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      Study of reference values and biological variation: a necessity and a model for Preventive Medicine Centers.

      Clinical chemistry and laboratory medicine : CCLM / FESCC
      Adult, Blood Chemical Analysis, standards, Clinical Chemistry Tests, Clinical Laboratory Techniques, Decision Support Techniques, Early Diagnosis, Female, Humans, Male, Middle Aged, Models, Statistical, Predictive Value of Tests, Preventive Medicine, methods, Reference Values, Statistical Distributions

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          Abstract

          Laboratory tests were at the origin of the modern approach to the evaluation of the health status in many Preventive Medicine Centers. Guided by the theory of reference values and its applications, years of efforts have been devoted to defining the health status of people, and understanding the biological variation of the population. At the Nancy Center for Preventive Medicine, 40,000 people are invited every year for health examination; many coming with their families. French legislation authorized every citizen to have full health examination every five years. Annually, 600,000 people are seen at 70 centers. The visit includes answering questionnaires, physiological and biological testing modified for age, risks, and social criteria. The process concludes with consultation with a general practitioner. Data accumulated over 30 years have led to the identification of primary factors influencing biological variation of common laboratory tests. For example, body mass index (BMI) has to be considered, in addition to age and gender, for measurement of gamma-glutamyltransferase, alanine aminotransferase, and other analytes. More recently, the familial Stanislas cohort has shown that apolipoprotein E (apoE) genetic polymorphism has to be considered as a factor for variation in some individuals. For example, there was greater than 100% difference in the mean concentration of apoE between epsilon2/epsilon2 and epsilon4/epsilon4 individuals. This example nicely illustrates the relationship between genotype and phenotype. Demonstrating the effects of multiple gene polymorphisms on phenotypes will be a valid approach to predictive laboratory medicine.

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