Managing biological variation data: modern approaches for study design and clinical application
| Autor: | J. Rex Astles, Shahram Shahangian, Paul R Johnson |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
Biochemistry (medical) Clinical Biochemistry Principal (computer security) Retrospective cohort study 030204 cardiovascular system & hematology Data science General Biochemistry Genetics and Molecular Biology Checklist 03 medical and health sciences 0302 clinical medicine Key terms 030220 oncology & carcinogenesis Biological variation Information system Humans Prospective Studies Sample collection Laboratories Biomarkers Retrospective Studies Cohort study |
| Zdroj: | Critical Reviews in Clinical Laboratory Sciences. 58:493-512 |
| ISSN: | 1549-781X 1040-8363 |
| DOI: | 10.1080/10408363.2021.1932718 |
| Popis: | For more than one half-century, variability observed in clinical test result measurements has been ascribed to three major independent factors: (i) pre-analytical variation, occurring at sample collection and processing steps; (ii) analytical variation of the test method for which measurements are taken, and; (iii) biological variation (BV). Appreciation of this last source of variability is the major goal of this review article. Several recent advances have been made to generate, collate, and utilize BV data of biomarker tests within the clinical laboratory setting. Consideration of both prospective and retrospective study designs will be addressed. The prospective/direct study design will be described in accordance with recent recommendations discussed in the framework of a newly-developed system of checklist items. Potential value of retrospective/indirect study design, modeled on data mining from cohort studies or pathology laboratory information systems (LIS), offers an alternative approach to obtain BV estimates for clinical biomarkers. Moreover, updates to BV databases have made these data more current and widely accessible. Principal aims of this review are to provide the clinical laboratory scientist with a historical framework of BV concepts, to highlight useful applications of BV data within the clinical laboratory environment, and to discuss key terms and concepts related to statistical treatment of BV data. |
| Databáze: | OpenAIRE |
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