Circulating Progenitor Cell Count for Cardiovascular Risk Stratification: A Pooled Analysis

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Circulating Progenitor Cell Count for Cardiovascular Risk Stratification: A Pooled Analysis

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Title: Circulating Progenitor Cell Count for Cardiovascular Risk Stratification: A Pooled Analysis
Author: Fadini, Gian Paolo; Maruyama, Shoichi; Ozaki, Takenori; Taguchi, Akihiko; Dimmeler, Stefanie; Zeiher, Andreas M.; de Kreutzenberg, Saula; Avogaro, Angelo; Nickenig, Georg; Schmidt-Lucke, Caroline; Werner, Nikos; Meigs, James Benjamin

Note: Order does not necessarily reflect citation order of authors.

Citation: Fadini, Gian Paolo, Shoichi Maruyama, Takenori Ozaki, Akihiko Taguchi, James Meigs, Stefanie Dimmeler, Andreas M. Zeiher, et al. 2010. Circulating Progenitor Cell Count for Cardiovascular Risk Stratification: A Pooled Analysis. PLoS ONE 5(7): e11488.
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Abstract: Background: Circulating progenitor cells (CPC) contribute to the homeostasis of the vessel wall, and a reduced CPC count predicts cardiovascular morbidity and mortality. We tested the hypothesis that CPC count improves cardiovascular risk stratification and that this is modulated by low-grade inflammation. Methodology/Principal Findings: We pooled data from 4 longitudinal studies, including a total of 1,057 patients having CPC determined and major adverse cardiovascular events (MACE) collected. We recorded cardiovascular risk factors and high-sensitive C-reactive protein (hsCRP) level. Risk estimates were derived from Cox proportional hazard analyses. CPC count and/or hsCRP level were added to a reference model including age, sex, cardiovascular risk factors, prevalent CVD, chronic renal failure (CRF) and medications. The sample was composed of high-risk individuals, as 76.3% had prevalent CVD and 31.6% had CRF. There were 331 (31.3%) incident MACE during an average 1.7±1.1 year follow-up time. CPC count was independently associated with incident MACE even after correction for hsCRP. According to C-statistics, models including CPC yielded a non-significant improvement in accuracy of MACE prediction. However, the integrated discrimination improvement index (IDI) showed better performance of models including CPC compared to the reference model and models including hsCRP in identifying MACE. CPC count also yielded significant net reclassification improvements (NRI) for CV death, non-fatal AMI and other CV events. The effect of CPC was independent of hsCRP, but there was a significant more-than-additive interaction between low CPC count and raised hsCRP level in predicting incident MACE. Conclusions/Significance: In high risk individuals, a reduced CPC count helps identifying more patients at higher risk of MACE over the short term, especially in combination with a raised hsCRP level.
Published Version: doi:10.1371/journal.pone.0011488
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901328/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4878946

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