Generation of data on within-subject biological variation in laboratory medicine: An update.

In recent decades, the study of biological variation of laboratory analytes has received increased attention. The reasons for this interest are related to the potential practical applications of such knowledge. Biological variation data allow the derivation of important parameters for the interpreta...

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Publicado en:Critical Reviews in Clinical Laboratory Sciences Vol. 53; no. 5; pp. 313 - 326
Autores principales: Braga, Federica, Panteghini, Mauro
Formato: algorithm review tables/charts Journal Article
Publicado: Taylor & Francis Ltd Oct2016
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Taylor & Francis Ltd
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        atl: Generation of data on within-subject biological variation in laboratory medicine: An update.
      aug:
        au:
          Braga, Federica
          Panteghini, Mauro
        affil: Centre for Metrological Traceability in Laboratory Medicine (CIRME), University of Milan, Milano, Italy
      sug:
        subj:
          Genotype
          Diagnosis, Laboratory
          Clinical Laboratories
          Reference Values
          Laboratory Test Interference
          Laboratory Test Panels
          Reference Databases
          Checklists
      ab: In recent decades, the study of biological variation of laboratory analytes has received increased attention. The reasons for this interest are related to the potential practical applications of such knowledge. Biological variation data allow the derivation of important parameters for the interpretation and use of laboratory tests, such as the index of individuality for the evaluation of the utility of population reference intervals for the test interpretation, the estimate of significant change in a timed series of results of an individual, the number of specimens required to obtain an accurate estimate of the homeostatic set point of the analyte and analytical performance specifications that assays should fulfill for their application in the clinical setting. It is, therefore, essential to experimentally derive biological variation information in an accurate and reliable way. Currently, a dated guideline for the biological variation data production and a more recent checklist to assist in the correct preparation of publications related to biological variation studies are available. Here, we update and integrate, with examples, the available guideline for biological variation data production to help researchers to comply with the recommendations of the checklist for drafting manuscripts on biological variation. Particularly, we focus on the distribution of the data, an essential aspect to be considered for the derivation of biological variation data. Indeed, the difficulty in deriving reliable estimates of biological variation for those analytes, the measured concentrations of which are not normally distributed, is more and more evident.
      pubtype: Academic Journal
      doctype:
        algorithm
        review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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