Biological and Analytical Variation of Clinical Biomarker Testing: Implications for Biomarker-guided Therapy
Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CV A ), ranging from 5–20 %. There are also variances within a subject over...
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| Published in | Current heart failure reports Vol. 10; no. 4; pp. 434 - 440 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Boston
Springer US
01.12.2013
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1546-9530 1546-9549 1546-9549 |
| DOI | 10.1007/s11897-013-0156-6 |
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| Abstract | Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CV
A
), ranging from 5–20 %. There are also variances within a subject over time (CV
I
) and between subjects (CV
G
). Variances are determined by experimentation under controlled conditions on healthy subjects. Once measured, the index of individuality (II), reference change value (RCV), and number of samples to establish a homeostatic set point can be calculated. These attributes affect how results of biomarker tests are interpreted in routine clinical practice such as cardiac troponin for acute coronary syndromes, the natriuretic peptides, galectin-3 and sST2 for heart failure, lipids and lipoproteins for primary cardiovascular disease risk, and liver function tests and skeletal muscle biomarkers for detecting complications from statin use. |
|---|---|
| AbstractList | Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CV
A
), ranging from 5–20 %. There are also variances within a subject over time (CV
I
) and between subjects (CV
G
). Variances are determined by experimentation under controlled conditions on healthy subjects. Once measured, the index of individuality (II), reference change value (RCV), and number of samples to establish a homeostatic set point can be calculated. These attributes affect how results of biomarker tests are interpreted in routine clinical practice such as cardiac troponin for acute coronary syndromes, the natriuretic peptides, galectin-3 and sST2 for heart failure, lipids and lipoproteins for primary cardiovascular disease risk, and liver function tests and skeletal muscle biomarkers for detecting complications from statin use. Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CVA), ranging from 5-20 %. There are also variances within a subject over time (CVI) and between subjects (CVG). Variances are determined by experimentation under controlled conditions on healthy subjects. Once measured, the index of individuality (II), reference change value (RCV), and number of samples to establish a homeostatic set point can be calculated. These attributes affect how results of biomarker tests are interpreted in routine clinical practice such as cardiac troponin for acute coronary syndromes, the natriuretic peptides, galectin-3 and sST2 for heart failure, lipids and lipoproteins for primary cardiovascular disease risk, and liver function tests and skeletal muscle biomarkers for detecting complications from statin use.Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CVA), ranging from 5-20 %. There are also variances within a subject over time (CVI) and between subjects (CVG). Variances are determined by experimentation under controlled conditions on healthy subjects. Once measured, the index of individuality (II), reference change value (RCV), and number of samples to establish a homeostatic set point can be calculated. These attributes affect how results of biomarker tests are interpreted in routine clinical practice such as cardiac troponin for acute coronary syndromes, the natriuretic peptides, galectin-3 and sST2 for heart failure, lipids and lipoproteins for primary cardiovascular disease risk, and liver function tests and skeletal muscle biomarkers for detecting complications from statin use. Testing for serum-based biomarkers are essential for diagnosis, risk stratification, and management of patients with cardiovascular disease. All biomarker assays have inherent analytical variability (coefficient of variance CVA), ranging from 5-20 %. There are also variances within a subject over time (CVI) and between subjects (CVG). Variances are determined by experimentation under controlled conditions on healthy subjects. Once measured, the index of individuality (II), reference change value (RCV), and number of samples to establish a homeostatic set point can be calculated. These attributes affect how results of biomarker tests are interpreted in routine clinical practice such as cardiac troponin for acute coronary syndromes, the natriuretic peptides, galectin-3 and sST2 for heart failure, lipids and lipoproteins for primary cardiovascular disease risk, and liver function tests and skeletal muscle biomarkers for detecting complications from statin use. |
| Author | Wu, Alan H. B. |
| Author_xml | – sequence: 1 givenname: Alan H. B. surname: Wu fullname: Wu, Alan H. B. email: wualan@labmed2.ucsf.edu organization: Department of Laboratory Medicine, University of California, San Francisco, San Francisco General Hospital |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24037380$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1093_clinchem_hvaa158 crossref_primary_10_1016_j_clinbiochem_2016_11_028 crossref_primary_10_1373_clinchem_2017_277186 crossref_primary_10_1515_cclm_2020_0046 crossref_primary_10_1515_cclm_2020_1433 crossref_primary_10_1111_jvim_15050 crossref_primary_10_1016_j_jacc_2022_02_043 crossref_primary_10_3390_diagnostics12081930 crossref_primary_10_1161_CIR_0000000000000490 crossref_primary_10_1183_09031936_00011815 crossref_primary_10_1373_jalm_2016_022731 crossref_primary_10_1002_jcla_21984 crossref_primary_10_1111_ctr_14395 crossref_primary_10_1089_omi_2016_0168 crossref_primary_10_1016_j_xcrm_2023_101077 crossref_primary_10_1002_mnfr_201600358 crossref_primary_10_1007_s12170_014_0428_z crossref_primary_10_33176_AACB_19_00032 crossref_primary_10_1093_cvr_cvx183 crossref_primary_10_1007_s00394_016_1295_9 crossref_primary_10_1208_s12248_019_0321_2 crossref_primary_10_1016_j_jcf_2018_11_011 crossref_primary_10_1373_clinchem_2015_251835 crossref_primary_10_23736_S1825_859X_19_00019_7 crossref_primary_10_1161_CIRCULATIONAHA_122_060625 crossref_primary_10_1038_s41598_020_63315_x crossref_primary_10_1530_EC_17_0327 crossref_primary_10_1111_jvim_16619 crossref_primary_10_1373_clinchem_2013_219410 crossref_primary_10_1016_j_jacc_2016_10_020 |
| Cites_doi | 10.1007/s00392-010-0125-y 10.1016/j.cca.2008.12.004 10.1001/archinternmed.2012.3698 10.1373/clinchem.2008.114728 10.1373/clinchem.2009.140616 10.1373/clinchem.2012.191700 10.1016/j.ahj.2013.02.029 10.1373/clinchem.2010.158964 10.1373/clinchem.2004.038752 10.1373/clinchem.2011.171827 10.1373/clinchem.2006.069369 10.1373/49.9.1554 10.1016/S0002-9149(03)00741-0 10.1373/clinchem.2008.107391 10.1093/clinchem/38.6.864 10.1007/s11897-010-0005-9 10.1016/j.ahj.2006.08.021 10.1161/01.CIR.0000052939.59093.45 10.1016/j.cca.2008.09.023 10.1056/NEJMoa0807646 10.1001/jama.2011.1896 10.1161/CIRCULATIONAHA.110.979500 10.1373/clinchem.2011.162545 10.1016/j.cccn.2003.12.032 10.1373/clinchem.2010.161166 10.1016/j.cca.2012.04.010 10.1080/00365519950185229 10.1093/eurheartj/ehs184 |
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| Keywords | Heart failure Biological variation Acute coronary syndromes Analytical variation Cardiovascular disease risk |
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| References | WuAHBSmithACMatherJFDuncanBWhiteCMAhlbergABiological variation for NT-pro- and B-type natriuretic peptides and implications for therapeutic monitoring of patients with congestive heart failureAm J Cardiol200392628311294389410.1016/S0002-9149(03)00741-01:CAS:528:DC%2BD3sXms12isbw%3D KellerTZellerTOjedaFSerial changes in highly sensitive troponin I assay and early diagnosis of myocardial infarctionJAMA201130526849310.1001/jama.2011.1896 Melzi d’ErilGTagnochettiTNautiABiological variation of N-terminal pro-brain natriuretic peptide in healthy individualsClin Chem200349155451292824810.1373/49.9.1554 WuAHBLuAToddJMoecksJWiansFShort- and long-term biological variation in cardiac troponin I with a high-sensitivity assay: implications for clinical practiceClin Chem2009555281898875510.1373/clinchem.2008.1073911:CAS:528:DC%2BD1MXptFaqsw%3D%3D LokDJAVan Der MeerPBrugginkPWPrognostic value of galectin-3, a novel marker of fibrosis, in patients with chronic heart failure: data from 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Markers of inflammation and cardiovascular disease. Application to clinical and public health practice. A statement for healthcare professions from the Centers for Disease Control and Prevention and the American Heart AssociationCirculation20031074995111255187810.1161/01.CIR.0000052939.59093.45 RidkerPMDanielsonEFonsecaFAHfor the JUPITER Study Group: Rosuvastatin to prevent vascular events in men and women with elevated C-reactive proteinN Engl J Med200835921952071899719610.1056/NEJMoa08076461:CAS:528:DC%2BD1cXhtl2gurnL AHB Wu (156_CR22) 2006; 152 J Goldberg (156_CR7) 2011; 57 VC Vasile (156_CR9) 2010; 56 MR Fokkema (156_CR18) 2006; 51 FS Apple (156_CR13) 2009; 55 T Keller (156_CR14) 2011; 305 HN Kim (156_CR21) 2011; 123 S Bruins (156_CR20) 2004; 50 AHB Wu (156_CR25) 2013; 165 PM Ridker (156_CR31) 2008; 359 DJA Lok (156_CR23) 2010; 99 SD Kafonek (156_CR27) 1992; 38 AHB Wu (156_CR33) 2009; 399 K Thygesen (156_CR8) 2012; 33 VC Vasile (156_CR4) 2011; 58 AHB Wu (156_CR11) 2009; 401 CG Fraser (156_CR30) 2004; 346 FS Apple (156_CR6) 2011; 57 F Braga (156_CR28) 2012; 413 AHB Wu (156_CR3) 2009; 55 C Ricos (156_CR26) 1999; 59 AHB Wu (156_CR17) 2003; 92 AHB Wu (156_CR32) 2013; 12 M Mueller (156_CR15) 2012; 58 G Melzi d’Eril (156_CR19) 2003; 49 CG Fraser (156_CR1) 2001 TA Pearson (156_CR29) 2003; 107 L Frankenstein (156_CR5) 2011; 58 RV Shah (156_CR24) 2010; 7 AM Nordenskjold (156_CR10) 2013; 59 SJ Aldous (156_CR12) 2011; 57 T Reichlin (156_CR16) 2012; 172 FS Apple (156_CR2) 2010; 57 16873298 - Clin Chem. 2006 Aug;52(8):1602-3 15345664 - Clin Chem. 2004 Nov;50(11):2052-8 23143329 - Clin Chem. 2013 Feb;59(2):401-9 18988755 - Clin Chem. 2009 Jan;55(1):52-8 22203537 - JAMA. 2011 Dec 28;306(24):2684-93 21555724 - Circulation. 2011 May 10;123(18):2015-9 21519037 - Clin Chem. 2011 Jul;57(7):1068-71 21784766 - Clin Chem. 2011 Aug;57(8):1154-60 1597012 - Clin Chem. 1992 Jun;38(6):864-72 20130888 - Clin Res Cardiol. 2010 May;99(5):323-8 19135041 - Clin Chim Acta. 2009 Mar;401(1-2):170-4 22525742 - Clin Chim Acta. 2012 Aug 16;413(15-16):1179-83 17070141 - Am Heart J. 2006 Nov;152(5):828-34 22922414 - Eur Heart J. 2012 Oct;33(20):2551-67 10667686 - Scand J Clin Lab Invest. 1999 Nov;59(7):491-500 15234632 - Clin Chim Acta. 2004 Aug 2;346(1):19-24 20425491 - Curr Heart Fail Rep. 2010 Mar;7(1):9-14 22134520 - Clin Chem. 2012 Jan;58(1):209-18 18848535 - Clin Chim Acta. 2009 Jan;399(1-2):109-11 20472824 - Clin Chem. 2010 Jul;56(7):1086-90 19478023 - Clin Chem. 2009 Jul;55(7):1303-6 23623945 - Clin Biochem. 2013 Aug;46(12):969-78 22892889 - Arch Intern Med. 2012 Sep 10;172(16):1211-8 12943894 - Am J Cardiol. 2003 Sep 1;92(5):628-31 12928248 - Clin Chem. 2003 Sep;49(9):1554-5 19299542 - Clin Chem. 2009 May;55(5):930-7 18997196 - N Engl J Med. 2008 Nov 20;359(21):2195-207 23708172 - Am Heart J. 2013 Jun;165(6):995-9 12551878 - Circulation. 2003 Jan 28;107(3):499-511 21519039 - Clin Chem. 2011 Jul;57(7):1080-1 |
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| SubjectTerms | Acute Coronary Syndrome - diagnosis Biomarkers - blood Biomarkers of Heart Failure (WHW Tang Cardiac Surgery Cardiology Cardiovascular Diseases - diagnosis Cardiovascular Diseases - drug therapy Diagnostic Techniques, Cardiovascular Diagnostic Tests, Routine Drug Monitoring - methods Humans Imaging Internal Medicine Medicine Medicine & Public Health Radiology Reference Values Risk Assessment - methods Section Editor Troponin - blood Vascular Surgery |
| Title | Biological and Analytical Variation of Clinical Biomarker Testing: Implications for Biomarker-guided Therapy |
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