Browsing by Author "Perich, Carmen"

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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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    Biological variation estimates of thyroid related measurands - meta-analysis of BIVAC compliant studies
    (WALTER DE GRUYTER GMBH, 2022-01-01) Fernandez-Calle, Pilar; Diaz-Garzon, Jorge; Bartlett, William; Sandberg, Sverre; Braga, Federica; Beatriz, Boned; Carobene, Anna; Coskun, Abdurrahman; Gonzalez-Lao, Elisabet; Marques, Fernando; Perich, Carmen; Simon, Margarida; Aarsand, Aasne K.; Variation, E.F.L.M. Working Grp Biol; Database, Task Grp Biol Variation
    Objectives Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. Methods A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. Results The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. Conclusions Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using ``big data{''} instead of the demanding experimental approach.
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    Biological Variation of Cardiac Troponins in Health and Disease: A Systematic Review and Meta-analysis
    (OXFORD UNIV PRESS INC, 2021-01-01) Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ozcurumez, Mustafa; Bartlett, William A.; Coskun, Abdurrahman; Carobene, Anna; Perich, Carmen; Simon, Margarita; Marques, Fernando; Boned, Beatriz; Gonzalez-Lao, Elisabet; Braga, Federica; Aarsand, Aasne K.; Chem, European Federation Clinical; Database, Task Grp Biol Variation
    BACKGROUND: Many studies have assessed the biological variation (BV) of cardiac-specific troponins (cTn), reporting widely varying within-subject BV (CVI) estimates. The aim of this study was to provide metaanalysis-derived BV estimates for troponin I (cTnI) and troponin T (cTnT) for different sampling intervals and states of health. METHODS: Relevant studies were identified by a systematic literature search. Studies were classified according to their methodological quality by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC-compliant studies were performed after stratification by cTn isoform, exclusion of results below the limit of detection, states of health, and sampling interval to deliver reference change values (RCV), index of individuality (II) and analytical performance specifications (APS) for these settings. RESULTS: Sixteen and 15 studies were identified for cTnI and cTnT, respectively, out of which 6 received a BIVAC grade A. Five studies had applied contemporary cTnI assays, but none contemporary cTnT. High-sensitivity (hs-) cTnI and cTnT delivered similar estimates in all settings. Long-term CVI estimates (15.1
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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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    Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters
    (WALTER DE GRUYTER GMBH, 2020-01-01) Coskun, Abdurrahman; Braga, Federica; Carobene, Anna; Tejedor Ganduxe, Xavier; Aarsand, Aasne K.; Fernandez-Calle, Pilar; Diaz-Garzon Marco, Jorge; Bartlett, William; Jonker, Niels; Aslan, Berna; Minchinela, Joana; Boned, Beatriz; Gonzalez-Lao, Elisabet; Marques-Garcia, Fernando; Perich, Carmen; Ricos, Carmen; Simon, Margarita; Sandberg, Sverre; Chem, European Federation Clinical
    Background: Interpretation of the complete blood count (CBC) parameters requires reliable biological variation (BV) data. The aims of this study were to appraise the quality of publications reporting BV data for CBC parameters by applying the BV Data Critical Appraisal Checklist (BIVAC) and to deliver global BV estimates based on BIVAC compliant studies. Methods: Relevant publications were identified by a systematic literature search and evaluated for their compliance with the 14 BIVAC criteria, scored as A, B, C or D, indicating decreasing compliance. Global CVI and CVG estimates with 95\% CI were delivered by a meta-analysis approach using data from BIVAC compliant papers (grades A-C). Results: In total, 32 studies were identified
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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