The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation
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 ( ) de...
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Published in | Clinical chemistry (Baltimore, Md.) Vol. 64; no. 3; pp. 501 - 514 |
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Main Authors | , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
01.03.2018
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Subjects | |
Online Access | Get full text |
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Abstract | 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 (
) 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, (
) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and (
) apply metaanalysis to deliver a global within-subject BV (CV
) estimate for alanine aminotransferase (ALT).
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.
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 CV
estimate for ALT of 15.4%.
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. |
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AbstractList | 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). 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. In total, 128 publications were identified, providing 935 different BV estimates. Nine percent achieved Dscores. 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%. 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. Abstract 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. 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 ( ) 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, ( ) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and ( ) apply metaanalysis to deliver a global within-subject BV (CV ) estimate for alanine aminotransferase (ALT). 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. 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 CV estimate for ALT of 15.4%. 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. BACKGROUNDConcern 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). METHODSIn 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. RESULTSIn 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%. CONCLUSIONSApplication 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. |
Author | Álvarez, Virtudes Jonker, Niels Aslan, Berna Carobene, Anna Bartlett, William A Minchinela, Joana Braga, Federica Simón, Margarita Boned, Beatriz Røraas, Thomas Díaz-Garzón, Jorge Coşkun, Abdurrahman Aarsand, Aasne K González-Lao, Elisabet Fernández-Fernández, Pilar Fernandez-Calle, Pilar Sandberg, Sverre Ricos, Carmen Perich, Carmen Corte, Zoraida |
Author_xml | – sequence: 1 givenname: Aasne K surname: Aarsand fullname: Aarsand, Aasne K email: aasne.aarsand@helse-bergen.no organization: Norwegian Quality Improvement of Laboratory Examinations (NOKLUS), Haraldsplass Deaconess Hospital, Bergen, Norway – sequence: 2 givenname: Thomas surname: Røraas fullname: Røraas, Thomas organization: Norwegian Quality Improvement of Laboratory Examinations (NOKLUS), Haraldsplass Deaconess Hospital, Bergen, Norway – sequence: 3 givenname: Pilar surname: Fernandez-Calle fullname: Fernandez-Calle, Pilar organization: Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain – sequence: 4 givenname: Carmen surname: Ricos fullname: Ricos, Carmen organization: Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain – sequence: 5 givenname: Jorge surname: Díaz-Garzón fullname: Díaz-Garzón, Jorge organization: Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain – sequence: 6 givenname: Niels surname: Jonker fullname: Jonker, Niels organization: Certe, Wilhelmina Ziekenhuis Assen, Assen, the Netherlands – sequence: 7 givenname: Carmen surname: Perich fullname: Perich, Carmen organization: Clinic Laboratory Hospital Vall d'Hebron, Barcelona, Spain – sequence: 8 givenname: Elisabet surname: González-Lao fullname: González-Lao, Elisabet organization: Catlab, Clinic Laboratory, Mutua Terrassa University Hospital, Barcelona, Spain – sequence: 9 givenname: Anna surname: Carobene fullname: Carobene, Anna organization: Servizio Medicina di Laboratorio, Ospedale San Raffaele, Milan, Italy – sequence: 10 givenname: Joana surname: Minchinela fullname: Minchinela, Joana organization: Metropolitana Nord Unified Laboratory (LUMN), Germans Trias i Pujol University Hospital, Badalona, Spain – sequence: 11 givenname: Abdurrahman surname: Coşkun fullname: Coşkun, Abdurrahman organization: Acibadem University, School of Medicine, Atasehir, Istanbul, Turkey – sequence: 12 givenname: Margarita surname: Simón fullname: Simón, Margarita organization: Laboratory de l'Alt Penedés, l'Anoia i el Garraf, Barcelona, Spain – sequence: 13 givenname: Virtudes surname: Álvarez fullname: Álvarez, Virtudes organization: Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain – sequence: 14 givenname: William A surname: Bartlett fullname: Bartlett, William A organization: Blood Sciences, Ninewells Hospital and Medical School, Scotland, UK – sequence: 15 givenname: Pilar surname: Fernández-Fernández fullname: Fernández-Fernández, Pilar organization: Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain – sequence: 16 givenname: Beatriz surname: Boned fullname: Boned, Beatriz organization: Royo Villanova Hospital, Zaragoza, Spain – sequence: 17 givenname: Federica surname: Braga fullname: Braga, Federica organization: Research Centre for Metrological Traceability in Laboratory Medicine (CIRME), University of Milan, Milan, Italy – sequence: 18 givenname: Zoraida surname: Corte fullname: Corte, Zoraida organization: San Agustin University Hospital, Aviles, Asturias, Spain – sequence: 19 givenname: Berna surname: Aslan fullname: Aslan, Berna organization: Institute for Quality Management in Healthcare (IQMH), Centre for Proficiency Testing, Toronto, ON, Canada – sequence: 20 givenname: Sverre surname: Sandberg fullname: Sandberg, Sverre organization: Department of Global Health and Primary Care, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29222339$$D View this record in MEDLINE/PubMed |
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Copyright | 2017 American Association for Clinical Chemistry. Copyright American Association for Clinical Chemistry Mar 2018 |
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References | 29301748 - Clin Chem. 2018 Mar;64(3):427-428 Lenters-Westra (2020022606031004900_B26) 2014; 60 Bartlett (2020022606031004900_B11) 2015; 53 Borenstein (2020022606031004900_B13) 2009 Statland (2020022606031004900_B19) 1973; 19 Perich (2020022606031004900_B4) 2015; 53 Braga (2020022606031004900_B32) 2015; 53 2020022606031004900_B25 Burdick (2020022606031004900_B14) 1992 Carobene (2020022606031004900_B28) 2013; 51 Cormen (2020022606031004900_B15) 1989 Tu (2020022606031004900_B17) 1995 Hölzel (2020022606031004900_B22) 1987; 33 Carobene (2020022606031004900_B34) 2017; 63 Panteghini (2020022606031004900_B8) 2015; 53 Carobene (2020022606031004900_B6) 2015; 53 Pineda-Tenor (2020022606031004900_B24) 2013; 51 Weykamp (2020022606031004900_B27) 2011; 57 Roraas (2020022606031004900_B29) 2012; 58 Fraser (2020022606031004900_B7) 2017 Burdick (2020022606031004900_B33) 2005 Bossuyt (2020022606031004900_B35) 2015; 61 Bailey (2020022606031004900_B18) 2014; 60 Simundic (2020022606031004900_B12) 2015; 61 2020022606031004900_B36 2020022606031004900_B16 Biosca (2020022606031004900_B30) 1997; 43 Winkel (2020022606031004900_B21) 1974; 20 Roraas (2020022606031004900_B31) 2016; 62 2020022606031004900_B9 2020022606031004900_B10 Qi (2020022606031004900_B20) 2016; 452 Ricos (2020022606031004900_B3) 1999; 59 2020022606031004900_B2 Fraser (2020022606031004900_B1) 2001 Aarsand (2020022606031004900_B5) 2015; 53 Hölzel (2020022606031004900_B23) 1987; 33 |
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[Editorial] publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2014-1141 contributor: fullname: Aarsand – volume: 61 start-page: 1446 year: 2015 ident: 2020022606031004900_B35 article-title: STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies publication-title: Clin Chem doi: 10.1373/clinchem.2015.246280 contributor: fullname: Bossuyt – volume: 60 start-page: 1570 year: 2014 ident: 2020022606031004900_B26 article-title: Biological variation of hemoglobin a1c: consequences for diagnosing diabetes mellitus publication-title: Clin Chem doi: 10.1373/clinchem.2014.227983 contributor: fullname: Lenters-Westra – start-page: 18 year: 2001 ident: 2020022606031004900_B1 article-title: Biological variation: from principles to practice contributor: fullname: Fraser – volume: 62 start-page: 725 year: 2016 ident: 2020022606031004900_B31 article-title: Biological variation: the effect of different distributions on estimated within-person variation and reference change values publication-title: Clin Chem doi: 10.1373/clinchem.2015.252296 contributor: fullname: Roraas – ident: 2020022606031004900_B16 – volume: 53 start-page: 871 year: 2015 ident: 2020022606031004900_B6 article-title: Reliability of biological variation data available in an online database: need for improvement publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2014-1133 contributor: fullname: Carobene – ident: 2020022606031004900_B10 – volume: 33 start-page: 57 year: 1987 ident: 2020022606031004900_B23 article-title: Intra-individual variation of some analytes in serum of patients with insulin-dependent diabetes mellitus publication-title: Clin Chem doi: 10.1093/clinchem/33.1.57 contributor: fullname: Hölzel – start-page: 157 volume-title: Tietz textbook of clinical chemistry and molecular biology year: 2017 ident: 2020022606031004900_B7 article-title: Biological variation contributor: fullname: Fraser – volume: 51 start-page: 1997 year: 2013 ident: 2020022606031004900_B28 article-title: A systematic review of data on biological variation for alanine aminotransferase, aspartate aminotransferase and gamma-glutamyl transferase publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2013-0096 contributor: fullname: Carobene – volume: 53 start-page: 879 year: 2015 ident: 2020022606031004900_B11 article-title: A checklist for critical appraisal of studies of biological variation publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2014-1127 contributor: fullname: Bartlett – volume: 51 start-page: 851 year: 2013 ident: 2020022606031004900_B24 article-title: Biological variation and reference change values of common clinical chemistry and haematologic laboratory analytes in the elderly population publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2012-0701 contributor: fullname: Pineda-Tenor – volume: 57 start-page: 1204 year: 2011 ident: 2020022606031004900_B27 article-title: The analytical goals for hemoglobin a(1c) measurement in IFCC units and National Glycohemoglobin Standardization program units are different publication-title: Clin Chem doi: 10.1373/clinchem.2011.162719 contributor: fullname: Weykamp – volume: 53 start-page: 829 year: 2015 ident: 2020022606031004900_B8 article-title: Defining analytical performance specifications 15 years after the Stockholm conference. [Editorial] publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2015-0303 contributor: fullname: Panteghini – volume-title: The jackknife and bootstrap year: 1995 ident: 2020022606031004900_B17 contributor: fullname: Tu – volume: 33 start-page: 1133 year: 1987 ident: 2020022606031004900_B22 article-title: Intra-individual variation of analytes in serum from patients with chronic liver diseases publication-title: Clin Chem doi: 10.1093/clinchem/33.7.1133 contributor: fullname: Hölzel – ident: 2020022606031004900_B2 – start-page: 78 volume-title: Statistics: textbooks and monographs year: 1992 ident: 2020022606031004900_B14 article-title: Confidence intervals on variance components contributor: fullname: Burdick – volume: 59 start-page: 491 year: 1999 ident: 2020022606031004900_B3 article-title: Current databases on biological variation: pros, cons and progress publication-title: Scand J Clin Lab Invest doi: 10.1080/00365519950185229 contributor: fullname: Ricos – volume: 58 start-page: 1306 year: 2012 ident: 2020022606031004900_B29 article-title: Confidence intervals and power calculations for within-person biological variation: effect of analytical imprecision, number of replicates, number of samples, and number of individuals publication-title: Clin Chem doi: 10.1373/clinchem.2012.187781 contributor: fullname: Roraas – volume: 452 start-page: 87 year: 2016 ident: 2020022606031004900_B20 article-title: Biological variations of thirteen plasma biochemical indicators publication-title: Clin Chim Acta doi: 10.1016/j.cca.2015.11.008 contributor: fullname: Qi – start-page: 194 year: 1989 ident: 2020022606031004900_B15 article-title: Introduction to algorithms contributor: fullname: Cormen – ident: 2020022606031004900_B36 – volume: 20 start-page: 1520 year: 1974 ident: 2020022606031004900_B21 article-title: Factors contributing to intra-individual variation of serum constituents: 5. Short-term day-to-day and within-hour variation of serum constituents in healthy subjects publication-title: Clin Chem doi: 10.1093/clinchem/20.12.1520 contributor: fullname: Winkel – volume: 53 start-page: 299 year: 2015 ident: 2020022606031004900_B4 article-title: Biological variation database: structure and criteria used for generation and update publication-title: Clin Chem Lab Med doi: 10.1515/cclm-2014-0739 contributor: fullname: Perich – volume: 43 start-page: 2206 year: 1997 ident: 2020022606031004900_B30 article-title: Model for establishing biological variation in non-healthy situations: renal posttransplantation data publication-title: Clin Chem doi: 10.1093/clinchem/43.11.2206 contributor: fullname: Biosca – volume: 61 start-page: 438 year: 2015 ident: 2020022606031004900_B12 article-title: Terms and symbols used in studies on biological variation: the need for harmonization publication-title: Clin Chem doi: 10.1373/clinchem.2014.233791 contributor: fullname: Simundic |
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Snippet | Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice. A European... Abstract BACKGROUND Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical... BACKGROUNDConcern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice.... |
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SubjectTerms | Alanine Alanine transaminase Biological effects Biological variation Clinical medicine Data processing Diabetes Diabetes mellitus Documents Enzymes Estimates Homogeneity Impact analysis Laboratories Lipids Older people Statistical analysis Statistics Studies Variance analysis Variation Working groups |
Title | The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation |
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