Longitudinal analysis of laboratory tests in a population-based study

Abstract

Clinical laboratories must have quality management systems that guarantee the reliability of their results. Furthermore, in longitudinal studies, it is important that the generated data be analyzed over time, as an additional measure of quality control (QC), seeking to identify fluctuations not explainable by biological variables. Applying this strategy to the SHIP-Brazil study was the aim of this work. Thus, we analyzed the results of fasting glucose, post-load glucose and glycated hemoglobin in the participants of the SHIP-Brazil study, from July 2014 to November 2016, in relation to the following aspects: difference of each individual's results from the mean of the month over time, mean and median of results over time, and percentage of results above the reference values over time, with trend line. According to the observed data, in order to guarantee the correct association of laboratory parameters with different health and disease conditions, the fasting blood glucose and post-load glucose measurements in the samples collected during the first months of the study are consistent, despite being performed in two different facilities. This QC strategy has proved very useful, and may even be used by clinical laboratories in their routine, observing result fluctuations of their population in the course of time, being capable of eventually detect bias even before the routine practices of internal and external quality control.