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

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. 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. 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. 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.