Systematic review of the biological variation data for diabetes related analytes

Background: Objective interpretation of laboratory test results used to diagnose and monitor diabetes mellitus in part requires the application of biological variation data (BVD). The quality of published BVD has been questioned. The aim of this study was to quality assess publications reporting BVD for diabetes-related analytes using the Biological Variation Data Critical Appraisal Checklist (BIVAC); to assess whether published BVD are fit for purpose and whether the study design and population attributes influence BVD estimates and to undertake a meta-analysis of the BVD from BIVAC-assessed publications. Methods: Publications reporting data for glucose, HbA1c, adiponectin, C-peptide, fructosamine, insulin like growth factor 1 (IGF-1), insulin like growth factor binding protein 3 (IGFBP-3), insulin, lactate and pyruvate were identified using a systematic literature search. These publications were assessed using the BIVAC, receiving grades A, B, C or D, where A is of highest quality. A meta-analysis of the BVD from the assessed studies utilised weightings based upon BIVAC grades and the width of the data confidence intervals to generate global BVD estimates. Results: BIVAC assessment of 47 publications delivered 1 A, 3 B, 39C and 4 D gradings. Publications relating to adiponectin, C-peptide, IGF-1, IGFBP-3, lactate and pyruvate were all assessed as grade C. Meta-analysis enabled global BV estimates for all analytes except pyruvate, lactate and fructosamine. Conclusions: This study delivers updated and evidence-based BV estimates for diabetes-related analytes. There remains a need for delivery of new high-quality BV studies for several clinically important analytes.