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Within-Subject Variability and Analytic Imprecision of Insulinlike Growth Factor Axis and Collagen Markers: Implications for Clinical Diagnosis and Doping Tests
The utility of insulinlike growth factor (IGF) axis and collagen markers for a growth hormone (GH) doping test in sport depends on their stability and reproducibility. We sought to determine short-term within-subject variability of these markers in a large cohort of healthy individuals. We measured...
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Published in: | Clinical chemistry (Baltimore, Md.) Md.), 2008-08, Vol.54 (8), p.1268-1276 |
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creator | Nguyen, Tuan V Nelson, Anne E Howe, Christopher J Seibel, Markus J Baxter, Robert C Handelsman, David J Kazlauskas, Ray Ho, Ken K |
description | The utility of insulinlike growth factor (IGF) axis and collagen markers for a growth hormone (GH) doping test in sport depends on their stability and reproducibility. We sought to determine short-term within-subject variability of these markers in a large cohort of healthy individuals.
We measured IGF-I, IGF binding protein 3 (IGFBP-3), acid labile subunit (ALS), and the collagen markers N-terminal propeptide of type I procollagen (PINP), C-terminal telopeptide of type I collagen (ICTP), and N-terminal propeptide of type III procollagen (PIIINP) in serum samples obtained on multiple occasions (median 3 per participant) over a 2- to 3-week period from 1103 elite athletes (699 men, 404 women) ages 22.2 (5.2) years [mean (SD)]. We estimated between-subject and within-subject variances by mixed-effects ANOVA.
Within-subject variance accounted for 32% to 36% and 4% to 13% of the total variance in IGF markers and collagen markers, respectively. The within-subject CV ranged from 11% to 21% for the IGF axis markers and from 13% to 15% for the collagen markers. The index of individuality for the IGF axis markers was 0.66-0.76, and for the collagen markers, 0.26-0.45. For each marker, individuals with initial extreme measured values tended to regress toward the population mean in subsequent repeated measurements. We developed a Bayesian model to estimate the long-term probable value for each marker.
These results indicate that in healthy individuals the within-subject variability was greater for IGF-I than for the collagen markers, and that where a single measurement is available, it is possible to estimate the long-term probable value of each of the markers by applying the Bayesian approach. Such an application can increase the reliability and decrease the cost of detecting GH doping. |
doi_str_mv | 10.1373/clinchem.2008.105726 |
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We measured IGF-I, IGF binding protein 3 (IGFBP-3), acid labile subunit (ALS), and the collagen markers N-terminal propeptide of type I procollagen (PINP), C-terminal telopeptide of type I collagen (ICTP), and N-terminal propeptide of type III procollagen (PIIINP) in serum samples obtained on multiple occasions (median 3 per participant) over a 2- to 3-week period from 1103 elite athletes (699 men, 404 women) ages 22.2 (5.2) years [mean (SD)]. We estimated between-subject and within-subject variances by mixed-effects ANOVA.
Within-subject variance accounted for 32% to 36% and 4% to 13% of the total variance in IGF markers and collagen markers, respectively. The within-subject CV ranged from 11% to 21% for the IGF axis markers and from 13% to 15% for the collagen markers. The index of individuality for the IGF axis markers was 0.66-0.76, and for the collagen markers, 0.26-0.45. For each marker, individuals with initial extreme measured values tended to regress toward the population mean in subsequent repeated measurements. We developed a Bayesian model to estimate the long-term probable value for each marker.
These results indicate that in healthy individuals the within-subject variability was greater for IGF-I than for the collagen markers, and that where a single measurement is available, it is possible to estimate the long-term probable value of each of the markers by applying the Bayesian approach. Such an application can increase the reliability and decrease the cost of detecting GH doping.</description><identifier>ISSN: 0009-9147</identifier><identifier>EISSN: 1530-8561</identifier><identifier>DOI: 10.1373/clinchem.2008.105726</identifier><identifier>PMID: 18567697</identifier><identifier>CODEN: CLCHAU</identifier><language>eng</language><publisher>Washington, DC: Am Assoc Clin Chem</publisher><subject>Adult ; Analysis of Variance ; Analytical, structural and metabolic biochemistry ; Athletes ; Biological and medical sciences ; Biomarkers - blood ; Clinical Laboratory Techniques - methods ; Clinical Laboratory Techniques - standards ; Cohort Studies ; Collagen - analysis ; Collagen - blood ; Data analysis ; Doping in Sports - prevention & control ; Female ; Fundamental and applied biological sciences. Psychology ; Growth disorders ; Growth Hormone - blood ; Growth hormones ; Humans ; Insulin ; Insulin-Like Growth Factor Binding Protein 3 - blood ; Insulin-Like Growth Factor I - analysis ; Investigative techniques, diagnostic techniques (general aspects) ; Male ; Medical diagnosis ; Medical sciences ; Metabolic disorders ; Minority & ethnic groups ; Sensitivity and Specificity ; Sports - standards ; Substance Abuse Detection - methods ; Substance Abuse Detection - standards ; Variance analysis</subject><ispartof>Clinical chemistry (Baltimore, Md.), 2008-08, Vol.54 (8), p.1268-1276</ispartof><rights>2008 INIST-CNRS</rights><rights>Copyright American Association for Clinical Chemistry Aug 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c439t-bf8994456e2650e930fc0ac8723c351f5075738ecd87eac58141c875828034953</citedby><cites>FETCH-LOGICAL-c439t-bf8994456e2650e930fc0ac8723c351f5075738ecd87eac58141c875828034953</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20551670$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18567697$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nguyen, Tuan V</creatorcontrib><creatorcontrib>Nelson, Anne E</creatorcontrib><creatorcontrib>Howe, Christopher J</creatorcontrib><creatorcontrib>Seibel, Markus J</creatorcontrib><creatorcontrib>Baxter, Robert C</creatorcontrib><creatorcontrib>Handelsman, David J</creatorcontrib><creatorcontrib>Kazlauskas, Ray</creatorcontrib><creatorcontrib>Ho, Ken K</creatorcontrib><title>Within-Subject Variability and Analytic Imprecision of Insulinlike Growth Factor Axis and Collagen Markers: Implications for Clinical Diagnosis and Doping Tests</title><title>Clinical chemistry (Baltimore, Md.)</title><addtitle>Clin Chem</addtitle><description>The utility of insulinlike growth factor (IGF) axis and collagen markers for a growth hormone (GH) doping test in sport depends on their stability and reproducibility. We sought to determine short-term within-subject variability of these markers in a large cohort of healthy individuals.
We measured IGF-I, IGF binding protein 3 (IGFBP-3), acid labile subunit (ALS), and the collagen markers N-terminal propeptide of type I procollagen (PINP), C-terminal telopeptide of type I collagen (ICTP), and N-terminal propeptide of type III procollagen (PIIINP) in serum samples obtained on multiple occasions (median 3 per participant) over a 2- to 3-week period from 1103 elite athletes (699 men, 404 women) ages 22.2 (5.2) years [mean (SD)]. We estimated between-subject and within-subject variances by mixed-effects ANOVA.
Within-subject variance accounted for 32% to 36% and 4% to 13% of the total variance in IGF markers and collagen markers, respectively. The within-subject CV ranged from 11% to 21% for the IGF axis markers and from 13% to 15% for the collagen markers. The index of individuality for the IGF axis markers was 0.66-0.76, and for the collagen markers, 0.26-0.45. For each marker, individuals with initial extreme measured values tended to regress toward the population mean in subsequent repeated measurements. We developed a Bayesian model to estimate the long-term probable value for each marker.
These results indicate that in healthy individuals the within-subject variability was greater for IGF-I than for the collagen markers, and that where a single measurement is available, it is possible to estimate the long-term probable value of each of the markers by applying the Bayesian approach. Such an application can increase the reliability and decrease the cost of detecting GH doping.</description><subject>Adult</subject><subject>Analysis of Variance</subject><subject>Analytical, structural and metabolic biochemistry</subject><subject>Athletes</subject><subject>Biological and medical sciences</subject><subject>Biomarkers - blood</subject><subject>Clinical Laboratory Techniques - methods</subject><subject>Clinical Laboratory Techniques - standards</subject><subject>Cohort Studies</subject><subject>Collagen - analysis</subject><subject>Collagen - blood</subject><subject>Data analysis</subject><subject>Doping in Sports - prevention & control</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Growth disorders</subject><subject>Growth Hormone - blood</subject><subject>Growth hormones</subject><subject>Humans</subject><subject>Insulin</subject><subject>Insulin-Like Growth Factor Binding Protein 3 - blood</subject><subject>Insulin-Like Growth Factor I - analysis</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Male</subject><subject>Medical diagnosis</subject><subject>Medical sciences</subject><subject>Metabolic disorders</subject><subject>Minority & ethnic groups</subject><subject>Sensitivity and Specificity</subject><subject>Sports - standards</subject><subject>Substance Abuse Detection - methods</subject><subject>Substance Abuse Detection - standards</subject><subject>Variance analysis</subject><issn>0009-9147</issn><issn>1530-8561</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNpdkd2OEyEcxSdG49bVNzCGmOjdVBi-vWu67tpkjReuekkoZVq6DFSYydi38VGldnQTrwjwO-f_carqJYJzhDl-Z7wLZme7eQOhmCNIecMeVTNEMawFZehxNYMQyloiwi-qZznvy5VwwZ5WF6gAnEk-q359d_3OhfrLsN5b04NvOjm9dt71R6DDBiyC9sfeGbDqDskal10MILZgFfJQGvDu3oKbFMd-B6616WMCi58u_5Euo_d6awP4pNO9Tfn9ycM7o_vikUFb2GWxKA8eXDm9DTFPyqt4cGEL7mzu8_PqSat9ti-m87L6ev3hbvmxvv18s1oubmtDsOzrdSukJIQy2zAKrcSwNVAbwRtsMEUthZxyLKzZCG61oQIRVH6paATERFJ8Wb09-x5S_DGUyqpz2dgyQrBxyIpJzIgksoCv_wP3cUhlTVk1CEtRKFYgcoZMijkn26pDcp1OR4WgOsWn_sanTvGpc3xF9mryHtad3TyIprwK8GYCdC57a5MOJZN_XAMpRYzDh2l2brsbXbIqd9r7YovUOI6UqFKzYQL_Bl0Cs4A</recordid><startdate>20080801</startdate><enddate>20080801</enddate><creator>Nguyen, Tuan V</creator><creator>Nelson, Anne E</creator><creator>Howe, Christopher J</creator><creator>Seibel, Markus J</creator><creator>Baxter, Robert C</creator><creator>Handelsman, David J</creator><creator>Kazlauskas, Ray</creator><creator>Ho, Ken K</creator><general>Am Assoc Clin Chem</general><general>American Association for Clinical Chemistry</general><general>Oxford University Press</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>4U-</scope><scope>7QO</scope><scope>7RV</scope><scope>7TM</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PCBAR</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>S0X</scope><scope>7X8</scope></search><sort><creationdate>20080801</creationdate><title>Within-Subject Variability and Analytic Imprecision of Insulinlike Growth Factor Axis and Collagen Markers: Implications for Clinical Diagnosis and Doping Tests</title><author>Nguyen, Tuan V ; Nelson, Anne E ; Howe, Christopher J ; Seibel, Markus J ; Baxter, Robert C ; Handelsman, David J ; Kazlauskas, Ray ; Ho, Ken K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-bf8994456e2650e930fc0ac8723c351f5075738ecd87eac58141c875828034953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Adult</topic><topic>Analysis of Variance</topic><topic>Analytical, structural and metabolic biochemistry</topic><topic>Athletes</topic><topic>Biological and medical sciences</topic><topic>Biomarkers - blood</topic><topic>Clinical Laboratory Techniques - methods</topic><topic>Clinical Laboratory Techniques - standards</topic><topic>Cohort Studies</topic><topic>Collagen - analysis</topic><topic>Collagen - blood</topic><topic>Data analysis</topic><topic>Doping in Sports - prevention & control</topic><topic>Female</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Growth disorders</topic><topic>Growth Hormone - blood</topic><topic>Growth hormones</topic><topic>Humans</topic><topic>Insulin</topic><topic>Insulin-Like Growth Factor Binding Protein 3 - blood</topic><topic>Insulin-Like Growth Factor I - analysis</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>Male</topic><topic>Medical diagnosis</topic><topic>Medical sciences</topic><topic>Metabolic disorders</topic><topic>Minority & ethnic groups</topic><topic>Sensitivity and Specificity</topic><topic>Sports - standards</topic><topic>Substance Abuse Detection - methods</topic><topic>Substance Abuse Detection - standards</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nguyen, Tuan V</creatorcontrib><creatorcontrib>Nelson, Anne E</creatorcontrib><creatorcontrib>Howe, Christopher J</creatorcontrib><creatorcontrib>Seibel, Markus J</creatorcontrib><creatorcontrib>Baxter, Robert C</creatorcontrib><creatorcontrib>Handelsman, David J</creatorcontrib><creatorcontrib>Kazlauskas, Ray</creatorcontrib><creatorcontrib>Ho, Ken K</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>University Readers</collection><collection>Biotechnology Research Abstracts</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>Nucleic Acids Abstracts</collection><collection>Toxicology Abstracts</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Science Journals</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Materials science collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>SIRS Editorial</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical chemistry (Baltimore, Md.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nguyen, Tuan V</au><au>Nelson, Anne E</au><au>Howe, Christopher J</au><au>Seibel, Markus J</au><au>Baxter, Robert C</au><au>Handelsman, David J</au><au>Kazlauskas, Ray</au><au>Ho, Ken K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Within-Subject Variability and Analytic Imprecision of Insulinlike Growth Factor Axis and Collagen Markers: Implications for Clinical Diagnosis and Doping Tests</atitle><jtitle>Clinical chemistry (Baltimore, Md.)</jtitle><addtitle>Clin Chem</addtitle><date>2008-08-01</date><risdate>2008</risdate><volume>54</volume><issue>8</issue><spage>1268</spage><epage>1276</epage><pages>1268-1276</pages><issn>0009-9147</issn><eissn>1530-8561</eissn><coden>CLCHAU</coden><abstract>The utility of insulinlike growth factor (IGF) axis and collagen markers for a growth hormone (GH) doping test in sport depends on their stability and reproducibility. We sought to determine short-term within-subject variability of these markers in a large cohort of healthy individuals.
We measured IGF-I, IGF binding protein 3 (IGFBP-3), acid labile subunit (ALS), and the collagen markers N-terminal propeptide of type I procollagen (PINP), C-terminal telopeptide of type I collagen (ICTP), and N-terminal propeptide of type III procollagen (PIIINP) in serum samples obtained on multiple occasions (median 3 per participant) over a 2- to 3-week period from 1103 elite athletes (699 men, 404 women) ages 22.2 (5.2) years [mean (SD)]. We estimated between-subject and within-subject variances by mixed-effects ANOVA.
Within-subject variance accounted for 32% to 36% and 4% to 13% of the total variance in IGF markers and collagen markers, respectively. The within-subject CV ranged from 11% to 21% for the IGF axis markers and from 13% to 15% for the collagen markers. The index of individuality for the IGF axis markers was 0.66-0.76, and for the collagen markers, 0.26-0.45. For each marker, individuals with initial extreme measured values tended to regress toward the population mean in subsequent repeated measurements. We developed a Bayesian model to estimate the long-term probable value for each marker.
These results indicate that in healthy individuals the within-subject variability was greater for IGF-I than for the collagen markers, and that where a single measurement is available, it is possible to estimate the long-term probable value of each of the markers by applying the Bayesian approach. Such an application can increase the reliability and decrease the cost of detecting GH doping.</abstract><cop>Washington, DC</cop><pub>Am Assoc Clin Chem</pub><pmid>18567697</pmid><doi>10.1373/clinchem.2008.105726</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adult Analysis of Variance Analytical, structural and metabolic biochemistry Athletes Biological and medical sciences Biomarkers - blood Clinical Laboratory Techniques - methods Clinical Laboratory Techniques - standards Cohort Studies Collagen - analysis Collagen - blood Data analysis Doping in Sports - prevention & control Female Fundamental and applied biological sciences. Psychology Growth disorders Growth Hormone - blood Growth hormones Humans Insulin Insulin-Like Growth Factor Binding Protein 3 - blood Insulin-Like Growth Factor I - analysis Investigative techniques, diagnostic techniques (general aspects) Male Medical diagnosis Medical sciences Metabolic disorders Minority & ethnic groups Sensitivity and Specificity Sports - standards Substance Abuse Detection - methods Substance Abuse Detection - standards Variance analysis |
title | Within-Subject Variability and Analytic Imprecision of Insulinlike Growth Factor Axis and Collagen Markers: Implications for Clinical Diagnosis and Doping Tests |
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