Procedures for assessing the uncertainty in measurement and estimates of biological variation are currently available for many measurands capable of direct analytical measurement. However, not all measurands or quantity values determined in a medical laboratory are provided by direct analytical measurement. Estimated glomerular filtration rate (eGFR) is such a quantity value. In this situation, the result is calculated from other measurements through a functional relationship in which the output value (the calculated quantity value) is derived from one or more input quantities by applying a defined mathematical equation. The aims of this review are: to summarise the principal methods for assessing uncertainty in measurement in complicated non-linear expressions; and to describe an approach for estimating the uncertainty in measurement and biological variation of the Chronic Kidney Disease Epidemiology Collaboration equations for eGFR. In practice, either the direct application of the propagation of uncertainty in measurement equation or a Monte Carlo simulation procedure using a readily available spreadsheet may be used to evaluate uncertainty in measurement or the propagation of biological variation. If the only recognised "uncertainty" is the biological variation in the measured serum creatinine, the equation for the propagation of uncertainties in measurement for the eGFR simplifies to an expression in which the coefficient of variation of the eGFR (or the biological variation of the eGFR) is directly proportional to the coefficient of variation of the measured serum creatinine (or the biological variation of the serum creatinine).
Keywords: Biological variation; EGFR; Estimated glomerular filtration rate; Measurement uncertainty; Monte Carlo simulation; Serum creatinine uncertainty in measurement.