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10.1186/s12931-017-0597-7 http://scihub22266oqcxt.onion/10.1186/s12931-017-0597-7 C5470282!5470282!28610627     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Respir+Res 2017 ; 18 (ä): ä Nephropedia Template TP {{tp|p=28610627|t=2017. Multiple biomarkers predict disease severity, progression and mortality in COPD |pdf=|usr=}}{{28610627}} gab.com Text Multiple biomarkers predict disease severity, progression and mortality in COPD JO: Respir Res http://www.kidney.de/pget.php?&tw=1&pmid=28610627 #FOAvip Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterized by multiple subtypes and variable disease progression. Blood biomarkers have been variably associated with subtype, severity, and disease progression. Just as combined clinical variables are more highly predictive of outcomes than individual clinical variables, we hypothesized that multiple biomarkers may be more informative than individual biomarkers to predict subtypes, disease severity, disease progression, and mortality. Methods: Fibrinogen, C-Reactive Protein (CRP), surfactant protein D (SP-D), soluble Receptor for Advanced Glycation Endproducts (sRAGE), and Club Cell Secretory Protein (CC16) were measured in the plasma of 1465 subjects from the COPDGene cohort and 2746 subjects from the ECLIPSE cohort. Regression analysis was performed to determine whether these biomarkers, individually or in combination, were predictive of subtypes, disease severity, disease progression, or mortality, after adjustment for clinical covariates. Results: In COPDGene, the best combinations of biomarkers were: CC16, sRAGE, fibrinogen, CRP, and SP-D for airflow limitation (p?<?10?4), SP-D, CRP, sRAGE and fibrinogen for emphysema (p?<?10?3), CC16, fibrinogen, and sRAGE for decline in FEV1 (p?<?0.05) and progression of emphysema (p?<?10?3), and all five biomarkers together for mortality (p?<?0.05). All associations except mortality were validated in ECLIPSE. The combination of SP-D, CRP, and fibrinogen was the best model for mortality in ECLIPSE (p?<?0.05), and this combination was also significant in COPDGene. Conclusion: This comprehensive analysis of two large cohorts revealed that combinations of biomarkers improve predictive value compared with clinical variables and individual biomarkers for relevant cross-sectional and longitudinal COPD outcomes. Electronic supplementary material: The online version of this article (doi:10.1186/s12931-017-0597-7) contains supplementary material, which is available to authorized users. Twit Text FOAVip Multiple biomarkers predict disease severity, progression and mortality in COPD ????Respir Res http://www.kidney.de/pget.php?&tw=1&pmid=28610627 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28610627 #FOAvip English Wikipedia <ref>{{Cite pmid|28610627}}</ref> Multiple biomarkers predict disease severity, progression and mortality in COPD #MMPMID28610627 Zemans RL; Jacobson S; Keene J; Kechris K; Miller BE; Tal-Singer R; Bowler RP Respir Res 2017[]; 18 (ä): ä PMID28610627show ga Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characterized by multiple subtypes and variable disease progression. Blood biomarkers have been variably associated with subtype, severity, and disease progression. Just as combined clinical variables are more highly predictive of outcomes than individual clinical variables, we hypothesized that multiple biomarkers may be more informative than individual biomarkers to predict subtypes, disease severity, disease progression, and mortality. Methods: Fibrinogen, C-Reactive Protein (CRP), surfactant protein D (SP-D), soluble Receptor for Advanced Glycation Endproducts (sRAGE), and Club Cell Secretory Protein (CC16) were measured in the plasma of 1465 subjects from the COPDGene cohort and 2746 subjects from the ECLIPSE cohort. Regression analysis was performed to determine whether these biomarkers, individually or in combination, were predictive of subtypes, disease severity, disease progression, or mortality, after adjustment for clinical covariates. Results: In COPDGene, the best combinations of biomarkers were: CC16, sRAGE, fibrinogen, CRP, and SP-D for airflow limitation (p? äMultiple biomarkers predict disease severity, progression and mortalit(epmc).pdf DeepDyve Pubget Overpricing