Araştırma Çıktıları
Permanent URI for this communityhttps://hdl.handle.net/11443/931
Browse
17 results
Search Results
Item 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 GrpBACKGROUND: 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 ChemistryItem 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, SverreBackground: 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.Item 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 plasmaItem 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 VariationObjectives 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 markersItem The EuBIVAS: Within- and Between-Subject Biological Variation Data for Electrolytes, Lipids, Urea, Uric Acid, Total Protein, Total Bilirubin, Direct Bilirubin, and Glucose(AMER ASSOC CLINICAL CHEMISTRY, 2018-01-01) Aarsand, Aasne K.; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Guerra, Elena; Locatelli, Massimo; Bartlett, William A.; Sandberg, Sverre; Roraas, Thomas; Ceriotti, Ferruccio; Solvik, Una Orvim; Sylte, Marit Sverresdotter; Coskun, Abdurrahman; Serteser, Mustafa; Unsal, Ibrahim; Tosato, Francesca; Plebani, Mario; Jonker, Niels; Barla, Gerhard; Carobene, Anna; Chem, European Federation ClinicalBACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined data describing biological variation (BV) of clinically important measurands. Here, EuBIVAS-based BV estimates of serum electrolytes, lipids, urea, uric acid, total protein, total bilirubin, direct bilirubin, and glucose, as well as their associated analytical performance specifications (APSs), are presented. METHOD: Samples were drawn from 91 healthy individuals (38 male, 53 femaleItem The European Biological Variation Study (EuBIVAS): a summary report(WALTER DE GRUYTER GMBH, 2022-01-01) Carobene, Anna; Aarsand, Aasne K.; Bartlett, William A.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Guerra, Elena; Jonker, Niels; Locatelli, Massimo; Plebani, Mario; Sandberg, Sverre; Ceriotti, FerruccioBiological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95\% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (Non-HDL Cholesterol, S100-beta protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and \%free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.Item European Biological Variation Study (EuBIVAS): within-and between-subject biological variation estimates for serum biointact parathyroid hormone based on weekly samplings from 91 healthy participants(AME PUBL CO, 2020-01-01) Bottani, Michela; Banfi, Giuseppe; Guerra, Elena; Locatelli, Massimo; Aarsand, Aasne K.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Gonzalez-Lao, Elisabet; Simon, Margarita; Carobene, Anna; Chem, European Federation ClinicalBackground: The European Biological Variation Study (EuBIVAS) was created by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation to establish high-quality biological variation (BV) estimates for clinically important measurands. In this study, the aim was to deliver reliable BV estimates for the biointact parathyroid hormone (PTH 1-84). Methods: Serum samples were obtained from a population of 91 healthy individuals (38 men, 43 premenopausal women, and 10 post-menopausal womenItem Within- and between-subject biological variation data for tumor markers based on the European Biological Variation Study(WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Aarsand, Aasne K.; Sandberg, Sverre; Guerra, Elena; Locatelli, Massimo; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Ceriotti, Ferruccio; Jonker, Niels; Bartlett, William A.; Carobene, Anna; Chem, European Federation ClinicalObjectives: Reliable biological variation (BV) data are required for the clinical use of tumor markers in the diagnosis and monitoring of treatment effects in cancer. The European Biological Variation Study (EuBIVAS) was established by the EFLM Biological Variation Working Group to deliver BV data for clinically important measurands. In this study, EuBIVAS-based BV estimates are provided for cancer antigen (CA) 125, CA 15-3, CA 19-9, carcinoembryonic antigen, cytokeratin-19 fragment, alpha-fetoprotein and human epididymis protein 4. Methods: Subjects from five European countries were enrolled in the study, and weekly samples were collected from 91 healthy individuals (53 females and 38 malesItem Within- and between-subject biological variation data for serum zinc, copper and selenium obtained from 68 apparently healthy Turkish subjects(WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Carobene, Anna; Aarsand, Aasne K.; Aksungar, Fehime B.; Serteser, Mustafa; Sandberg, Sverre; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Karpuzoglu, Fatma H.; Coskun, Cihan; Kizilkaya, Emine; Fidan, Damla; Jonker, Niels; Ugur, Esra; Unsal, Ibrahim; Chem, European Federation Clinical; Database, Task Grp Biol VariationObjectives Trace elements (TrEL) are nutritionally essential components in maintaining health and preventing diseases. There is a lack of reliable biological variation (BV) data for TrELs, required for the diagnosis and monitoring of TrEL disturbances. In this study, we aimed to provide updated within- and between-subject BV estimates for zinc (Zn), copper (Cu) and selenium (Se). Methods Weekly serum samples were drawn from 68 healthy subjects (36 females and 32 males) for 10 weeks and stored at -80 degrees C prior to analysis. Serum Zn, Cu and Se levels were measured using inductively-coupled plasma mass spectrometry (ICP-MS). Outlier and variance homogeneity analyses were performed followed by CV-ANOVA (Roraas method) to determine BV and analytical variation estimates with 95\% CI and the associated reference change values (RCV) for all subjects, males and females. Results Significant differences in mean concentrations between males and females were observed, with absolute and relative (\%) differences for Zn at 0.5 mu mol/L (3.5\%), Cu 2.0 mu mol/L (14.1\%) and Se 0.06 mu mol/L (6.0\%). The within-subject BV (CVI {[}95\% CI]) estimates were 8.8\% (8.2-9.3), 7.8\% (7.3-8.3) and 7.7\% (7.2-8.2) for Zn, Cu and Se, respectively. Within-subject biological variation (CVI) estimates derived for male and female subgroups were similar for all three TrELs. Marked individuality was observed for Cu and Se. Conclusions The data of this study provides updated BV estimates for serum Zn, Cu and Se derived from a stringent protocol and state of the art methodologies. Furthermore, Cu and Se display marked individuality, highlighting that population based reference limits should not be used in the monitoring of patients.Item 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 VariationObjectives 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.