Indirect reference intervals of plasma and serum thyrotropin (TSH) concentrations from intra-laboratory data bases from several German and Italian medical centres

Background: The dogma of establishing intra-laboratory reference limits (RLs) and their periodic review cannot be fulfilled by most laboratories due to the expenses involved. Thus, most laboratories adopt external sources for their RLs, often neglecting the problems of transferability. This is particularly problematic for analytes with a large diversity of existing RLs, as for example thyrotropin (TSH). Several attempts were taken to derive RLs from the large data pools stored in modern laboratory information systems. These attempts were further developed to a more sophisticated indirect procedure. The new approach can be considered a combined concept because it pre-excludes some subjects by direct criteria a-posterior. In the current study, the applicability of the new concept for modern protein bindings assays was examined for estimating RLs of serum and plasma TSH with data sets from several German and Italian laboratories. Methods: A smoothed kernel density function was estimated for the distribution of the total mixed data of the sample group (combined data of non-diseased and diseased subjects). It was assumed that the "central" part of the distribution of all data represents the non-diseased ("healthy'") population. The central part was defined by truncation points using an optimisation method, and was used to estimate a Gaussian distribution of the values of presumably non-diseased subjects after Box-Cox transformation of the empirical data. This distribution was now considered as the distribution of the non-diseased subgroup. The percentiles of this parametrical distribution were calculated to obtain RLs. Results: RLs determined by the indirect combined decomposition technique led to similar RLs as found by several recent study reports using a direct method according to international recommendations. Furthermore, the RLs obtained from 13 laboratories in two different European regions reflected the well-known differences of various analytical procedures. Stratification for gender and age was necessary in contrast to earlier reports. With increasing age, an increase of the upper RL and the reference range was observed. Hospitalisation also affected the RLs. Common RLs appeared acceptable only within the same analytical systems. Some laboratories used RLs which were not appropriate for the population served. Conclusions: The proposed strategy of combining exclusion criteria with a resolution technique led to retrospective RLs from intra-laboratory data pools for TSH which were comparable with directly determined RLs. Differences between laboratories were due primarily to the well-known bias of the different analytical procedures and to the status of the population.