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Permanent URI for this collectionhttps://hdl.handle.net/11443/932

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Author: search.filters.author.Aslan, BernaHas files: No

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    The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation
    (AMER ASSOC CLINICAL CHEMISTRY, 2018-01-01) Aarsand, Aasne K.; Roraas, Thomas; Fernandez-Calle, Pilar; Ricos, Carmen; Diaz-Garzon, Jorge; Jonker, Niels; Perich, Carmen; Gonzalez-Lao, Elisabet; Carobene, Anna; Minchinela, Joana; Coskun, Abdurrahman; Simon, Margarita; Alvarez, Virtudes; Bartlett, William A.; Fernandez-Fernandez, Pilar; Boned, Beatriz; Braga, Federica; Corte, Zoraida; Aslan, Berna; Sandberg, Sverre; Chem, European Federation Clinical; Variation, Working Grp Biological; Biological, Task \& Finish Grp
    BACKGROUND: Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice. A European Federation of Clinical Chemistry and Laboratory Medicine Task and Finish Group has addressed this issue. The aim of this report is to (a) describe the Biological Variation Data Critical Appraisal Checklist (BIVAC), which verifies whether publications have included all essential elements that may impact the veracity of associated BV estimates, (b) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and (c) apply metaanalysis to deliver a global within-subject BV (CVI) estimate for alanine aminotransferase (ALT). METHODS: In the BIVAC, publications were rated as A, B, C, or D, indicating descending compliance for 14 BIVAC quality items, focusing on study design, methodology, and statistical handling. A D grade indicated that associated BV estimates should not be applied in clinical practice. Systematic searches were applied to identify BV studies for 28 different measurands. RESULTS: In total, 128 publications were identified, providing 935 different BV estimates. Nine percent achieved D scores. Outlier analysis and variance homogeneity testing were scored as C in >60\% of 847 cases. Metaanalysis delivered a CVI estimate for ALT of 15.4\%. CONCLUSIONS: Application of BIVAC to BV publications identified deficiencies in required study detail and delivery, especially for statistical analysis. Those deficiencies impact the veracity of BV estimates. BV data from BIVAC-compliant studies can be combined to deliver robust global estimates for safe clinical application. (c) 2017 American Association for Clinical Chemistry
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    Biological variation data for lipid cardiovascular risk assessment biomarkers. A systematic review applying the biological variation data critical appraisal checklist (BIVAC)
    (ELSEVIER, 2019-01-01) Diaz-Garzon, Jorge; Fernandez Calle, Pilar; Minchinela, Joana; Aarsand, Aasne K.; Bartlett, William A.; Aslan, Berna; Boned, Beatriz; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Gonzalez-Lao, Elisabet; Jonker, Niels; Marques-Garcia, Fernando; Perich, Carmen; Ricos, Carmen; Simon, Margarita; Sandberg, Sverre
    Background: Biological variation (BV) data can be used to set analytical performance specifications (APS) for lipid assays. Poor performance will impact upon the efficacy of international guidelines for cardiovascular risk assessment (CVR) and relevant clinical decision limits. This systematic review applies the Biological Variation Data Critical Appraisal Checklist (BIVAC) to published studies of BV of CVR biomarkers enabling metanalysis of the data. Methods: Studies of BV of total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides and apolipoproteins A(1) and B, retrieved using a systematic literature search, were evaluated and graded using the BIVAC. Meta analysis of CV1 and CVG estimates were performed utilizing weightings based upon BIVAC grades and the width of the data confidence intervals. Results: Applying the BIVAC, ten publications were graded as D, 43 as C, 5 as B and 1 as A (fully compliant). A total of 196 CV1 and 87 CVG estimates were available for the different lipid measurands. The meta-analysis-derived BV data estimates were generally concordant with those in the online 2014 BV database. Conclusions: Application of BIVAC identifies BV data suitable for many important applications including setting APS. Additionally, this review identifies a need for new BIVAC compliant studies to deliver BV reference data in different subpopulations.
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    Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes
    (WALTER DE GRUYTER GMBH, 2022-01-01) Jonker, Niels; Aslan, Berna; Boned, Beatriz; Marques-Garcia, Fernando; Ricos, Carmen; Alvarez, Virtudes; Bartlett, William; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Gonzalez-Lao, Elisabet; Minchinela, Joana; Perich, Carmen; Simon, Margarita; Sandberg, Sverre; Aarsand, Aasne K.
    Objectives Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma
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    Critical review and meta-analysis of biological variation estimates for tumor markers
    (WALTER DE GRUYTER GMBH, 2022-01-01) Marques-Garcia, Fernando; Boned, Beatriz; Gonzalez-Lao, Elisabet; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Carmen Perich, Maria; Simon, Margarida; Jonker, Niels; Aslan, Berna; Bartlett, William Alexander; Sandberg, Sverre; Aarsand, Aasne K.; Chem, European Federation Clinical; Database, Task Grp Biol Variation
    Objectives Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. Methods Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95\% CI. Results The systematic review identified 49 studies delivering results for 22 tumor markers