European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates of ß-isomerized C-terminal telopeptide of type I collagen (ß-CTX), N-terminal propeptide of type I collagen (PINP), osteocalcin, intact fibroblast growth factor 23 and uncarboxylated-unphosphorylated matrix-Gla protein-a cooperation between the EFLM Working Group on Biological Variation and the International Osteoporosis Foundation-International Federation of Clinical Chemistry Committee on Bone Metabolism.

We have calculated the biological variation (BV) of different bone metabolism biomarkers on a large, well-described cohort of subjects. BV is important to calculate reference change value (or least significant change) which allows evaluating if the difference observed between two consecutive measurements in a patient is biologically significant or not. INTRODUCTION: Within-subject (CVI) and between-subject (CVG) biological variation (BV) estimates are essential in determining both analytical performance specifications (APS) and reference change values (RCV). Previously published estimates of BV for bone metabolism biomarkers are generally not compliant with the most up-to-date quality criteria for BV studies. We calculated the BV and RCV for different bone metabolism markers, namely ß-isomerized C-terminal telopeptide of type I collagen (ß-CTX), N-terminal propeptide of type I collagen (PINP), osteocalcin (OC), intact fibroblast growth factor 23 (iFGF-23), and uncarboxylated-unphosphorylated Matrix-Gla Protein (uCuP-MGP) using samples from the European Biological Variation Study (EuBIVAS). METHODS: In the EuBIVAS, 91 subjects were recruited from six European laboratories. Fasting blood samples were obtained weekly for ten consecutive weeks. The samples were run in duplicate on IDS iSYS or DiaSorin Liaison instruments. The results were subjected to outlier and variance homogeneity analysis before CV-ANOVA was used to obtain the BV estimates. RESULTS: We found no effect of gender upon the CVI estimates. The following CVI estimates with 95% confidence intervals (95% CI) were obtained: ß-CTX 15.1% (14.4-16.0%), PINP 8.8% (8.4-9.3%), OC 8.9% (8.5-9.4%), iFGF23 13.9% (13.2-14.7%), and uCuP-MGP 6.9% (6.1-7.3%). CONCLUSIONS: The EuBIVAS has provided updated BV estimates for bone markers, including iFGF23, which have not been previously published, facilitating the improved follow-up of patients being treated for metabolic bone disease.

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.