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Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies

BACKGROUND: 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. METHODS: We studied the associations and risk predic...

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Autores principales: Lind, Lars, Zanetti, Daniela, Högman, Marieann, Sundman, Lars, Ingelsson, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644047/
https://www.ncbi.nlm.nih.gov/pubmed/33152050
http://dx.doi.org/10.1371/journal.pone.0241558
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author Lind, Lars
Zanetti, Daniela
Högman, Marieann
Sundman, Lars
Ingelsson, Erik
author_facet Lind, Lars
Zanetti, Daniela
Högman, Marieann
Sundman, Lars
Ingelsson, Erik
author_sort Lind, Lars
collection PubMed
description BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
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spelling pubmed-76440472020-11-16 Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies Lind, Lars Zanetti, Daniela Högman, Marieann Sundman, Lars Ingelsson, Erik PLoS One Research Article BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. Public Library of Science 2020-11-05 /pmc/articles/PMC7644047/ /pubmed/33152050 http://dx.doi.org/10.1371/journal.pone.0241558 Text en © 2020 Lind et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lind, Lars
Zanetti, Daniela
Högman, Marieann
Sundman, Lars
Ingelsson, Erik
Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title_full Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title_fullStr Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title_full_unstemmed Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title_short Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies
title_sort commonly used clinical chemistry tests as mortality predictors: results from two large cohort studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644047/
https://www.ncbi.nlm.nih.gov/pubmed/33152050
http://dx.doi.org/10.1371/journal.pone.0241558
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