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Background  Clinical laboratory tests are important for clinicians to make diagnostic decisions, but discrepancies may directly lead to incorrect diagnosis. We would like to introduce some statistical methods to evaluate the comparability of chemistry analytes while comparing the performances of different measurement systems.    Methods  We used a panel of 10 fresh-frozen single donation serum samples to assess assays for the measurement of glucose and other 13 analytes. Statistical methods used in this article include traditional statistical analysis, robust statistics, regression analysis and differences on medical decision levels (MDL). All the statistical analysis results would be evaluated. 20 Chinese tertiary hospitals accredited to ISO 15189 took part in this work. The commercial random access platforms included: Olympus (8 labs), Hitachi (6 labs) and Roche (6 labs). To compare the acceptable rates, Chi square test was used.    Results  The statistical analysis results are as follows: (1) Coefficient of variations are between 2.8 and 3.9 %, with the slopes and intercepts of regression functions between 0.928 to 1.064 and −0.174 to 0.630, respectively. (2) The percentage of robust  z -scores between −2 and 2 is bigger than 90 %. (3) The total percentages of differences on all the MDLs are: less than optimal was 31.7 % (19/60); less than desirable was 60.0 % (36/60); less than minimum was 65.0 % (39/60); more than minimum was 35.0 % (21/60). In this study, 2 laboratories (Nos. 8 and 16) were considered as poor performance by z-scores. 10 laboratories (Nos. 4, 5, 7, 8, 9, 10, 11, 14, 16 and 19) have unacceptable measurement errors on MDLs. 10 laboratories (Nos. 1, 2, 3, 6, 12, 13, 15, 17, 18, 20) can achieve mutual recognition of serum glucose testing results, including: 5 (5/8) Olympus, 2 (2/6) Hitachi and 3 (3/6) Roche. There was no significant difference among acceptable rates of the three measurements systems for the serum glucose assay.    Conclusions  Traditional statistical analysis, robust statistics and robust z-score, fitting linear regression equations and calculating differences on different MDLs can be used on studying the comparability and mutual recognition of clinical chemistry analytes among hospitals or laboratories in China. The mutual recognition and interchangeability of results remains jeopardized even among tertiary hospitals in China. More works and efforts should be done for improvement of the current situation of interchangeability of results in clinical laboratories in China.

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The study of statistical methods for evaluating the comparability of routine chemistry analytes among 3 routine laboratory measurement systems in China