Pilar Fernández-Calle1,2, Jorge Díaz-Garzón1,2, William Bartlett3, Sverre Sandberg4, Federica Braga5, Boned Beatriz1,6, Anna Carobene7, Abdurrahman Coskun8, Elisabet Gonzalez-Lao1, Fernando Marques1,9, Carmen Perich1, Margarida Simon1,10, Aasne K Aarsand11. 1. Analytical Quality Commission, Spanish Society of Laboratory Medicine (SEQCML), Barcelona, Spain. 2. Department of Laboratory Medicine, Hospital Universitario La Paz, Madrid, Spain. 3. Undergraduate Teaching, School of Medicine, University of Dundee, Dundee, Scotland. 4. Department of Medical Biochemistry and Pharmacology, Norwegian Organization for Quality Improvement of Laboratory Examinations (NOKLUS), Haukeland University Hospital, Bergen, Norway. 5. Research Centre for Metrological Traceability in Laboratory Medicine (CIRME), University of Milan, Milan, Italy. 6. Department of Laboratory Medicine, Hospital Royo Villanova, Zaragoza, Spain. 7. Servizio Medicina di Laboratorio, Ospedale San Raffaele, Milan, Italy. 8. Department of Medical Biochemistry Atasehir, School of Medicine, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey. 9. Clinical Biochemistry Department, Metropolitan North Clinical Laboratory (LUMN), Germans Trias i Pujol University Hospital, Barcelona, Spain. 10. Department of Clinical Biochemistry, Hospital Universitario Badalona, Badalona, Spain. 11. Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway.
Abstract
OBJECTIVES: Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. METHODS: A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. RESULTS: The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. CONCLUSIONS: Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using "big data" instead of the demanding experimental approach.
OBJECTIVES: Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. METHODS: A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. RESULTS: The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. CONCLUSIONS: Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using "big data" instead of the demanding experimental approach.