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Permanent URI for this collectionhttps://hdl.handle.net/11443/932
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Item Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects(WALTER DE GRUYTER GMBH, 2018-01-01) Coskun, Abdurrahman; Carobene, Anna; Kilercik, Meltem; Serteser, Mustafa; Sandberg, Sverre; Aarsand, Aasne K.; Fernandez-Calle, Pilar; Jonker, Niels; Bartlett, William A.; Diaz-Garzon, Jorge; Huet, Sibel; Kiziltas, Cansu; Dalgakiran, Ilayda; Ugur, Esra; Unsal, Ibrahim; Varia, E.F.L.M. Working Grp BiologicalBackground: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. Methods: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. Results: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. Conclusions: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.Item Personalized reference intervals - statistical approaches and considerations(WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Sandberg, Sverre; Unsal, Ibrahim; Yavuz, Fulya G.; Cavusoglu, Coskun; Serteser, Mustafa; Kilercik, Meltem; Aarsand, Aasne K.For many measurands, physicians depend on population-based reference intervals (popRI), when assessing laboratory test results. The availability of personalized reference intervals (prRI) may provide a means to improve the interpretation of laboratory test results for an individual. prRI can be calculated using estimates of biological and analytical variation and previous test results obtained in a steady-state situation. In this study, we aim to outline statistical approaches and considerations required when establishing and implementing prRI in clinical practice. Data quality assessment, including analysis for outliers and trends, is required prior to using previous test results to estimate the homeostatic set point. To calculate the prRI limits, two different statistical models based on `prediction intervals' can be applied. The first model utilizes estimates of `within-person biological variation' which are based on an individual's own data. This model requires a minimum of five previous test results to generate the prRI. The second model is based on estimates of `within-subject biological variation', which represents an average estimate for a population and can be found, for most measurands, in the EFLM Biological Variation Database. This model can be applied also when there are lower numbers of previous test results available. The prRI offers physicians the opportunity to improve interpretation of individuals' test results, though studies are required to demonstrate if using prRI leads to better clinical outcomes. We recommend that both popRIs and prRIs are included in laboratory reports to aid in evaluating laboratory test results in the follow-up of patients.