The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation. (1st March 2018) - Aarsand, Aasne K; Røraas, Thomas; Fernandez-Calle, Pilar; Ricos, Carmen; Díaz-Garzón, Jorge; Jonker, Niels; Perich, Carmen; González-Lao, Elisabet; Carobene, Anna; Minchinela, Joana; Coşkun, Abdurrahman; Simón, Margarita; et al.
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.