a rankit scale where the cumulated ranked coefficients of variation were plotted as fractions on the ordinate as function of the personal values of the variation, SD P or CV P .…”

“…This was compared with the theoretical χ 2 function for homogenous distribution of CV values: pooled CV P ·√χ 2 /df shown on the same rankit scale using the mean degrees of freedom (df) for series of results from each woman (Supplemental Figure 2). 19,23,28–30…”

Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference

“…Several measurands in the database developed by Ricos' group [29] present such characteristics and should temporarily be placed to model 3 while waiting for better studies or for different mathematical approaches, e.g. as proposed in [30] for D-dimer.…”