E Cavalier1,2, P Lukas3, M Bottani4, A K Aarsand5,6,7, F Ceriotti8, A Coşkun7,9, J Díaz-Garzón7,10, P Fernàndez-Calle7,10, E Guerra11, M Locatelli11, S Sandberg5,6,7,12, A Carobene7,11. 1. Department of Clinical Chemistry, University of Liège, CHU de Liège, 4000, Liège, Belgium. Etienne.cavalier@chuliege.be. 2. International Federation of Clinical Chemistry-International Osteoporosis Foundation Committee for Bone Markers, Milan, Italy. Etienne.cavalier@chuliege.be. 3. Department of Clinical Chemistry, University of Liège, CHU de Liège, 4000, Liège, Belgium. 4. IRCCS Istituto Ortopedico Galeazzi, Laboratory of Experimental Biochemistry & Molecular Biology, Milan, Italy. 5. Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway. 6. Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway. 7. Biological Variation Working Group, European Federation of Clinical Chemistry and Laboratory Medicine, Milan, Italy. 8. Clinical Laboratory, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy. 9. School of Medicine, Acibadem Mehmet Ali Aydinlar University, Atasehir, Istanbul, Turkey. 10. Quality Analytical Commission of Spanish Society of Laboratory Medicine (SEQC-ML), Hospital Universitario La Paz, Madrid, Spain. 11. Laboratory Medicine, Ospedale San Raffaele, Milan, Italy. 12. Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Abstract
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 β-isomerized C-terminal telopeptide of type I collagen (β-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: β-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.
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 β-isomerized C-terminal telopeptide of type I collagen (β-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: β-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.
Entities:
Keywords:
Biological variation; Bone markers; CTX; FGF23; MGP; Osteocalcin; PINP; Reference change value
Authors: E Cavalier; R Eastell; N R Jørgensen; K Makris; S Tournis; S Vasikaran; J A Kanis; C Cooper; H Pottel; H A Morris Journal: Calcif Tissue Int Date: 2021-03-04 Impact factor: 4.333
Authors: Michaël R Laurent; Jean De Schepper; Dominique Trouet; Nathalie Godefroid; Emese Boros; Claudine Heinrichs; Bert Bravenboer; Brigitte Velkeniers; Johan Lammens; Pol Harvengt; Etienne Cavalier; Jean-François Kaux; Jacques Lombet; Kathleen De Waele; Charlotte Verroken; Koenraad van Hoeck; Geert R Mortier; Elena Levtchenko; Johan Vande Walle Journal: Front Endocrinol (Lausanne) Date: 2021-03-19 Impact factor: 5.555