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C-Reactive Protein and Prediction of 1-Year Mortality in Prevalent Hemodialysis Patients

Identifieur interne : 006215 ( Main/Exploration ); précédent : 006214; suivant : 006216

C-Reactive Protein and Prediction of 1-Year Mortality in Prevalent Hemodialysis Patients

Auteurs : Jonathan Bazeley [États-Unis] ; Brian Bieber [États-Unis] ; Yun Li [États-Unis] ; Hal Morgenstern [États-Unis] ; Patricia De Sequera [Espagne] ; Christian Combe [France] ; Hiroyasu Yamamoto [Japon] ; Martin Gallagher [Australie] ; Friedrich K. Port [États-Unis] ; Bruce M. Robinson [États-Unis]

Source :

RBID : PMC:3186454

Abstract

SummaryBackground and objectives

Measurement of C-reactive protein (CRP) levels remains uncommon in North America, although it is now routine in many countries. Using Dialysis Outcomes and Practice Patterns Study data, our primary aim was to evaluate the value of CRP for predicting mortality when measured along with other common inflammatory biomarkers.

Design, setting, participants, & measurements

We studied 5061 prevalent hemodialysis patients from 2005 to 2008 in 140 facilities routinely measuring CRP in 10 countries. The association of CRP with mortality was evaluated using Cox regression. Prediction of 1-year mortality was assessed in logistic regression models with differing adjustment variables.

Results

Median baseline CRP was lower in Japan (1.0 mg/L) than other countries (6.0 mg/L). CRP was positively, monotonically associated with mortality. No threshold below which mortality rate leveled off was identified. In prediction models, CRP performance was comparable with albumin and exceeded ferritin and white blood cell (WBC) count based on measures of model discrimination (c-statistics, net reclassification improvement [NRI]) and global model fit (generalized R2). The primary analysis included age, gender, diabetes, catheter use, and the four inflammatory markers (omitting one at a time). Specifying NRI ≥5% as appropriate reclassification of predicted mortality risk, NRI for CRP was 12.8% compared with 10.3% for albumin, 0.8% for ferritin, and <0.1% for WBC.

Conclusions

These findings demonstrate the value of measuring CRP in addition to standard inflammatory biomarkers to improve mortality prediction in hemodialysis patients. Future studies are indicated to identify interventions that lower CRP and to identify whether they improve clinical outcomes.


Url:
DOI: 10.2215/CJN.00710111
PubMed: 21868617
PubMed Central: 3186454


Affiliations:


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Le document en format XML

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<name sortKey="Yamamoto, Hiroyasu" sort="Yamamoto, Hiroyasu" uniqKey="Yamamoto H" first="Hiroyasu" last="Yamamoto">Hiroyasu Yamamoto</name>
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<name sortKey="Robinson, Bruce M" sort="Robinson, Bruce M" uniqKey="Robinson B" first="Bruce M." last="Robinson">Bruce M. Robinson</name>
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<region type="state">Michigan</region>
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<region type="state">Michigan</region>
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<sec>
<title>Summary</title>
<sec>
<title>Background and objectives</title>
<p>Measurement of C-reactive protein (CRP) levels remains uncommon in North America, although it is now routine in many countries. Using Dialysis Outcomes and Practice Patterns Study data, our primary aim was to evaluate the value of CRP for predicting mortality when measured along with other common inflammatory biomarkers.</p>
</sec>
<sec>
<title>Design, setting, participants, & measurements</title>
<p>We studied 5061 prevalent hemodialysis patients from 2005 to 2008 in 140 facilities routinely measuring CRP in 10 countries. The association of CRP with mortality was evaluated using Cox regression. Prediction of 1-year mortality was assessed in logistic regression models with differing adjustment variables.</p>
</sec>
<sec>
<title>Results</title>
<p>Median baseline CRP was lower in Japan (1.0 mg/L) than other countries (6.0 mg/L). CRP was positively, monotonically associated with mortality. No threshold below which mortality rate leveled off was identified. In prediction models, CRP performance was comparable with albumin and exceeded ferritin and white blood cell (WBC) count based on measures of model discrimination (c-statistics, net reclassification improvement [NRI]) and global model fit (generalized
<italic>R</italic>
<sup>2</sup>
). The primary analysis included age, gender, diabetes, catheter use, and the four inflammatory markers (omitting one at a time). Specifying NRI ≥5% as appropriate reclassification of predicted mortality risk, NRI for CRP was 12.8% compared with 10.3% for albumin, 0.8% for ferritin, and <0.1% for WBC.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>These findings demonstrate the value of measuring CRP in addition to standard inflammatory biomarkers to improve mortality prediction in hemodialysis patients. Future studies are indicated to identify interventions that lower CRP and to identify whether they improve clinical outcomes.</p>
</sec>
</sec>
</div>
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<name sortKey="Bazeley, Jonathan" sort="Bazeley, Jonathan" uniqKey="Bazeley J" first="Jonathan" last="Bazeley">Jonathan Bazeley</name>
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<name sortKey="Bazeley, Jonathan" sort="Bazeley, Jonathan" uniqKey="Bazeley J" first="Jonathan" last="Bazeley">Jonathan Bazeley</name>
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<name sortKey="Li, Yun" sort="Li, Yun" uniqKey="Li Y" first="Yun" last="Li">Yun Li</name>
<name sortKey="Li, Yun" sort="Li, Yun" uniqKey="Li Y" first="Yun" last="Li">Yun Li</name>
<name sortKey="Morgenstern, Hal" sort="Morgenstern, Hal" uniqKey="Morgenstern H" first="Hal" last="Morgenstern">Hal Morgenstern</name>
<name sortKey="Port, Friedrich K" sort="Port, Friedrich K" uniqKey="Port F" first="Friedrich K." last="Port">Friedrich K. Port</name>
<name sortKey="Port, Friedrich K" sort="Port, Friedrich K" uniqKey="Port F" first="Friedrich K." last="Port">Friedrich K. Port</name>
<name sortKey="Robinson, Bruce M" sort="Robinson, Bruce M" uniqKey="Robinson B" first="Bruce M." last="Robinson">Bruce M. Robinson</name>
<name sortKey="Robinson, Bruce M" sort="Robinson, Bruce M" uniqKey="Robinson B" first="Bruce M." last="Robinson">Bruce M. Robinson</name>
</country>
<country name="Espagne">
<region name="Communauté de Madrid">
<name sortKey="De Sequera, Patricia" sort="De Sequera, Patricia" uniqKey="De Sequera P" first="Patricia" last="De Sequera">Patricia De Sequera</name>
</region>
</country>
<country name="France">
<region name="Nouvelle-Aquitaine">
<name sortKey="Combe, Christian" sort="Combe, Christian" uniqKey="Combe C" first="Christian" last="Combe">Christian Combe</name>
</region>
</country>
<country name="Japon">
<region name="Région de Kantō">
<name sortKey="Yamamoto, Hiroyasu" sort="Yamamoto, Hiroyasu" uniqKey="Yamamoto H" first="Hiroyasu" last="Yamamoto">Hiroyasu Yamamoto</name>
</region>
</country>
<country name="Australie">
<region name="Nouvelle-Galles du Sud">
<name sortKey="Gallagher, Martin" sort="Gallagher, Martin" uniqKey="Gallagher M" first="Martin" last="Gallagher">Martin Gallagher</name>
</region>
</country>
</tree>
</affiliations>
</record>

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