Glycated haemoglobin HbA1c or HbA1: expression of results

Abstract

We have been made aware of the importance of glycated haemoglobin results now the DCCT results have been published. We need to know these measurements both for individual patients and for clinic populations so that we can compare the results of treatment and education. We need to know the significance of a patient's results so that we can suitably inform him. This is possible for all centres so long as centres can accurately compare their glycated haemoglobin results with those from the DCCT. In this issue Dr E H McLaren's group' uses the technique of Standard Deviation Scores (SDS) to do this. I thought this was so important that it deserved further comment. There are many different methods of measuring glycated haemoglobin. These different methods affect the results. The method used to collect the blood also alters the resultss.s. The reference intervals (normal ranges) differ widely from laboratory to laboratory, The consequence of all of these factors is that it is difficult to compare results between centres. The SDS should allow accurate comparison but only if performed correctly. To understand SDS you must first understand Standard Deviation. This is a way of quantifying variability. One Standard Deviation is roughly the average distance from the mean of all the observations made in a normal population. It is written ±1 SD. About 95% of a normally distributed population will fall between ±2 SD of the mean, and a little over 99% fall between ±3 SD. The number of Standard Deviations away from the mean allows a score to be produced: the SDS. To use the SDS the data must have a 'normal distribution'. Provided sufficient samples have been taken, a simple histogram will demonstrate if the distribution is normal or if the data are skewed. If the data are positively skewed there are a few very high values, but most fall in the lower levels. Another simple way to see if the data are skewed is to find the midpoint between the highest and the lowest values found in a population; this is called the median. This should be approximately the same as the mean (average). The data from many biological variables are positively skewed. The term 'reference population' is preferable to 'normal population' since it should consist of a large number of healthy individuals, as far as is known. People with diabetes who are not ill could be included, for instance. If these were included then glycated haemoglobin values would be positively skewed. Most positively skewed data require transformation before a reliable standard deviation can be found. This is particularly important for the SDS used to quantitate