Aasne K Aarsand1,2, Thomas Røraas2, Pilar Fernandez-Calle3,4, Carmen Ricos4, Jorge Díaz-Garzón3,4, Niels Jonker5, Carmen Perich4,6, Elisabet González-Lao4,7, Anna Carobene8, Joana Minchinela4,9, Abdurrahman Coşkun10, Margarita Simón4,11, Virtudes Álvarez4, William A Bartlett12, Pilar Fernández-Fernández4, Beatriz Boned4,13, Federica Braga14, Zoraida Corte4,15, Berna Aslan16, Sverre Sandberg17,2,18. 1. Norwegian Porphyria Centre, Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway; aasne.aarsand@helse-bergen.no. 2. Norwegian Quality Improvement of Laboratory Examinations (NOKLUS), Haraldsplass Deaconess Hospital, Bergen, Norway. 3. La Paz University Hospital, Madrid, Spain. 4. Spanish Society of Laboratory Medicine (SEQC-ML), Analytical Quality Commission, Barcelona, Spain. 5. Certe, Wilhelmina Ziekenhuis Assen, Assen, the Netherlands. 6. Clinic Laboratory Hospital Vall d'Hebron, Barcelona, Spain. 7. Catlab, Clinic Laboratory, Mutua Terrassa University Hospital, Barcelona, Spain. 8. Servizio Medicina di Laboratorio, Ospedale San Raffaele, Milan, Italy. 9. Metropolitana Nord Unified Laboratory (LUMN), Germans Trias i Pujol University Hospital, Badalona, Spain. 10. Acibadem University, School of Medicine, Atasehir, Istanbul, Turkey. 11. Laboratory de l'Alt Penedés, l'Anoia i el Garraf, Barcelona, Spain. 12. Blood Sciences, Ninewells Hospital and Medical School, Scotland, UK. 13. Royo Villanova Hospital, Zaragoza, Spain. 14. Research Centre for Metrological Traceability in Laboratory Medicine (CIRME), University of Milan, Milan, Italy. 15. San Agustin University Hospital, Aviles, Asturias, Spain. 16. Institute for Quality Management in Healthcare (IQMH), Centre for Proficiency Testing, Toronto, ON, Canada. 17. Norwegian Porphyria Centre, Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway. 18. Department of Global Health and Primary Care, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway.
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.
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.
Authors: Michela Bottani; Giuseppe Banfi; Elena Guerra; Massimo Locatelli; Aasne K Aarsand; Abdurrahman Coşkun; Jorge Díaz-Garzón; Pilar Fernandez-Calle; Sverre Sandberg; Ferruccio Ceriotti; Elisabet González-Lao; Margarita Simon; Anna Carobene Journal: Ann Transl Med Date: 2020-07