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

Lars Lind, Daniela Zanetti, Marieann Högman and 2 more

PLoS ONE · 2020

doi:10.1371/journal.pone.0241558 (opens in a new tab)

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Abstract

<h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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).<h4>Conclusions</h4>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 licence: CC BY

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