TY - JOUR
T1 - Inflammatory biomarkers improve clinical prediction of mortality in chronic obstructive pulmonary disease
AU - Celli, Bartolome R.
AU - Locantore, Nicholas
AU - Yates, Julie
AU - Tal-Singer, Ruth
AU - Miller, Bruce E.
AU - Bakke, Per
AU - Calverley, Peter
AU - Coxson, Harvey
AU - Crim, Courtney
AU - Edwards, Lisa D.
AU - Lomas, David A.
AU - Duvoix, Annelyse
AU - MacNee, William
AU - Rennard, Stephen
AU - Silverman, Edwin
AU - Vestbo, Jørgen
AU - Wouters, Emiel
AU - Agustí, Alvar
PY - 2012/5/15
Y1 - 2012/5/15
N2 - Rationale: Accurate prediction of mortality helps select patients for interventions aimed at improving outcome. Objectives: Because chronic obstructive pulmonary disease is characterized by low-grade systemic inflammation, we hypothesized that addition of inflammatory biomarkers to established predictive factors will improve accuracy. Methods: A total of 1,843 patients enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study were followed for 3 years. Kaplan-Meier curves, log-rank analysis, and Cox proportional hazards analyses determined the predictive value for mortality of clinical variables, while C statistics assessed the added discriminative power offered by addition of biomarkers. Measurements and Main Results: At recruitment we measured anthropometrics, spirometry, 6-minute walk distance, dyspnea, BODE index, history of hospitalization, comorbidities, and computed tomography scan emphysema. White blood cell and neutrophil counts, serum or plasma levels of fibrinogen, chemokine ligand 18, surfactant protein D, C-reactive protein, Clara cell secretory protein-16, IL-6 and -8, and tumor necrosis factor-α were determined at recruitment and subsequent visits. A total of 168 of the 1,843 patients (9.1%) died. Non-survivors were older and hadmore severe airflow limitation, increased dyspnea, higher BODE score, more emphysema, and higher rates of comorbidities and history of hospitalizations. The best predictive model for mortality using clinical variables included age, BODE, and hospitalization history (C statistic of 0.686; P < 0.001). One single biomarker (IL-6) significantly improved the C statistic to 0.708, but this was further improved to 0.726 (P = 0.003) by the addition of all biomarkers. Conclusions: The addition of a panel of selected biomarkers improves the ability of established clinical variables to predict mortality in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT00292552).
AB - Rationale: Accurate prediction of mortality helps select patients for interventions aimed at improving outcome. Objectives: Because chronic obstructive pulmonary disease is characterized by low-grade systemic inflammation, we hypothesized that addition of inflammatory biomarkers to established predictive factors will improve accuracy. Methods: A total of 1,843 patients enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study were followed for 3 years. Kaplan-Meier curves, log-rank analysis, and Cox proportional hazards analyses determined the predictive value for mortality of clinical variables, while C statistics assessed the added discriminative power offered by addition of biomarkers. Measurements and Main Results: At recruitment we measured anthropometrics, spirometry, 6-minute walk distance, dyspnea, BODE index, history of hospitalization, comorbidities, and computed tomography scan emphysema. White blood cell and neutrophil counts, serum or plasma levels of fibrinogen, chemokine ligand 18, surfactant protein D, C-reactive protein, Clara cell secretory protein-16, IL-6 and -8, and tumor necrosis factor-α were determined at recruitment and subsequent visits. A total of 168 of the 1,843 patients (9.1%) died. Non-survivors were older and hadmore severe airflow limitation, increased dyspnea, higher BODE score, more emphysema, and higher rates of comorbidities and history of hospitalizations. The best predictive model for mortality using clinical variables included age, BODE, and hospitalization history (C statistic of 0.686; P < 0.001). One single biomarker (IL-6) significantly improved the C statistic to 0.708, but this was further improved to 0.726 (P = 0.003) by the addition of all biomarkers. Conclusions: The addition of a panel of selected biomarkers improves the ability of established clinical variables to predict mortality in chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT00292552).
KW - Biologic markers
KW - Mortality
KW - Prognosis
KW - Pulmonary disease, chronic obstructive
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U2 - 10.1164/rccm.201110-1792OC
DO - 10.1164/rccm.201110-1792OC
M3 - Article
C2 - 22427534
AN - SCOPUS:84861410475
SN - 1073-449X
VL - 185
SP - 1065
EP - 1072
JO - American Journal of Respiratory and Critical Care Medicine
JF - American Journal of Respiratory and Critical Care Medicine
IS - 10
ER -