Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease. We studied the associations and risk prediction of 11 plasma and...
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| description | The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease.
We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006-2010, with up to 48- and 9-years follow-up, respectively.
In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P |
| doi_str_mv | 10.1371/journal.pone.0241558 |
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We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006-2010, with up to 48- and 9-years follow-up, respectively.
In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P<0.0001, except bilirubin P<0.005). For calcium, blood urea nitrogen, bilirubin, hematocrit, uric acid, and iron, U-shaped associations were seen (P<0.0001). For leukocyte count, gamma-glutamyl transferase, alkaline phosphatases and lactate dehydrogenase, linear positive associations were seen, while for albumin the association was negative. Similar associations were seen in UKB. Addition of all biomarkers to a model with classical risk factors improved mortality prediction (delta C-statistics: +0.009 in X69 and +0.023 in UKB, P<0.00001 in both cohorts).
Commonly used clinical chemistry tests were associated with all-cause mortality both in the medium- and long-term perspective, and improved mortality prediction beyond classical risk factors. Since both linear and U-shaped relationships were found, we propose to define the normal range of a clinical chemistry test based on its association with mortality, rather than from the distribution.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0241558</identifier><identifier>PMID: 33152050</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Age ; Albumins ; Authorship ; Bilirubin ; Biobanks ; Biological markers ; Biological Specimen Banks ; Biology and Life Sciences ; Biomarkers ; Biomarkers - blood ; Blood pressure ; Body mass index ; Calcium ; Calcium (blood) ; Chemistry ; Clinical chemistry ; Clinical Chemistry Tests - methods ; Cohort analysis ; Cohort Studies ; Diabetes ; Evaluation ; Fasting ; Forecasts and trends ; Glucose ; Health risks ; Hematocrit ; Humans ; Identification and classification ; Kaplan-Meier Estimate ; L-Lactate dehydrogenase ; Laboratories ; Lactate dehydrogenase ; Lactic acid ; Leukocytes ; Medical screening ; Medicine ; Medicine and Health Sciences ; Mortality ; Observations ; Physical Sciences ; Predictions ; Principal Component Analysis ; Reproducibility of Results ; Research and Analysis Methods ; Risk analysis ; Risk Factors ; Test validity ; Urea ; Uric acid ; Variables ; Young Adult ; γ-Glutamyltransferase</subject><ispartof>PloS one, 2020-11, Vol.15 (11), p.e0241558-e0241558</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Lind et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Lind et al 2020 Lind et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c729t-81652956cdef3e9a2d061e0a56c35d62551a7aa24bd5410d5295a68d012dccd13</citedby><cites>FETCH-LOGICAL-c729t-81652956cdef3e9a2d061e0a56c35d62551a7aa24bd5410d5295a68d012dccd13</cites><orcidid>0000-0002-1225-1021</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644047/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644047/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,550,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33152050$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-430537$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><contributor>Guo, Yiru</contributor><creatorcontrib>Lind, Lars</creatorcontrib><creatorcontrib>Zanetti, Daniela</creatorcontrib><creatorcontrib>Högman, Marieann</creatorcontrib><creatorcontrib>Sundman, Lars</creatorcontrib><creatorcontrib>Ingelsson, Erik</creatorcontrib><title>Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease.
We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006-2010, with up to 48- and 9-years follow-up, respectively.
In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P<0.0001, except bilirubin P<0.005). For calcium, blood urea nitrogen, bilirubin, hematocrit, uric acid, and iron, U-shaped associations were seen (P<0.0001). For leukocyte count, gamma-glutamyl transferase, alkaline phosphatases and lactate dehydrogenase, linear positive associations were seen, while for albumin the association was negative. Similar associations were seen in UKB. Addition of all biomarkers to a model with classical risk factors improved mortality prediction (delta C-statistics: +0.009 in X69 and +0.023 in UKB, P<0.00001 in both cohorts).
Commonly used clinical chemistry tests were associated with all-cause mortality both in the medium- and long-term perspective, and improved mortality prediction beyond classical risk factors. Since both linear and U-shaped relationships were found, we propose to define the normal range of a clinical chemistry test based on its association with mortality, rather than from the distribution.</description><subject>Age</subject><subject>Albumins</subject><subject>Authorship</subject><subject>Bilirubin</subject><subject>Biobanks</subject><subject>Biological markers</subject><subject>Biological Specimen Banks</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Blood pressure</subject><subject>Body mass index</subject><subject>Calcium</subject><subject>Calcium (blood)</subject><subject>Chemistry</subject><subject>Clinical chemistry</subject><subject>Clinical Chemistry Tests - methods</subject><subject>Cohort analysis</subject><subject>Cohort Studies</subject><subject>Diabetes</subject><subject>Evaluation</subject><subject>Fasting</subject><subject>Forecasts and trends</subject><subject>Glucose</subject><subject>Health risks</subject><subject>Hematocrit</subject><subject>Humans</subject><subject>Identification and classification</subject><subject>Kaplan-Meier Estimate</subject><subject>L-Lactate dehydrogenase</subject><subject>Laboratories</subject><subject>Lactate dehydrogenase</subject><subject>Lactic acid</subject><subject>Leukocytes</subject><subject>Medical screening</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Mortality</subject><subject>Observations</subject><subject>Physical Sciences</subject><subject>Predictions</subject><subject>Principal Component Analysis</subject><subject>Reproducibility of Results</subject><subject>Research and Analysis Methods</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>Test validity</subject><subject>Urea</subject><subject>Uric acid</subject><subject>Variables</subject><subject>Young Adult</subject><subject>γ-Glutamyltransferase</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNqNk12LEzEUhgdR3HX1H4gGBFGwNV-TmfFCKPVrYWFh1b0NaZJpUzKTmg_X_nvTdnbpyF7IXGQ4ed43OefkFMVzBKeIVOj92iXfCzvduF5PIaaoLOsHxSlqCJ4wDMnDo_-T4kkIawhLUjP2uDghBJUYlvC00HPXda63W5CCVkBa0xspLJAr3ZkQ_RZEHWIAIoDO-SisiVuw8VoZGZ0PH8CVDslmoPWuA_HGASv8UgPpVhkHISZldHhaPGqFDfrZsJ4VP798_jH_Nrm4_Ho-n11MZIWbOKkRK3FTMql0S3QjsIIMaShyhJSK4bJEohIC04UqKYJqBwtWK4iwklIhcla8PPhurAt8qFDgmJZVwzBqdsT5gVBOrPnGm074LXfC8H3A-SUXPhppNWdUCt0oReuGUUgq0TKJEVWLCtd1W7fZ693BK9zoTVqM3D6Z69neLSVOSS58lfGPw-XSotNK6j56YUeq8U5vVnzpfvOKUQrpzuDNYODdr5TbwnOLpLZW9NqlfZo1JJSQJqOv_kHvL8ZALUXO1_Sty-fKnSmf5ZQrWKH9sdN7qPyp_ERkfn2tyfGR4O1IkJmo_8SlSCHw8-9X_89eXo_Z10fsSgsbV8HZFI3rwxikB1B6F4LX7V2REeS74bmtBt8NDx-GJ8teHDfoTnQ7LeQvl6sVLQ</recordid><startdate>20201105</startdate><enddate>20201105</enddate><creator>Lind, 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used clinical chemistry tests as mortality predictors: Results from two large cohort studies</title><author>Lind, Lars ; Zanetti, Daniela ; Högman, Marieann ; Sundman, Lars ; Ingelsson, Erik</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c729t-81652956cdef3e9a2d061e0a56c35d62551a7aa24bd5410d5295a68d012dccd13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Age</topic><topic>Albumins</topic><topic>Authorship</topic><topic>Bilirubin</topic><topic>Biobanks</topic><topic>Biological markers</topic><topic>Biological Specimen Banks</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Blood pressure</topic><topic>Body mass index</topic><topic>Calcium</topic><topic>Calcium (blood)</topic><topic>Chemistry</topic><topic>Clinical chemistry</topic><topic>Clinical Chemistry Tests - methods</topic><topic>Cohort 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One</addtitle><date>2020-11-05</date><risdate>2020</risdate><volume>15</volume><issue>11</issue><spage>e0241558</spage><epage>e0241558</epage><pages>e0241558-e0241558</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease.
We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006-2010, with up to 48- and 9-years follow-up, respectively.
In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P<0.0001, except bilirubin P<0.005). For calcium, blood urea nitrogen, bilirubin, hematocrit, uric acid, and iron, U-shaped associations were seen (P<0.0001). For leukocyte count, gamma-glutamyl transferase, alkaline phosphatases and lactate dehydrogenase, linear positive associations were seen, while for albumin the association was negative. Similar associations were seen in UKB. Addition of all biomarkers to a model with classical risk factors improved mortality prediction (delta C-statistics: +0.009 in X69 and +0.023 in UKB, P<0.00001 in both cohorts).
Commonly used clinical chemistry tests were associated with all-cause mortality both in the medium- and long-term perspective, and improved mortality prediction beyond classical risk factors. Since both linear and U-shaped relationships were found, we propose to define the normal range of a clinical chemistry test based on its association with mortality, rather than from the distribution.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33152050</pmid><doi>10.1371/journal.pone.0241558</doi><tpages>e0241558</tpages><orcidid>https://orcid.org/0000-0002-1225-1021</orcidid><oa>free_for_read</oa></addata></record> |
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| issn | 1932-6203 1932-6203 |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; SWEPUB Freely available online; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Age Albumins Authorship Bilirubin Biobanks Biological markers Biological Specimen Banks Biology and Life Sciences Biomarkers Biomarkers - blood Blood pressure Body mass index Calcium Calcium (blood) Chemistry Clinical chemistry Clinical Chemistry Tests - methods Cohort analysis Cohort Studies Diabetes Evaluation Fasting Forecasts and trends Glucose Health risks Hematocrit Humans Identification and classification Kaplan-Meier Estimate L-Lactate dehydrogenase Laboratories Lactate dehydrogenase Lactic acid Leukocytes Medical screening Medicine Medicine and Health Sciences Mortality Observations Physical Sciences Predictions Principal Component Analysis Reproducibility of Results Research and Analysis Methods Risk analysis Risk Factors Test validity Urea Uric acid Variables Young Adult γ-Glutamyltransferase |
| title | Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T13%3A25%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Commonly%20used%20clinical%20chemistry%20tests%20as%20mortality%20predictors:%20Results%20from%20two%20large%20cohort%20studies&rft.jtitle=PloS%20one&rft.au=Lind,%20Lars&rft.date=2020-11-05&rft.volume=15&rft.issue=11&rft.spage=e0241558&rft.epage=e0241558&rft.pages=e0241558-e0241558&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0241558&rft_dat=%3Cgale_plos_%3EA640707147%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2457962191&rft_id=info:pmid/33152050&rft_galeid=A640707147&rft_doaj_id=oai_doaj_org_article_64cae9dd48964037af6c214db7288f8f&rfr_iscdi=true |