0
Original Research: COPD |

Stable-State Midrange-Proadrenomedullin Level Is a Strong Predictor of Mortality in Patients With COPDMidrange-Proadrenomedullin in Stable COPD FREE TO VIEW

Maaike C. Zuur-Telgen, MD; Marjolein G. J. Brusse-Keizer, PhD; Paul D. L. P. M. VanderValk, MD, PhD; Job van der Palen, PhD; Huib A. M. Kerstjens, MD, PhD; M. G. Ron Hendrix, MD, PhD
Author and Funding Information

From the Department of Pulmonary Medicine (Drs Zuur-Telgen, Brusse-Keizer, VanderValk, and van der Palen) and the Department of Internal Medicine (Dr Zuur-Telgen), Medisch Spectrum Twente, Enschede; Regional Laboratory of Public Health (Dr Hendrix) and the Department of Research Methodology, Measurement, and Data Analysis (Dr van der Palen), University of Twente, Enschede; the Department of Pulmonary Medicine (Dr Kerstjens) and the Department of Medical Microbiology (Dr Hendrix), University Medical Centre Groningen, University of Groningen, Groningen; and Groningen Research Institute for Asthma and COPD (GRIAC) (Dr Kerstjens), Groningen, The Netherlands.

Correspondence to: Maaike C. Zuur-Telgen, MD, Department of Pulmonary Medicine, Medisch Spectrum Twente, PO Box 50 000, 7500 KA Enschede, The Netherlands; e-mail: maaiketelgen@gmail.com


The abstract of this article was presented at the American Thoracic Society Meeting, May 17-22, 2013, Philadelphia, PA.

Funding/Support: This study was funded by an unrestricted research grant from GlaxoSmithKline for the COMIC (Cohort of Mortality and Inflammation in COPD) cohort.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2014;145(3):534-541. doi:10.1378/chest.13-1063
Text Size: A A A
Published online

Background:  Midrange-proadrenomedullin (MR-proADM) has been shown to be elevated in patients hospitalized for an acute exacerbation of COPD (AECOPD) and in patients with community-acquired pneumonia. When measured during AECOPDs, MR-proADM has also been shown to be a predictor of mortality. We hypothesized that MR-proADM levels measured in a stable state could also predict mortality.

Methods:  We included 181 patients in whom we had paired plasma samples for MR-proADM determinations during a stable state and at hospitalization for an AECOPD when they also produced sputum. Time to death or censoring was compared between patients with MR-proADM above or below the median of 0.71 nmol/L. The predictive value of MR-proADM for survival was determined by calculating the C statistic.

Results:  Patients with COPD and MR-proADM levels > 0.71 nmol/L in the stable state had a threefold-higher risk of dying than did patients with MR-proADM levels < 0.71 nmol/L (hazard ratio, 2.98 [95% CI, 1.51-5.90]; C statistic, 0.76). The corrected OR for 1-year mortality was 8.90 (95% CI, 1.94-44.6) in patients with high MR-proADM levels measured in the stable state, compared with patients with low levels measured in the stable state.

Conclusions:  MR-proADM measured in the stable state appeared to be a strong predictor of mortality in patients with COPD. MR-proADM is far easier to measure than other predictors of mortality in COPD, such as BMI, airflow obstruction, dyspnea, and exercise capacity score.

Figures in this Article

COPD will be the third-leading cause of mortality worldwide by 2020.1 The prediction of mortality is helpful in identifying patients in whom adjustment of care may be appropriate. Airflow limitation,2,3 low BMI,4 breathlessness,5 exercise capacity,6,7 frequency and severity of exacerbations,8 and degree of systemic inflammation912 can help predict the prognosis of COPD. The explained variance in mortality by these parameters, however, is very low. Integrating them into multidimensional indexes, such as the BMI, airflow obstruction, dyspnea, and exercise capacity (BODE) index10 and the age, dyspnea, and airflow obstruction (ADO) score,13 helps in predicting survival better than do the individual variables.

An easily accessible marker with a close relation to survival in COPD would constitute an important step forward. Several biomarkers have been studied in COPD14,15 and in acute exacerbations of COPD (AECOPDs), but so far none has gained wide acceptance.15

The predictive values for mortality of two biomarkers, procalcitonin (PCT)16 and midrange-proadrenomedullin (MR-proADM), have been studied in COPD.17 PCT is a marker of systemic bacterial infection, and levels correlate with the cause and severity of pneumonia in a healthy population.18,19 PCT is also elevated at hospitalization for an AECOPD.20 Adrenomedullin (ADM) has immune-modulating, metabolic, and vascular actions. It can behave both as a hormone and as a cytokine and can simultaneously control pulmonary blood flow, leukocyte migration, and electrolyte balance.2123 ADM-sensitive receptors are ubiquitously present in the body, and receptors for ADM, and ADM itself, have been established in the lung in high concentrations.24 ADM is cleared rapidly from the circulation and it is, therefore, difficult to measure.25 The more stable precursor of ADM, MR-proADM, closely reflects the level of active ADM26 and has been shown to predict survival in patients with acute myocardial infarction, heart failure, community-acquired pneumonia (CAP), and systemic inflammatory response syndrome.17,2729 Furthermore, MR-proADM levels are increased in patients with pulmonary arterial hypertension and end-stage pulmonary disease17 and in the acute phase of CAP and in AECOPDs.17,19 Finally, MR-proADM measured at hospitalization for an AECOPD has been shown to be independently associated with 2-year survival.17

Therefore, both PCT and MR-proADM have predictive value for mortality when measured at hospitalization for an AECOPD, but it is unknown whether their measurement in the stable state is also useful in predicting mortality and future hospitalization. Measurement in the stable state may well be more accurate because of less variability. Better and easier prediction of mortality should allow for better targeting of additional interventions.30

The aim of our study was to investigate whether increased levels of PCT and MR-proADM in the stable state can predict mortality and time to next hospitalization for an AECOPD. Additionally, we compared levels of PCT and MR-proADM in the stable state with those at hospitalization for an AECOPD.

Setting and Study Population

This study was part of the Cohort of Mortality and Inflammation in COPD (COMIC) study, a single-center cohort study on the immune status of patients with COPD as a determinant for survival. From December 2005 to April 2010, 795 patients were included, with a follow-up period of 3 years. The COMIC study was approved by the hospital’s medical ethical committee (P05-49). All patients provided written informed consent.

Patients had to meet the following criteria: (1) a clinical diagnosis of COPD according to the GOLD (Global Initiative for Chronic Obstructive Lung Disease) guidelines,31 (2) current or former smoker, (3) age ≥ 40 years, (4) no medical condition compromising survival within the follow-up period or serious psychiatric morbidity, (5) absence of any other active lung disease (eg, sarcoidosis), (6) no maintenance therapy with antibiotics, and (7) ability to speak Dutch. Patients were enrolled when hospitalized for an AECOPD or when they visited the outpatient clinic in the stable state. To be included in the AECOPD group, patients had to be hospitalized for an AECOPD and to be able to produce an adequate sputum sample at the day of hospitalization.32 An AECOPD was defined as an acute negative change from baseline, reported by the patient, in dyspnea and/or sputum volume and/or color of sputum (yellowish or greenish sputum) and/or cough, which may warrant additional treatment with prednisolone with or without antibiotics by a physician in a patient with underlying COPD. To be included in the stable-state group, patients had to meet the following criteria: no use of antibiotic and/or prednisolone 4 weeks prior to enrollment and no exacerbation within the 4 weeks before study entry. In addition, data on common comorbidities such as hypertension, myocardial infarction, and heart failure were obtained because they were probably related to MR-proADM because of its vascular activity and were related to survival.29,3335 Patients were asked to complete a questionnaire about their dyspnea in the stable state (modified Medical Research Council).36 Plasma samples were obtained in 181 patients in both the stable state and at hospitalization for an AECOPD, and biomarker levels of MR-proADM and PCT were determined.

Outcomes

The primary outcome parameter was survival, based on all-cause mortality. Date of death was verified from the municipal administration. The secondary outcome was time to next hospitalization for an AECOPD.

Measurements of MR-proADM and PCT

MR-proADM and PCT levels were measured in plasma. Levels were determined with an automated sandwich immunoassay using time-resolved amplified cryptate emission technology.19

Statistical Analysis

Continuous variables are expressed as mean (± SD) or median (interquartile range), and categorical variables as counts (percentages). Differences in PCT and MR-proADM levels between survivors and nonsurvivors and between the stable state and hospitalization for an AECOPD were analyzed by Student t test or Mann-Whitney U test, as appropriate. Patients were classified as having high or low levels of MR-proADM and PCT based on the median, both in the stable state and during hospitalizations for an AECOPD. As a secondary analysis, the test characteristics of different cutoff levels of the MR-proADM level in the stable state (including the value used by Stolz et al17) were assessed. Time from the stable state or first hospitalization for an AECOPD to event (death or next hospitalization for an AECOPD) was analyzed by Kaplan-Meier survival curves with log-rank tests. Hazard ratios (HRs) were determined by Cox regression analysis. All analyses were corrected for age, sex, BMI, and GOLD stage in a multivariate Cox regression analysis, and the C statistic was calculated.37 One- and 2-year survival after the stable state or hospitalization for an AECOPD was analyzed by logistic regression analyses and corrected for the same parameters. All tests were two-sided, and a P value of .05 was considered statistically significant. The data were analyzed using SPSS, version 18 (IBM).

Baseline Characteristics

The detailed baseline characteristics of the 181 patients are presented in Table 1. The median follow-up times after inclusion at the stable state and at hospitalization for an AECOPD were 29 and 35 months, respectively. Mortality was 28%.

Table Graphic Jump Location
Table 1 —Baseline Characteristics

Data are shown as mean (SD) unless otherwise indicated. ADO = age, dyspnea, and airflow obstruction; GOLD = Global Initiative for Chronic Obstructive Lung Disease; mMRC = modified Medical Research Council; VC = vital capacity.

a 

Scores of 180 patients.

MR-proADM and PCT Levels in Survivors and Nonsurvivors

MR-proADM and PCT levels differed significantly between survivors and nonsurvivors, both when measured in the stable state and at hospitalization for an AECOPD (Table 2).

Table Graphic Jump Location
Table 2 —MR-proADM and PCT Results

IQR = interquartile range; MR-proADM = midrange-proadrenomedullin; PCT = procalcitonin.

Stable State
MR-proADM in Stable State:

Survival time was significantly shorter in patients with high stable-state MR-proADM levels (above the median of 0.71 nmol/L) than in those with low levels, with a corrected HR of 2.98 (95% CI, 1.51-5.90) and a C statistic of 0.76 (Fig 1A, Table 3). The 1- and 2-year relative risks (RRs) for mortality of patients with low vs high MR-proADM levels were 8.20 and 2.76, respectively (Table 4). The time to next hospitalization did not differ.

Figure Jump LinkFigure 1. Kaplan-Meier survival curves for MR-proADM and PCT in the stable state and at an AECOPD. A, MR-proADM stable state. B, MR-proADM AECOPD. C, PCT stable state. D, PCT AECOPD. AECOPD = acute exacerbation of COPD; MR-proADM = midrange-proadrenomedullin; PCT = procalcitonin.Grahic Jump Location
Table Graphic Jump Location
Table 3 —Survival Analysis

AECOPD = acute exacerbation of COPD; cHR = HR corrected for age, sex, BMI, and GOLD status; HR = hazard ratio. See Table 1 and 2 legends for expansion of other abbreviations.

a 

Above or below study median (0.71 nmol/L).

b 

Above or below study median (0.79 nmol/L).

c 

Above or below study median (0.84 nmol/L) in study by Stolz et al.17

d 

Above or below study median (0.05 ng/mL).

e 

Above or below study median (0.06 ng/mL).

Table Graphic Jump Location
Table 4 —1- and 2-y Mortality Risk

AUC = area under the curve; cOR = corrected OR for sex, age, BMI, and GOLD stage; RR = relative risk. See Table 1, 2, and 3 legends for expansion of other abbreviations.

e-Table 1 shows cutoff points of different MR-proADM levels for 1- and 2-year survival. When higher cutoff values than the median of our population were used, the sensitivity decreased, whereas the specificity increased.

PCT in Stable State:

Stable-state PCT levels above and below the median (0.05 ng/mL) did not relate to survival time, with a corrected HR of 1.13 (95% CI, 0.61-2.07) and a C statistic of 0.74 (Fig 1C, Table 3). The 1- and 2-year RRs for mortality of patients with low vs high PCT levels were 2.38 and 1.58, respectively (Table 4). The time to next hospitalization did not differ.

Hospitalization for AECOPD
MR-proADM at Hospitalization for AECOPD:

In patients with high MR-proADM levels (above the median of 0.79 nmol/L) at hospitalization for an AECOPD, survival time was shorter than in those with low levels, with a corrected HR of 1.58 (95% CI, 0.80-3.14) and a C statistic of 0.74 (Fig 1B, Table 3). The 1- and 2-year RRs for mortality of patients with low vs high MR-proADM levels were 4.10 and 2.26, respectively (Table 4). The time to next hospitalization did not differ.

When we used the median MR-proADM level of Stolz et al17 (0.84 nmol/L), survival time was shorter in patients with high vs low MR-proADM levels, with a corrected HR of 1.82 (95% CI, 0.93-3.55) and a C statistic of 0.74 (Table 3). The 1- and 2-year RRs for mortality of patients with low vs high MR-proADM levels were 5.85 and 2.44, respectively (Table 4). The time to next hospitalization did not differ.

PCT at Hospitalization for AECOPD:

In patients with high PCT levels (above the median of 0.06 ng/mL) at hospitalization for an AECOPD, with a corrected HR of 1.80 (95% CI, 0.99-3.28), survival and time to next hospitalization did not differ significantly from those with low levels of PCT.

Association Between Levels of Both MR-proADM and PCT in Stable State and at Hospitalization for AECOPD

MR-proADM levels in the stable state and at hospitalization for an AECOPD were linearly associated with a correlation coefficient of 0.73 (P < .001) (e-Fig 1). There was no linear association between PCT levels measured in the stable state and at hospitalization for an AECOPD.

MR-proADM levels and PCT levels in the stable state were moderately correlated (r = 0.40, P < .001). There was no linear association between MR-proADM levels and PCT levels measured at hospitalization for an AECOPD.

This study demonstrates, we believe for the first time, that high plasma MR-proADM levels in patients with COPD in a stable situation are associated with a threefold-increased risk of mortality when corrected for potential confounding variables. Uncorrected, a high MR-proADM level confers a 3.5-fold increased risk. PCT measured at the same time was not significantly associated with survival.

The threefold-increased risk of 2-year mortality associated with high MR-proADM levels measured in the stable state is highly relevant, especially because the absolute mortality risk is high, with 23% not surviving 2 years. At 1 year, it was even increased ninefold. The associated C statistic of 0.76 is not only higher than that of PCT measured under the same conditions, but also slightly higher than that of the BODE index (0.74),10 which is currently considered one of the best predictors of mortality in COPD. However, MR-proADM is considerably easier to measure than the four parameters for the BODE index.

MR-proADM levels in the stable state were elevated in 99% of our population compared with healthy individuals.26 It is unknown why MR-proADM levels are raised in our population both in the stable state and at hospitalization for an AECOPD. Our study showed that patients with COPD and high MR-proADM levels in the stable state also have high levels at hospitalization for an AECOPD and vice versa. What is known is that MR-proADM has immune-modulating as well as vascular actions. Therefore, an explanation of the higher levels of MR-proADM and mortality is offered. The higher mortality rate in patients with higher serum MR-proADM levels may reflect an increased severity of inflammatory lung disease, which is not directly reflected by the ADO score or BODE index. A variety of cells may augment ADM secretion in response to various cytokines.38,39 The increased MR-proADM may also reflect the more systemic effects of COPD, including COPD-induced cardiopulmonary stress or cardiovascular comorbidity. Indeed, MR-proADM has been shown to be increased in various cardiovascular disease states.33 In the current study, we also observed a relation between MR-proADM and cardiac comorbidities (heart failure and myocardial infarction), although these comorbidities were not associated with survival and, therefore, not confounders in the relation between MR-proADM and survival (data not shown).

ADM possibly plays an active role in the disease process, although its mechanism is unknown; it may merely reflect an epiphenomenon. ADM has a wide range of effects, including bronchodilatation40 and pro-and antiinflammatory effects. These may be beneficial in partly counteracting the pathophysiologic process that occurs in more severe COPD. Increased levels then reflect either more severe disease or an insufficient response. Elucidating the cause and mechanisms of ADM and COPD is necessary if MR-proADM is to be used as a diagnostic and possibly therapeutic tool.

Although PCT levels were correlated with MR-proADM levels in the stable state, they did not discriminate between survivors and nonsurvivors. Because PCT is a marker of systemic bacterial infection in patients with CAP19 and because the stable state is not characterized by bacterial infection, it is perhaps reasonable to expect low PCT levels. It may be that because of this overall relatively low level of PCT in the stable state, it cannot distinguish accurately between survivors and nonsurvivors but it can be used during exacerbations to distinguish between those of bacterial or nonbacterial origin and, therefore, can be used to guide antibiotic therapy.41 By contrast, an association between cause and MR-proADM in CAP was not found in one study.19

We confirm the observation by Stolz et al17 that high MR-proADM levels at hospitalization for an AECOPD were related to a shorter survival, rendering the measurement of MR-proADM informative both in the stable state and in hospitalizations for AECOPDs. It could be that there are more competing causes of death at the time of an AECOPD and, therefore, MR-proADM is slightly less predictive at that time than in the stable state. When measured at hospitalization for an AECOPD, high PCT levels were associated with a shorter survival in a univariate, but not in a multivariate analysis, when corrected for age. This univariate association probably reflects the fact that PCT is a more specific marker of systemic bacterial infection, which is probably more prominent at hospitalization for an AECOPD in a subset of patients of older age. Furthermore, there was no correlation between the MR-proADM and PCT levels measured at hospitalization.

Until now, the cutoff value for MR-proADM levels in patients with COPD was chosen to be the median of the population. In the current study, this cutoff value (0.711 ng/mL) is predictive of 1-year mortality, with a sensitivity and specificity of 88.9% and 53.1%, respectively. A cutoff point with a high specificity is most suitable when only patients with a high mortality should receive, for example, palliative care (e-Table 1). If a more intensive clinical follow-up is the preferred intervention, the cutoff point should have a high sensitivity (e-Table 1).

Our study could have been influenced by selection bias, because we included only patients who were able to produce a sufficient amount of sputum at hospitalization for an AECOPD. Those patients may have other characteristics in terms of the presence or absence of bacteria or cause of exacerbation (eg, viral or bacterial infection). In our study, patients with an exacerbation were all hospitalized, which probably means we included patients with a more severe exacerbation, which could have influenced our results. Another selection issue is the inclusion of patients who were able to deliver a paired blood sample (in the stable state and at hospitalization for an AECOPD). Because of this inclusion criterion, patients could have died or been lost to follow-up before they were hospitalized for an AECOPD or returned to the stable state after an AECOPD. In addition, given the hospitalization, patients with more severe exacerbations were included, which could have influenced the mortality rate.

In conclusion, we believe that MR-proADM is a marker of poor prognosis. It is currently unclear whether that prognosis can be influenced by more intensive care.

If one believes that with the warning signal of a high MR-proADM level, treatment can be intensified or changed, thereby improving prognosis, the relevant trial would be to measure MR-proADM in all patients with COPD. In the case of a high MR-proADM level, patients could be randomized to receive usual care or alternatively, more intensive care (more frequent contacts, additional medication, rehabilitation, and so forth). The primary outcome should be survival, with quality of life as a possible secondary outcome.

If, on the other hand, one hypothesizes that high MR-proADM levels predict inevitable death in the near future, this could perhaps aid in implementing end-of-life (palliative) care,30 because this is frequently instituted very late or not at all in many patients with COPD. A guide for clinical decision-making would be the measurement of MR-proADM. In the case of a high value, patients should be randomized to usual care or an explicit end-of-life setting with best supportive care. The primary end point should then be quality of life, and perhaps secondarily, total cost.

Author contributions: Dr Zuur-Telgen is guarantor of the manuscript and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Zuur-Telgen: contributed to the study design, laboratory work, statistical analysis, and writing of the manuscript.

Dr Brusse-Keizer: contributed to the study design, statistical analysis, and writing of the manuscript.

Dr VanderValk: contributed to the study design and writing of the manuscript.

Dr van der Palen: contributed to the study design, statistical analysis, and writing of the manuscript.

Dr Kerstjens: contributed to the study design and writing of the manuscript.

Dr Hendrix: contributed to the study design, laboratory work, and writing of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The sponsor had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript.

Other contributions: The authors thank the Research Department of Thermofischer, Hennigsdorf, Berlin, for supplying the MR-proADM and the PCT kits and for the use of the Kryptor. They thank B. Steenhuis, BSc, for helping with the measurement of MR-proADM and PCT. They also thank GlaxoSmithKline for the unrestricted research grant.

Additional information: The e-Table and e-Figure can be found in the “Supplemental Materials” area of the online article.

ADM

adrenomedullin

ADO

age, dyspnea, and airflow obstruction

AECOPD

acute exacerbation of COPD

BODE

BMI, airflow obstruction, dyspnea, and exercise capacity

CAP

community-acquired pneumonia

GOLD

Global Initiative for Chronic Obstructive Lung Disease

HR

hazard ratio

MR-proADM

midrange-proadrenomedullin

PCT

procalcitonin

RR

relative risk

Murray CJ, Lopez AD. Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study. Lancet. 1997;349(9063):1436-1442. [CrossRef] [PubMed]
 
Sapey E, Stockley RA. COPD exacerbations. 2: aetiology. Thorax. 2006;61(3):250-258. [CrossRef] [PubMed]
 
Anthonisen NR, Wright EC, Hodgkin JE. Prognosis in chronic obstructive pulmonary disease. Am Rev Respir Dis. 1986;133(1):14-20. [PubMed]
 
Schols AM, Broekhuizen R, Weling-Scheepers CA, Wouters EF. Body composition and mortality in chronic obstructive pulmonary disease. Am J Clin Nutr. 2005;82(1):53-59. [PubMed]
 
Nishimura K, Izumi T, Tsukino M, Oga T. Dyspnea is a better predictor of 5-year survival than airway obstruction in patients with COPD. Chest. 2002;121(5):1434-1440. [CrossRef] [PubMed]
 
Cote CG, Casanova C, Marín JM, et al. Validation and comparison of reference equations for the 6-min walk distance test. Eur Respir J. 2008;31(3):571-578. [CrossRef] [PubMed]
 
Oga T, Nishimura K, Tsukino M, Sato S, Hajiro T. Analysis of the factors related to mortality in chronic obstructive pulmonary disease: role of exercise capacity and health status. Am J Respir Crit Care Med. 2003;167(4):544-549. [CrossRef] [PubMed]
 
Soler-Cataluña JJ, Martínez-García MA, Román Sánchez P, Salcedo E, Navarro M, Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease. Thorax. 2005;60(11):925-931. [CrossRef] [PubMed]
 
Donaldson GC, Seemungal TA, Bhowmik A, Wedzicha JA. Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease. Thorax. 2002;57(10):847-852. [CrossRef] [PubMed]
 
Celli BR, Cote CG, Marin JM, et al. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(10):1005-1012. [CrossRef] [PubMed]
 
Agustí AG, Noguera A, Sauleda J, Sala E, Pons J, Busquets X. Systemic effects of chronic obstructive pulmonary disease. Eur Respir J. 2003;21(2):347-360. [CrossRef] [PubMed]
 
Seemungal TA, Wedzicha JA. Acute exacerbations of COPD: the challenge is early treatment. COPD. 2009;6(2):79-81. [CrossRef] [PubMed]
 
Puhan MA, Garcia-Aymerich J, Frey M, et al. Expansion of the prognostic assessment of patients with chronic obstructive pulmonary disease: the updated BODE index and the ADO index. Lancet. 2009;374(9691):704-711. [CrossRef] [PubMed]
 
Hurst JR, Donaldson GC, Perera WR, et al. Use of plasma biomarkers at exacerbation of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2006;174(8):867-874. [CrossRef] [PubMed]
 
Koutsokera A, Stolz D, Loukides S, Kostikas K. Systemic biomarkers in exacerbations of COPD: the evolving clinical challenge. Chest. 2012;141(2):396-405. [CrossRef] [PubMed]
 
Lacoma A, Prat C, Andreo F, et al. Value of procalcitonin, C-reactive protein, and neopterin in exacerbations of chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2011;6:157-169. [PubMed]
 
Stolz D, Christ-Crain M, Morgenthaler NG, et al. Plasma pro-adrenomedullin but not plasma pro-endothelin predicts survival in exacerbations of COPD. Chest. 2008;134(2):263-272. [CrossRef] [PubMed]
 
Prat C, Domínguez J, Andreo F, et al. Procalcitonin and neopterin correlation with aetiology and severity of pneumonia. J Infect. 2006;52(3):169-177. [CrossRef] [PubMed]
 
Bello S, Lasierra AB, Mincholé E, et al. Prognostic power of proadrenomedullin in community-acquired pneumonia is independent of aetiology. Eur Respir J. 2012;39(5):1144-1155. [CrossRef] [PubMed]
 
Stolz D, Christ-Crain M, Morgenthaler NG, et al. Copeptin, C-reactive protein, and procalcitonin as prognostic biomarkers in acute exacerbation of COPD. Chest. 2007;131(4):1058-1067. [CrossRef] [PubMed]
 
Linscheid P, Seboek D, Zulewski H, Keller U, Müller B. Autocrine/paracrine role of inflammation-mediated calcitonin gene-related peptide and adrenomedullin expression in human adipose tissue. Endocrinology. 2005;146(6):2699-2708. [CrossRef] [PubMed]
 
Yoshibayashi M, Kamiya T, Kitamura K, et al. Plasma levels of adrenomedullin in primary and secondary pulmonary hypertension in patients <20 years of age. Am J Cardiol. 1997;79(11):1556-1558. [CrossRef] [PubMed]
 
Cheung BM, Hwang IS, Li CY, et al. Increased adrenomedullin expression in lungs in endotoxaemia. J Endocrinol. 2004;181(2):339-345. [CrossRef] [PubMed]
 
Ichiki Y, Kitamura K, Kangawa K, Kawamoto M, Matsuo H, Eto T. Distribution and characterization of immunoreactive adrenomedullin in human tissue and plasma. FEBS Lett. 1994;338(1):6-10. [CrossRef] [PubMed]
 
Struck J, Tao C, Morgenthaler NG, Bergmann A. Identification of an adrenomedullin precursor fragment in plasma of sepsis patients. Peptides. 2004;25(8):1369-1372. [CrossRef] [PubMed]
 
Morgenthaler NG, Struck J, Alonso C, Bergmann A. Measurement of midregional proadrenomedullin in plasma with an immunoluminometric assay. Clin Chem. 2005;51(10):1823-1829. [CrossRef] [PubMed]
 
Vizza CD, Letizia C, Sciomer S, et al. Increased plasma levels of adrenomedullin, a vasoactive peptide, in patients with end-stage pulmonary disease. Regul Pept. 2005;124(1-3):187-193. [CrossRef] [PubMed]
 
Guertler C, Wirz B, Christ-Crain M, Zimmerli W, Mueller B, Schuetz P. Inflammatory responses predict long-term mortality risk in community-acquired pneumonia. Eur Respir J. 2011;37(6):1439-1446. [CrossRef] [PubMed]
 
von Haehling S, Filippatos GS, Papassotiriou J, et al. Mid-regional pro-adrenomedullin as a novel predictor of mortality in patients with chronic heart failure. Eur J Heart Fail. 2010;12(5):484-491. [CrossRef] [PubMed]
 
Janssen DJ, Spruit MA, Schols JM, et al. Predicting changes in preferences for life-sustaining treatment among patients with advanced chronic organ failure. Chest. 2012;141(5):1251-1259. [CrossRef] [PubMed]
 
Pauwels RA, Buist AS, Calverley PM, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) workshop summary. Am J Respir Crit Care Med. 2001;163(5):1256-1276. [CrossRef] [PubMed]
 
Telgen MC, Brusse-Keizer MG, van der Valk PD, van der Palen J, Kerstjens HA, Hendrix MG. Impact on clinical decision making of quality control standards applied to sputum analysis in COPD. Respir Med. 2011;105(3):371-376. [CrossRef] [PubMed]
 
Jougasaki M, Burnett JC Jr. Adrenomedullin: potential in physiology and pathophysiology. Life Sci. 2000;66(10):855-872. [CrossRef] [PubMed]
 
Behnes M, Papassotiriou J, Walter T, et al. Long-term prognostic value of mid-regional pro-adrenomedullin and C-terminal pro-endothelin-1 in patients with acute myocardial infarction. Clin Chem Lab Med. 2008;46(2):204-211. [CrossRef] [PubMed]
 
Khan SQ, O’Brien RJ, Struck J, et al. Prognostic value of midregional pro-adrenomedullin in patients with acute myocardial infarction: the LAMP (Leicester Acute Myocardial Infarction Peptide) study. J Am Coll Cardiol. 2007;49(14):1525-1532. [CrossRef] [PubMed]
 
Mahler DA, Wells CK. Evaluation of clinical methods for rating dyspnea. Chest. 1988;93(3):580-586. [CrossRef] [PubMed]
 
Huber-Carol C, Balakrishnan N, Nikulin MS, Mesbah M, eds.Goodness-of-Fit Tests and Model Validity. Boston, MA: Birkhäuser; 2002;273-277.
 
Kamoi H, Kanazawa H, Hirata K, Kurihara N, Yano Y, Otani S. Adrenomedullin inhibits the secretion of cytokine-induced neutrophil chemoattractant, a member of the interleukin-8 family, from rat alveolar macrophages. Biochem Biophys Res Commun. 1995;211(3):1031-1035. [CrossRef] [PubMed]
 
Sugo S, Minamino N, Shoji H, Kangawa K, Matsuo H. Effects of vasoactive substances and cAMP related compounds on adrenomedullin production in cultured vascular smooth muscle cells. FEBS Lett. 1995;369(2-3):311-314. [CrossRef] [PubMed]
 
Kohno M, Hanehira T, Hirata K, et al. An accelerated increase of plasma adrenomedullin in acute asthma. Metabolism. 1996;45(11):1323-1325. [CrossRef] [PubMed]
 
Stolz D, Christ-Crain M, Bingisser R, et al. Antibiotic treatment of exacerbations of COPD: a randomized, controlled trial comparing procalcitonin-guidance with standard therapy. Chest. 2007;131(1):9-19. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. Kaplan-Meier survival curves for MR-proADM and PCT in the stable state and at an AECOPD. A, MR-proADM stable state. B, MR-proADM AECOPD. C, PCT stable state. D, PCT AECOPD. AECOPD = acute exacerbation of COPD; MR-proADM = midrange-proadrenomedullin; PCT = procalcitonin.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Baseline Characteristics

Data are shown as mean (SD) unless otherwise indicated. ADO = age, dyspnea, and airflow obstruction; GOLD = Global Initiative for Chronic Obstructive Lung Disease; mMRC = modified Medical Research Council; VC = vital capacity.

a 

Scores of 180 patients.

Table Graphic Jump Location
Table 2 —MR-proADM and PCT Results

IQR = interquartile range; MR-proADM = midrange-proadrenomedullin; PCT = procalcitonin.

Table Graphic Jump Location
Table 3 —Survival Analysis

AECOPD = acute exacerbation of COPD; cHR = HR corrected for age, sex, BMI, and GOLD status; HR = hazard ratio. See Table 1 and 2 legends for expansion of other abbreviations.

a 

Above or below study median (0.71 nmol/L).

b 

Above or below study median (0.79 nmol/L).

c 

Above or below study median (0.84 nmol/L) in study by Stolz et al.17

d 

Above or below study median (0.05 ng/mL).

e 

Above or below study median (0.06 ng/mL).

Table Graphic Jump Location
Table 4 —1- and 2-y Mortality Risk

AUC = area under the curve; cOR = corrected OR for sex, age, BMI, and GOLD stage; RR = relative risk. See Table 1, 2, and 3 legends for expansion of other abbreviations.

References

Murray CJ, Lopez AD. Global mortality, disability, and the contribution of risk factors: Global Burden of Disease Study. Lancet. 1997;349(9063):1436-1442. [CrossRef] [PubMed]
 
Sapey E, Stockley RA. COPD exacerbations. 2: aetiology. Thorax. 2006;61(3):250-258. [CrossRef] [PubMed]
 
Anthonisen NR, Wright EC, Hodgkin JE. Prognosis in chronic obstructive pulmonary disease. Am Rev Respir Dis. 1986;133(1):14-20. [PubMed]
 
Schols AM, Broekhuizen R, Weling-Scheepers CA, Wouters EF. Body composition and mortality in chronic obstructive pulmonary disease. Am J Clin Nutr. 2005;82(1):53-59. [PubMed]
 
Nishimura K, Izumi T, Tsukino M, Oga T. Dyspnea is a better predictor of 5-year survival than airway obstruction in patients with COPD. Chest. 2002;121(5):1434-1440. [CrossRef] [PubMed]
 
Cote CG, Casanova C, Marín JM, et al. Validation and comparison of reference equations for the 6-min walk distance test. Eur Respir J. 2008;31(3):571-578. [CrossRef] [PubMed]
 
Oga T, Nishimura K, Tsukino M, Sato S, Hajiro T. Analysis of the factors related to mortality in chronic obstructive pulmonary disease: role of exercise capacity and health status. Am J Respir Crit Care Med. 2003;167(4):544-549. [CrossRef] [PubMed]
 
Soler-Cataluña JJ, Martínez-García MA, Román Sánchez P, Salcedo E, Navarro M, Ochando R. Severe acute exacerbations and mortality in patients with chronic obstructive pulmonary disease. Thorax. 2005;60(11):925-931. [CrossRef] [PubMed]
 
Donaldson GC, Seemungal TA, Bhowmik A, Wedzicha JA. Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease. Thorax. 2002;57(10):847-852. [CrossRef] [PubMed]
 
Celli BR, Cote CG, Marin JM, et al. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(10):1005-1012. [CrossRef] [PubMed]
 
Agustí AG, Noguera A, Sauleda J, Sala E, Pons J, Busquets X. Systemic effects of chronic obstructive pulmonary disease. Eur Respir J. 2003;21(2):347-360. [CrossRef] [PubMed]
 
Seemungal TA, Wedzicha JA. Acute exacerbations of COPD: the challenge is early treatment. COPD. 2009;6(2):79-81. [CrossRef] [PubMed]
 
Puhan MA, Garcia-Aymerich J, Frey M, et al. Expansion of the prognostic assessment of patients with chronic obstructive pulmonary disease: the updated BODE index and the ADO index. Lancet. 2009;374(9691):704-711. [CrossRef] [PubMed]
 
Hurst JR, Donaldson GC, Perera WR, et al. Use of plasma biomarkers at exacerbation of chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2006;174(8):867-874. [CrossRef] [PubMed]
 
Koutsokera A, Stolz D, Loukides S, Kostikas K. Systemic biomarkers in exacerbations of COPD: the evolving clinical challenge. Chest. 2012;141(2):396-405. [CrossRef] [PubMed]
 
Lacoma A, Prat C, Andreo F, et al. Value of procalcitonin, C-reactive protein, and neopterin in exacerbations of chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2011;6:157-169. [PubMed]
 
Stolz D, Christ-Crain M, Morgenthaler NG, et al. Plasma pro-adrenomedullin but not plasma pro-endothelin predicts survival in exacerbations of COPD. Chest. 2008;134(2):263-272. [CrossRef] [PubMed]
 
Prat C, Domínguez J, Andreo F, et al. Procalcitonin and neopterin correlation with aetiology and severity of pneumonia. J Infect. 2006;52(3):169-177. [CrossRef] [PubMed]
 
Bello S, Lasierra AB, Mincholé E, et al. Prognostic power of proadrenomedullin in community-acquired pneumonia is independent of aetiology. Eur Respir J. 2012;39(5):1144-1155. [CrossRef] [PubMed]
 
Stolz D, Christ-Crain M, Morgenthaler NG, et al. Copeptin, C-reactive protein, and procalcitonin as prognostic biomarkers in acute exacerbation of COPD. Chest. 2007;131(4):1058-1067. [CrossRef] [PubMed]
 
Linscheid P, Seboek D, Zulewski H, Keller U, Müller B. Autocrine/paracrine role of inflammation-mediated calcitonin gene-related peptide and adrenomedullin expression in human adipose tissue. Endocrinology. 2005;146(6):2699-2708. [CrossRef] [PubMed]
 
Yoshibayashi M, Kamiya T, Kitamura K, et al. Plasma levels of adrenomedullin in primary and secondary pulmonary hypertension in patients <20 years of age. Am J Cardiol. 1997;79(11):1556-1558. [CrossRef] [PubMed]
 
Cheung BM, Hwang IS, Li CY, et al. Increased adrenomedullin expression in lungs in endotoxaemia. J Endocrinol. 2004;181(2):339-345. [CrossRef] [PubMed]
 
Ichiki Y, Kitamura K, Kangawa K, Kawamoto M, Matsuo H, Eto T. Distribution and characterization of immunoreactive adrenomedullin in human tissue and plasma. FEBS Lett. 1994;338(1):6-10. [CrossRef] [PubMed]
 
Struck J, Tao C, Morgenthaler NG, Bergmann A. Identification of an adrenomedullin precursor fragment in plasma of sepsis patients. Peptides. 2004;25(8):1369-1372. [CrossRef] [PubMed]
 
Morgenthaler NG, Struck J, Alonso C, Bergmann A. Measurement of midregional proadrenomedullin in plasma with an immunoluminometric assay. Clin Chem. 2005;51(10):1823-1829. [CrossRef] [PubMed]
 
Vizza CD, Letizia C, Sciomer S, et al. Increased plasma levels of adrenomedullin, a vasoactive peptide, in patients with end-stage pulmonary disease. Regul Pept. 2005;124(1-3):187-193. [CrossRef] [PubMed]
 
Guertler C, Wirz B, Christ-Crain M, Zimmerli W, Mueller B, Schuetz P. Inflammatory responses predict long-term mortality risk in community-acquired pneumonia. Eur Respir J. 2011;37(6):1439-1446. [CrossRef] [PubMed]
 
von Haehling S, Filippatos GS, Papassotiriou J, et al. Mid-regional pro-adrenomedullin as a novel predictor of mortality in patients with chronic heart failure. Eur J Heart Fail. 2010;12(5):484-491. [CrossRef] [PubMed]
 
Janssen DJ, Spruit MA, Schols JM, et al. Predicting changes in preferences for life-sustaining treatment among patients with advanced chronic organ failure. Chest. 2012;141(5):1251-1259. [CrossRef] [PubMed]
 
Pauwels RA, Buist AS, Calverley PM, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) workshop summary. Am J Respir Crit Care Med. 2001;163(5):1256-1276. [CrossRef] [PubMed]
 
Telgen MC, Brusse-Keizer MG, van der Valk PD, van der Palen J, Kerstjens HA, Hendrix MG. Impact on clinical decision making of quality control standards applied to sputum analysis in COPD. Respir Med. 2011;105(3):371-376. [CrossRef] [PubMed]
 
Jougasaki M, Burnett JC Jr. Adrenomedullin: potential in physiology and pathophysiology. Life Sci. 2000;66(10):855-872. [CrossRef] [PubMed]
 
Behnes M, Papassotiriou J, Walter T, et al. Long-term prognostic value of mid-regional pro-adrenomedullin and C-terminal pro-endothelin-1 in patients with acute myocardial infarction. Clin Chem Lab Med. 2008;46(2):204-211. [CrossRef] [PubMed]
 
Khan SQ, O’Brien RJ, Struck J, et al. Prognostic value of midregional pro-adrenomedullin in patients with acute myocardial infarction: the LAMP (Leicester Acute Myocardial Infarction Peptide) study. J Am Coll Cardiol. 2007;49(14):1525-1532. [CrossRef] [PubMed]
 
Mahler DA, Wells CK. Evaluation of clinical methods for rating dyspnea. Chest. 1988;93(3):580-586. [CrossRef] [PubMed]
 
Huber-Carol C, Balakrishnan N, Nikulin MS, Mesbah M, eds.Goodness-of-Fit Tests and Model Validity. Boston, MA: Birkhäuser; 2002;273-277.
 
Kamoi H, Kanazawa H, Hirata K, Kurihara N, Yano Y, Otani S. Adrenomedullin inhibits the secretion of cytokine-induced neutrophil chemoattractant, a member of the interleukin-8 family, from rat alveolar macrophages. Biochem Biophys Res Commun. 1995;211(3):1031-1035. [CrossRef] [PubMed]
 
Sugo S, Minamino N, Shoji H, Kangawa K, Matsuo H. Effects of vasoactive substances and cAMP related compounds on adrenomedullin production in cultured vascular smooth muscle cells. FEBS Lett. 1995;369(2-3):311-314. [CrossRef] [PubMed]
 
Kohno M, Hanehira T, Hirata K, et al. An accelerated increase of plasma adrenomedullin in acute asthma. Metabolism. 1996;45(11):1323-1325. [CrossRef] [PubMed]
 
Stolz D, Christ-Crain M, Bingisser R, et al. Antibiotic treatment of exacerbations of COPD: a randomized, controlled trial comparing procalcitonin-guidance with standard therapy. Chest. 2007;131(1):9-19. [CrossRef] [PubMed]
 
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).
Supporting Data

Online Supplement

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Find Similar Articles
CHEST Journal Articles
  • CHEST Journal
    Print ISSN: 0012-3692
    Online ISSN: 1931-3543