Q: Why do different labs have different ranges for their blood work? The local oncology lab has a Creatinine high range of 1.4 while the lab of a Myeloma specialist has a high level of 1.1. Is it the average of the patients with that same disease that are tested there?

A:Any biological parameter that is measured in a population needs a defined physiological or ‘normal’ range. But every test is affected by pre-analytical variables like technique and timing of blood collection, posture of patient and the transport and storage of specimens. Then there are variations in the analytic technique which impact on the test result. But most of these can be standardised. Problem is caused by inherent factors of age, sex, body build, occupation, genetic background, diet, altitude of residence etc., which affect test values. All these variables have to be taken into account while defining ‘normal’ values. A reference interval is typically established by assaying specimens that are obtained from individuals that meet carefully defined criteria (reference sample group). It is difficult to be certain in any survey of a population for the purpose of obtaining data from which ‘normal’ ranges are established that ‘normal’ subjects are completely healthy. Analyte values for the normal and abnormal will overlap, and a value within the recognised normal range may be definitely pathological in a particular subject. For this reason the concept of ‘normal ranges’ or ‘normal values’ has been replaced by ‘reference limits’ and ‘reference values’ in which the variables are defined when establishing the values for a reference population. For any test, the range between the reference limits is called the reference interval and ideally each laboratory should establish its own. This is typically established by analysing a minimum of 120 reference samples. For example, to establish a reference interval for hemoglobin - a test that is gender dependent - the laboratory would need to obtain hemoglobin results on 240 reference individuals (120 men and 120 women). These individuals are typically recruited from the general regional population and then selected for inclusion in the study using carefully defined criteria. The selection is often accomplished by administering a health questionnaire. Sometimes a physical examination is also required as a way to determine acceptability for inclusion. The data generated is assumed to fit a specified type of statistical pattern, either symmetric (also called normal or Gaussian distribution) or asymmetric with a skewed distribution – to the left or right. If a range of observations is used and sampling is carried on, eventually some observations will be outside it, and the range will get bigger and bigger. To avoid this, a range between two quantiles is used, usually the 2.5 centile and the 97.5 centile, which is called the normal range, 95% reference range, or 95% reference interval. This leaves 5% of normals outside the `normal range', which is the set of values within which 95% of measurements from apparently healthy individuals will lie. In other words, in a statistically normal distribution of data (and most biological analytes have normal distribution), most observations will fall within two standard deviations of the mean with 2.5% below and 2.5% above it. A normal value will be the Mean + 2 S.D. (as defined by the lab). Each lab must define its reference interval as the reagents / kits / instruments etc. vary from lab to lab.