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European Journal of Heart Failure 2005 7(4):557-565; doi:10.1016/j.ejheart.2004.06.004
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© 2005 European Society of Cardiology

A direct comparison of the natriuretic peptides and their relationship to survival in chronic heart failure of a presumed non-ischaemic origin

Eric Stantona,*, Mark Hansenb, Hairinda C. Wijeysunderac, Peter Kupchakd, Christian Halle, Jean L. Rouleauf,1 and On behalf of the PRAISE-2 study investigators

a McMaster University, St. Joseph's Hospital 50 Charlton Avenue East, Hamilton, ON, Canada L8N 4A6
b Faculty of Medicine, Division of Cardiology, University Health Network, Toronto General Hospital Canada
c Cardiology Fellow, Faculty of Medicine, University of Toronto Canada
d SYN·X Pharma Inc. Toronto, Canada
e Research Institute for Internal Medicine, Faculty of Medicine, University of Oslo Norway
f Searle Chair in Cardiovascular Research Canada

* Corresponding author. Tel.: +1 905 521 6058; Fax: +1 905 521 6068. E-mail address: stantone{at}mcmaster.ca


   Abstract
Top
 Notes
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
The natriuretic peptides have been validated as sensitive and specific markers of left ventricular dysfunction; brain natriuretic peptide (BNP), N-terminal atrial natriuretic peptide (NT-proANP) and N-terminal brain natriuretic peptide (NT-proBNP) elevations have been associated with New York Heart Association (NYHA) Class I–IV heart failure. We directly compared the association of each of these markers with 1-year survival in 173 patients with chronic heart failure of a presumed nonischaemic origin entering the PRAISE-2 Trial, a clinical study which assessed the therapeutic effect of Amlodipine in patients with NYHA Class III and IV heart failure and a left ventricular ejection fraction (LVEF) <30%. BNP, NT-proBNP, and NT-proANP levels were all correlated with 1-year mortality by univariate Cox proportional hazards analyses. With respect to multivariate Cox proportional hazards regression models containing variables deemed significant in univariate analyses, NT-proANP alone was identified as an independent predictor of 1-year mortality when log-transformed continuous covariates were utilized in the analysis. When the analysis was repeated using dichotomous covariates, NT-proANP remained the most significant predictor of 1-year mortality, followed by NT-proBNP, NYHA classification and BNP. We conclude that all three natriuretic peptides are significant predictors of short-term mortality in subjects with chronic congestive heart failure (CHF) of a presumed nonischaemic origin. Larger prospective studies are required to validate the clinical utility of NT-proANP as a discriminating marker of short-term survival, and to validate proposed cutoffs of approximately 2300 pmol/l for NT-proANP, 1500 pg/ml for NT-proBNP, and 50 pmol/l for BNP as prognostic indicators of adverse short-term outcome.

Key Words: Heart failure • Natriuretic peptides • Survival

Received September 4, 2003; Revised May 12, 2004; Accepted June 27, 2004


   1. Introduction
Top
 Notes
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
Despite the recent advances that have been made in terms of treatment options for congestive heart failure (CHF) subjects, prognosis remains poor, particularly for patients with New York Heart Association (NYHA) Class III and IV CHF [1,2]. It is thus extremely important from a clinical perspective to be able to identify subjects who are at extreme risk of short-term mortality, in order to be able to assign them to treatments which offer them greater hope of near-term survival. Indeed, many approaches have been developed, many of them evaluating demographic variables, measures of neurohormones or oxidative stress, and measures of LV function or electrophysiologic markers [3]. Lee et al. [35] derived and validated a model in a large community-based cohort in order to identify independent demographic and clinical predictors of 1-year mortality in heart failure patients. Elevated norepinephrine levels have been associated with higher mortality rates in severe heart failure subjects with reduced left ventricular ejection fractions (LVEF) [16] and in subjects with asymptomatic left ventricular dysfunction [31]. Elevated serum creatinine levels have been shown to be independently predictive of mortality in subjects with newly diagnosed heart failure [32], and reduced creatinine clearance has been associated with increased risk of mortality in patients with asymptomatic and symptomatic left ventricular dysfunction [33] and in ambulatory patients with CHF [34]. Adrenolutin, a marker of oxidative stress, has been associated with poor prognosis in severe heart failure subjects [18].

Natriuretic peptides, a class of cardiac neurohormones first described by de Bold et al. [4], are a group of homologous yet genetically distinct molecules which play a role in renal, endocrine and cardiovascular homeostasis [5,6]. Atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) are of myocardial cell origin, and are synthesized as high molecular weight precursors, which are cleaved to give the corresponding amino-terminal segment of the precursor molecule (NT-proANP and NT-proBNP, respectively) and the biologically active peptide. Natriuretic peptides are released in response to increased cardiac volume and pressure overload typical of CHF. BNP has been demonstrated to be a good prognostic indicator in patients with acute coronary syndromes and is useful in differentiating between patients presenting to an emergency department with dyspnea due to congestive heart failure and dyspnea due to noncardiac causes [7,8]. NT-proBNP is also an independent predictor of long-term mortality in patients with acute coronary syndromes and CHF [9,10]. Clinical treatment guided by plasma NT-proBNP concentrations has been shown to reduce the risk of a subsequent cardiovascular event [11]. NT-proANP has been shown to differentiate between asymptomatic (NYHA Class I) heart failure subjects and control subjects [12], and is an independent predictor of mortality in CHF subjects with preserved systolic function [13].

There is very little comparative data on the various natriuretic peptides in predicting survival in advanced Class III and IV heart failure. The aim of our study was to directly compare BNP, NT-proBNP, and NT-proANP in the same study population, in order to determine whether the natriuretic peptides were independent predictors of 1-year survival, and to determine the relative abilities of these natriuretic peptides in predicting 1-year survival in subjects with NYHA class III or IV heart failure of a presumed nonischaemic origin, after adjusting for other previously established predictors of survival.


   2. Methods
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
The Prospective Randomized Amlodipine Survival Evaluation 2 (PRAISE-2) study was a multicenter, randomized, double-blinded, parallel group, placebo-controlled study to evaluate the effect of amlodipine on survival in patients with congestive heart failure of a presumed nonischaemic etiology. A total of 181 subjects from the PRAISE-2 trial were enrolled in the neurohormone substudy, with 99 subjects assigned to the placebo group and 82 subjects assigned to the amlodipine group. A synopsis of the study design and methodology has been provided elsewhere [14].

2.1. Assays of neurohormones
Neurohormones, markers of oxidative stress and NT-proANP were measured as previously described [15–18]. BNP concentration was measured by the commercial immunoradiometric assay from Shionogi, as previously described [14]. The NT-proANP assay has a detection limit of 185 pmol/l, an interassay coefficient of variation (CV) of 6.3% at a mean level of 976 pmol/l, an intraassay CV of 4.1% at a mean level of 1033 pmol/l, and a mean recovery of 85% [28]. NT-proBNP concentration was measured at SYN-X Pharma in Toronto, Canada, employing a sandwich enzyme-linked immunosorbant assay (ELISA) consisting of a goat polyclonal anti-NT-proBNP capture protein and a biotinylated goat polyclonal anti-NT-proBNP detector antibody. The NT-proBNP assay has a detection limit of 13 pg/ml, an interassay CV of 3.1% at a mean level of 1000 pg/ml, an intraassay CV of 1.6% at a mean level of 1000 pg/ml and a mean recovery of 97% [36]. The NT-proANP and NT-proBNP assays used in this study are not available commercially.

2.2. Statistical analysis
The univariate and multivariate Cox proportional hazards analyses showing the association of NT-proANP, BNP, neurohormones, markers of oxidative stress and demographic variables with overall survival have been reported elsewhere [14] with NYHA class, age, creatinine, norepinephrine, dopamine, NT-proANP and BNP having been identified as significant individual predictors of survival.

The effect of treatment (amlodipine vs. placebo) on 1-year survival was assessed using Fisher's exact test, and the effect of treatment on total survival time (in days) was assessed with a Kaplan–Meier survival curve and by employing a log-rank test. The relationships between quartiles of each of the natriuretic peptide baseline levels and 1-year mortality were also assessed using Kaplan–Meier survival curves and log-rank tests.

Of the significant predictors (NYHA class, age, creatinine, norepinephrine, dopamine) listed above, a stepwise multivariate Cox regression model was developed to determine which of these remained independent predictors of 1-year mortality, with an adjusted p-value of less than 0.05 (as determined by a likelihood ratio test) required for inclusion in the model. The ability of each of the natriuretic peptides to independently predict 1-year survival was assessed, after adjusting for the other variables deemed to be significant in the stepwise procedure described above. As most of the continuous covariates followed sharply right-skewed distributions (with the exception of age, which was approximately normally distributed), logarithmic transformations were performed prior to analysis, with Shapiro–Wilk tests of normality being used to assess the appropriateness of the transformations. Finally, a multivariate model was fitted using all three natriuretic peptides and the other variables deemed to be significant from the stepwise procedure above, to determine which of the natriuretic peptides (if any) remained independent predictors of 1-year mortality. The model fit was repeated, by forcing the effect of treatment into the model. The univariate analyses of continuous variables were repeated using penalized B-spline fits [29], and for each continuous variable, the hypothesis of linear contribution to the log hazard function was assessed.

Receiver operating characteristic (ROC) curves were generated for each of the natriuretic peptides with respect to 1-year outcome status, and areas under the curve (AUCs) were computed for each marker. Pairwise comparisons of AUC values between markers were conducted following the procedure of Hanley and McNeil [19]. For each natriuretic peptide, an optimal cutoff value was obtained from the ROC analysis; the relative risk of suffering a fatal event within 1 year of enrollment for subjects with baseline levels above vs. below the cutoff were determined for each marker. Age, creatinine, norepinephrine, and dopamine were also dichotomized by determining optimal cutoffs for each via univariate ROC analyses. The Cox proportional hazards regression analyses as described above were all repeated, using these dichotomized variables in place of their respective continuous covariates.

For each natriuretic peptide marker, a cutoff value was also found by taking the 90th percentile with respect to the subset of subjects who survived for a minimum of 1 year following enrollment in the study; this was done in order to compare the relative abilities of the natriuretic peptides to predict 1-year mortality at fixed specificity levels. The Cox proportional hazard regression analyses as described above were all repeated, using these new dichotomized variables.

Internal validation of each of the models derived from the Cox proportional hazards analyses was conducted by generating 100 bootstrap replicates of the data set (using only the variables selected in the original model), performing stepwise multivariate Cox regression analyses with an inclusion criterion of p=0.05, and determining the relative frequency with which each individual variable appeared in the chosen model. Variables which appeared in the chosen models less than 30% of the time were considered for deletion from the final model [30]. The procedure was repeated using p=0.01 as an inclusion criterion. For the final models, proportional hazard assumptions were assessed via plots of martingale residuals from models omitting continuous variables of interest vs. the variables themselves. In order to identify potentially influential subjects, DFBETAS plots for continuous variables of interest were generated [37].

Receiver operating characteristic (ROC) curve analyses were performed using MedCalc Version 7.1 (MedCalc Software, Mariakerke, Belgium); all other statistical analyses were conducted using S-Plus Version 6 for Windows (Insightful, Seattle, WA).


   3. Results
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
3.1. Study subjects
A total of 181 subjects from the larger PRAISE-2 trial were enrolled in the neurohormone substudy. A comparison of baseline demographics between the substudy and the larger study is given in Table 1; there were slightly higher proportions of males and of NYHA Class III subjects in the substudy. Of the 181 subjects in the substudy, 99 subjects were assigned to the placebo group and 82 subjects were assigned to the amlodipine group (Table 2). There were no significant differences in baseline demographic characteristics between the amlodipine group and the placebo group.


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  		Table 1 Comparison of baseline demographics between PRAISE-2 neurohormone substudy cohort and larger PRAISE-2 study

 


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  		Table 2 Baseline demographics of PRAISE-2 neurohormone substudy cohort

 
3.2. Treatment and 1-year mortality
Of the 181 subjects, eight did not suffer from fatal events yet were not followed up for a minimum 1-year period. Therefore, the present analysis was conducted on the subset of 173 subjects who either died within 1 year or survived for a minimum of 1 year following baseline. Of these 173 subjects, 78 were assigned to amlodipine therapy, 11 of whom died within 1 year of study enrollment (14.1%). In contrast, 16 of the 95 subjects assigned to placebo died within 1 year of study enrollment (16.8%); the difference in mortality rates was not significant (Fisher's exact p=0.678; log rank p=0.658 when comparing 1-year survival curves; Fig. 1).


Figure 1
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  		Fig. 1 Kaplan–Meier 1-year survival curves, stratified by treatment group.

 
3.3. Natriuretic peptides and 1-year mortality
Baseline levels of all three natriuretic peptides were available for 153 of the study subjects. Table 3 displays 1-year mortality rates stratified by quartiles of baseline levels of BNP, NT-proBNP, and NT-proANP, respectively, with respect to this subset of subjects. Mortality rates increase with increasing quartile of each of the natriuretic peptides (p<0.002 in each case when applying a test of trend).


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  		Table 3 One-year mortality rates for PRAISE-2 patients, stratified by quartiles of natriuretic peptide levels

 
3.4. Cox regression analysis with continuous covariates
When applying univariate Cox proportional hazards regression models with the 1-year mortality data, one found that NYHA class (p<0.01 LR test), age (p=0.043) and creatinine (p=0.048) were significant individual predictors, with dopamine (p=0.09) not being a significant predictor at the p=0.05 level. After adjusting for NYHA class, only dopamine (p=0.039) provided additional significant prognostic information regarding 1-year mortality. However, validation procedures utilizing bootstrap replicates of the data suggested that dopamine was a weak predictor, as it was included in only 32% of chosen models with p=0.05 as an inclusion criterion, and in only 17% of chosen models with p=0.01 as an inclusion criterion. NYHA class alone remained as a predictor of 1-year mortality, as it was included in 72% of chosen models with p=0.05 as an inclusion criterion, and in 52% of chosen models with p=0.01 as an inclusion criterion. Therefore, dopamine was excluded from the model utilizing continuous covariates.

Multivariate Cox proportional hazards models revealed that each of the natriuretic peptides were independent individual predictors of short-term mortality after adjusting for NYHA class (p=0.003 for BNP; p=0.0005 for NT-proBNP; p<0.0001 for NT-proANP). In a multivariate Cox proportional hazard model including NYHA class and baseline levels of all three natriuretic peptides, the only variable which remained significant was the baseline NT-proANP level (p=0.005). The results were unaltered when treatment was forced into the above multivariate model (Table 4).


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  		Table 4 Multivariate Cox proportional hazards models relating 1-year mortality to covariates deemed significant in univariate analyses

 
3.5. ROC analysis
ROC curve analyses revealed that the area under the curve (AUC) for NT-proANP (AUC=0.793) was greater than that for NT-proBNP (0.744) or BNP (0.734) in terms of distinguishing between those who survived a minimum of 1 year from those who died within 1 year of enrollment (Fig. 2). Pairwise comparisons reveal that none of the differences in AUC values related to 1-year mortality were significant. From the ROC curves, the optimal cutoff levels were determined to be 56.4 pmol/l for BNP, 975 pg/ml for NT-proBNP, and 2300 pmol/l for NT-proANP. All three natriuretic peptides were significant individual predictors of 1-year mortality when these cutoffs were employed (Table 5).


Figure 2
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  		Fig. 2 ROC curves for natriuretic peptides as markers of 1-year mortality.

 


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  		Table 5 One-year mortality rates for PRAISE-2 patients, stratified by natriuretic peptide levels using ROC-derived cutoffs

 
3.6. Cox regression analysis with dichotomous covariates
After adjusting for NYHA class, only a creatinine level of greater than 1.1 mg/dl provided additional significant prognostic information regarding 1-year mortality (p=0.034). As a dichotomous variable, dopamine (cutoff of 117.4 pg/ml) was no longer significant after adjusting for NYHA class (p=0.065). Validation procedures utilizing bootstrap replicates of the data suggested that both NYHA class and a creatinine level of greater than 1.1 mg/dl were predictors of 1-year mortality (included in 68% and 61% of chosen models with p=0.05 as an inclusion criterion, respectively, and in 45% and 38% of chosen models with p=0.01 as an inclusion criterion, respectively). Each of the natriuretic peptides were independent individual predictors of short-term mortality after adjusting for NYHA class and creatinine (p=0.005 for BNP; p=0.013 for NT-proBNP; p=0.003 for NT-proANP).

It is interesting to note that the optimal cutoffs occur at different sensitivity levels for the different natriuretic peptides with respect to predicting 1-year mortality (26.3% for BNP; 32.7% for NT-proBNP; 35.3% for NT-proANP; see Table 5). In order to compare the relative predictive abilities of the natriuretic peptides at fixed specificity levels, cutoff levels were recalculated by estimating the 90th percentile of the distribution of each marker for subjects who survived for a minimum of 1 year. The cutoff levels were determined to be 183 pmol/l for BNP, 1482 pg/ml for NT-proBNP and 3902 pmol/l for NT-proANP. Table 6 displays the mortality rates for patients with natriuretic peptide levels above and below the designated cutoff levels; again, all three natriuretic peptides were significant individual predictors of 1-year mortality, but the greatest relative risk of mortality was associated with elevated NT-proBNP levels. Figs. 3, 4 and 5 display Kaplan–Meier survival curves for subjects with marker levels above and below the cutoff levels for BNP, NT-proBNP and NT-proANP, respectively. After adjusting for NYHA class and creatinine, only an NT-proBNP level above 1482 pg/ml predicted 1-year mortality (p=0.013), whereas a BNP level above 183 pmol/l (p=0.398) and an NT-proANP level above 3902 pmol/l (p=0.205) did not. In a multivariate Cox proportional hazards model including NYHA class, creatinine and all three natriuretic peptides as dichotomous variables with the above cutoffs, the only variables which remained significant were NYHA class (p=0.050) and NT-proBNP (p=0.013). When treatment was forced into the above multivariate model, NT-proBNP remained significant (p=0.023) but the prognostic ability of NYHA class was somewhat diminished (p=0.058).


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  		Table 6 One-year mortality rates for PRAISE-2 patients, stratified by natriuretic peptide levels using cutoffs reflecting fixed specificity levels

 


Figure 3
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  		Fig. 3 Kaplan–Meier curves, stratified by baseline BNP level cutoff.

 


Figure 4
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  		Fig. 4 Kaplan–Meier curves, stratified by baseline NT-proBNP level cutoff.

 


Figure 5
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  		Fig. 5 Kaplan–Meier curves, stratified by baseline NT-proANP level cutoff.

 
Validation procedures utilizing bootstrap replicates of the data were conducted utilizing cutoffs of 56.4 pmol/l for BNP and 2300 pmol/l for NT-proANP (optimal ROC cutoffs) and 1482 pg/ml for NT-proBNP (cutoff reflecting 90% specificity). The results are summarized in Table 7; NT-proANP remained the strongest predictor of 1-year mortality, with NYHA class and NT-proBNP being weaker contributors to the overall model. The 1-year mortality rate was 6% for subjects with baseline NT-proANP levels lower than 2300 pmol/l and 35% for subjects with NT-proANP levels above this cutoff (Table 5); the 1-year mortality rate increased to 57% (8/14) with respect to the subset of NYHA Class IV subjects with elevated NT-proANP levels, and 86% (6/7) with respect to the subset of NYHA Class IV subjects with elevated levels of both NT-proANP and NT-proBNP.


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  		Table 7 Results of internal validation procedure conducted on 100 bootstrap replicates of the original data set, using the dichotomous variables at the specified cutoffs

 
3.7. Assessment of Cox models
For each continuous variable, the nonlinear contribution to the log-hazard function was not found to be statistically significant when univariate analyses were performed utilizing penalized B-spline fits (p>0.05 in each case). The assumption of proportional hazards was not violated for any of the continuous variables included in the final model-building analyses. One influential subject was identified (cardiac death 212 days subsequent to baseline; BNP, NT-proBNP and NT-proANP levels of 3 pmol/l, 212 pg/ml and 1726 pmol/l, respectively). The exclusion of this subject from the data set would have resulted in a slight elevation of the coefficient estimates for the respective natriuretic peptides, with the overall statistical conclusions remaining unchanged.


   4. Discussion
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
Several studies have demonstrated that elevated levels of natriuretic peptides are important independent predictors of outcome in patients presenting with an acute coronary syndrome [9,20,21]. Ishii et al. [22] demonstrated that BNP was an independent predictor of cardiac outcomes including death in patients presenting to hospital with worsening chronic heart failure. McDonagh et al. [23] reported using a multivariate analysis that BNP but not NT-proANP was an independent predictor of mortality in patients with left ventricular dysfunction. Andersson and Hall [13] concluded that NT-proANP was an independent marker of increased mortality and morbidity in patients with heart failure and preserved systolic function. However, there is little data available comparing the plasma levels of BNP, NT-proBNP, and NT-proANP and their relationship to survival in patients with chronic stable CHF of a presumed nonischaemic etiology. Hammerer-Lercher et al. [24] performed a head to head comparison of NT-proBNP, BNP, and NT-proANP in the detection of heart failure. Although there was no difference between NT-proBNP, BNP, and NT-proANP in the detection of impaired left ventricular function, both BNP and NT-proBNP (but not NT-proANP) correlated negatively with the resting LVEF. However, their study provided no mortality data.

Our results show that increased plasma levels of BNP, NT-proBNP, and NT-proANP were all independent predictors of mortality in patients with stable chronic heart failure of a presumed nonischaemic origin. The reason for the superiority of natriuretic peptides over other proven indicators of poor prognosis in this patient population is not clear, but may be related to the cardiac origin of natriuretic peptides, a characteristic that makes them more sensitive markers of cardiac stress and injury [3,18,26]. However, the possibility that undiscovered chronic ischaemia may have contributed to the death of some of the study subjects cannot be excluded. NT-proANP appeared to show the most promise when log-transformed continuous covariates were introduced into a multivariate Cox proportional hazards model, and elevated levels of NT-proANP and NT-proBNP appeared to identify patients at immediate risk of short-term mortality, especially among the subset of NYHA Class IV subjects, when dichotomous covariates were considered. One possible explanation for this may relate to the difference in the clearance rate of the active BNP compared to the inactive N-terminal fragments of both proANP and proBNP. The clearance of both ANP and BNP from the circulation results from enzymatic degradation by neutral endopeptidase and through the C-type natriuretic receptor. The inactive N-terminal fragments of proANP and proBNP have no specific clearance receptors, and consequently, these peptides circulate in a higher concentration than the active fragments [25].

Gardner et al. [27] recently reported the results of a prospective study in which 142 patients with advanced heart failure and referred for consideration of cardiac transplantation were followed up for a median of approximately 1 year. Their results showed that an NT-proBNP baseline level of 1490 pg/ml was the only independent predictor of all-cause mortality when compared with other standard clinical markers used in determining candidates for immediate transplantation, and they quoted a relative risk of 4.0 and an AUC of 0.738 for NT-proBNP as a predictor of short-term mortality in these patients. The present analysis reveals remarkably similar performance metrics for NT-proBNP, with a relative risk of 1-year mortality of 4.04 (Table 3) and an AUC of 0.744 (Fig. 5) with respect to a cutoff of 1482 pg/ml. It would appear that this cutoff is robust in predicting who will be at immediate risk of short-term mortality, whether the patients at risk have advanced heart failure and are of immediate need of transplantation as in the Gardner et al. study or whether they have stable chronic heart failure of a presumed nonischaemic origin as in the present study. However, the NT-proBNP measurements were made on a Roche Elecsys 2010 analyzer in the Gardner et al. study, whereas the NT-proBNP assay utilized in the present study was an ELISA that is not commercially available. Further studies in a larger cohort will be required to validate the cutoff of 1500 pg/ml for NT-proBNP as a prognostic indicator of outcome, using a generally available commercial assay.

The present study suggests that natriuretic peptides are independent predictors of short-term mortality in patients with NYHA class III or IV chronic heart failure of a presumed nonischaemic origin and with a very low concomitant LVEF. NT-proANP appears to hold particular promise as a marker of short-term mortality, and should be investigated in a larger prospective study to confirm its clinical utility in this respect. The proposed cutoffs of approximately 2300 pmol/l for NT-proANP, 1500 pg/ml for NT-proBNP, and 50 pmol/l for BNP should also be validated as prognostic indicators of adverse short-term outcome in a larger prospective study, using generally available commercial assays.


   Notes
Top
 Notes
Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
1 Present Address: Faculty of Medicine, University of Montreal, 2900 Edouard Montpetit Boulevard, Montreal, Quebec, Canada H3C 3J4. Back


   References
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 

  1. Ho K.K., Anderson K.M., Kannel W.B., Grossman W., Levy D. Survival after the onset of congestive heart failure in Framingham Heart Study subjects. Circulation (1993) 88:107–115.[Abstract/Free Full Text]
  2. Bentkover J.D., Stewart E.J., Ignaszewski A., Lepage S., Liu P., Cooper J. New technologies and potential cost savings related to morbidity and mortality reduction in Class III/IV heart failure patients in Canada. International Journal of Cardiology (2002) 88:33–41.[CrossRef][Web of Science]
  3. Kjaer A., Hesse B. Heart failure and neuroendocrine activation: diagnostic, prognostic and therapeutic perspectives. Clinical Physiology (2001) 21:661–672.[CrossRef][Web of Science][Medline]
  4. de Bold A.J., Borenstein H.B., Veress A.T., Sonnenberg H. A rapid and potent natriuretic response to intravenous injection of atrial myocardial extracts in rats. Life Sciences (1981) 28:89–94.[CrossRef][Web of Science][Medline]
  5. Sagnella G.A. Measurement and importance of plasma brain natriuretic peptide and related peptides. Annals of Clinical Biochemistry (2001) 38:83–93.[Free Full Text]
  6. Boomsma F., van den Meiracker A.H. Plasma A- and B-type natriuretic peptides: physiology, methodology and clinical use. Cardiovascular Research (2001) 51:442–449.[Free Full Text]
  7. de Lemos J.A., Morrow D.A., Bentley J.H., Omland T., Sabatine M.S., McCabe C.H., et al. The prognostic value of B-type natriuretic peptide in patients with acute coronary syndromes. The New England Journal of Medicine (2001) 345(14):1014–1021.[Abstract/Free Full Text]
  8. Maisel A.S., Krishnaswamy P., Nowak R.M., McCord J., Hollander J.E., Duc P., et al. Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure. New England Journal of Medicine (2002) 347:161–167.[Abstract/Free Full Text]
  9. Omland T., Persson A., Ng L., O'Brien R., Karlsson T., Herlitz J., et al. N-terminal pro-B-type natriuretic peptide and long-term mortality in acute coronary syndromes. Circulation (2002) 106:2913–2918.[Abstract/Free Full Text]
  10. Hartmann F.S., Richardt G., Packer M., Coats A.J., Fowler M.B., Krum H., et al. Plasma N-terminal pro-BNP predicts the occurrence of major clinical events in severe chronic heart failure: results of a substudy of the COPERNICUS trial. Journal of the American College of Cardiology (2002) 39:200A.
  11. Troughton R.W., Frampton C.M., Yandle T.G., Espiner E.A., Nicholls M.G., Richards A.M. Treatment of heart failure guided by plasma amino-terminal brain natriuretic peptide (N-BNP) concentrations. Lancet (2000) 355:1126–1130.[CrossRef][Web of Science][Medline]
  12. Lerman A., Gibbons R.J., Rodeheffer R.J., Bailey K.R., McKinley L.J., Heublein D.M., et al. Circulating N-terminal atrail natriuretic peptide as a marker for symptomless left-ventricular dysfunction. Lancet (1993) 341:1105–1109.[CrossRef][Web of Science][Medline]
  13. Andersson B., Hall C. N-terminal proatrial natriuretic peptide and prognosis in patients with heart failure and preserved systolic function. Journal of Cardiac Failure (2000) 6:208–213.[CrossRef][Web of Science][Medline]
  14. Wijeysundera H.C., Hansen M.S., Stanton E., Cropp A.S., Hall C., Dhalla N.S., et al. Neurohormones and oxidative stress in nonischemic cardiomyopathy: relationship to survival and the effect of treatment with amlodipine. American Heart Journal (2003) 146:291–297.[CrossRef][Web of Science][Medline]
  15. Hall C., Rouleau J.L., Moye L., de Champlain J., Bichet D., Klein M., et al. N-terminal proatrial natriuretic factor: an independent predictor of long-term prognosis after myocardial infarction. Circulation (1994) 89:1934–1942.[Abstract/Free Full Text]
  16. Moe G.W., Rouleau J.L., Charbonneau L., Proulx G., Arnold J.MO., Hall C., et al. Neurohormonal activation in severe heart failure: relations to patient death and the effect of treatment with flosequinan. American Heart Journal (2000) 139:587–595.[Web of Science][Medline]
  17. Sia Y.T., Lapointe N., Parker T.G., Tsoporis J.N., Deschepper C.F., Calderone A., et al. Beneficial effects of long-term use of the antioxidant probucol in heart failure of the rat. Circulation (2002) 105:2549–2555.[Abstract/Free Full Text]
  18. Rouleau J.L., Pitt B., Dhalla N.S., Dhalls K.S., Swedberg K., Hansen M.S., et al. Prognostic importance of the oxidized product of catecholamines, adrenolutin, in patients with severe heart failure. American Heart Journal (2003) 145:926–932.[CrossRef][Web of Science][Medline]
  19. Hanley J.A., McNeil B.J. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology (1983) 148:839–843.[Abstract/Free Full Text]
  20. Jernberg T., Stridsberg M., Venge P., Lindahl B. N-terminal pro brain natriuretic peptide on admission for early risk stratification of patients with chest pain and no ST-segment elevation. Journal of the American College of Cardiology (2002) 40:437–445.[Abstract/Free Full Text]
  21. Omland T., de Lemos J.A., Morrow D.A., Antman E.M., Cannon C.P., Hall C., et al. Prognostic value of N-terminal pro-atrial and pro-brain natriuretic peptide in patients with acute coronary syndromes. American Journal of Cardiology (2002) 89:463–465.[CrossRef][Web of Science][Medline]
  22. Ishii J., Nomura M., Nakamura Y., Naruse H., Mori Y., Ishikawa T., et al. Risk stratification using a combination of cardiac troponin T and brain natriuretic peptide in patients hospitalized for worsening chronic heart failure. American Journal of Cardiology (2002) 89:691–695.[CrossRef][Web of Science][Medline]
  23. McDonagh T.A., Cunningham A.D., Morrison C.E., McMurray J.J.V., Ford I., Morton J.J., et al. Left ventricular dysfunction, natriuretic peptides, and mortality in an urban population. Heart (2001) 86:21–26.[Abstract/Free Full Text]
  24. Hammerer-Lercher A., Neubauer E., Muller S., Pachinger O., Puschendorf B., Mair J. Head-to-head comparison of N-terminal pro-brain natriuretic peptide, brain natriuretic peptide and N-terminal pro-atrial natriuretic peptide in diagnosing left ventricular dysfunction. Clinica Chimica Acta (2001) 310:193–197.[CrossRef][Web of Science][Medline]
  25. Hunt P.J., Richards A.M., Nicholls M.G., Yandle T.G., Doughty R.N., Espiner E.A. Immunoreactive amino-terminal pro-brain natriuretic peptide (NT-PROBNP): a new marker of cardiac impairment. Clinical Endocrinology (1997) 47:287–296.[CrossRef][Medline]
  26. Jessup M., Brozena S. Heart failure. New England Journal of Medicine (2003) 348:2007–2018.[Free Full Text]
  27. Gardner R.S., Ozalp F., Murday A.J., Robb S.D., McDonagh T.A. N-terminal pro-brain natriuretic peptide: a new gold standard in predicting mortality in patients with advanced heart failure. European Heart Journal (2003) 24:1735–1743.[Abstract/Free Full Text]
  28. Hysted M.E., Geiran O.R., Attramadal H., Spurkland A., Vege A., Simonsen S., et al. Regional cardiac expression and concentration of natriuretic peptides in patients with severe chronic heart failure. Acta Physiologica Scandinavica (2001) 171:395–403.[CrossRef][Web of Science][Medline]
  29. Eilers P.H., Marx B.D. Flexible smoothing with B-splines and penalties. Statistical Science (1996) 11:89–102.[CrossRef][Web of Science]
  30. Sauerbrei W. The use of resampling methods to simplify regression models in medical statistics. Applied Statistics (1999) 48:313–329.
  31. Benedict C.R., Shelton B., Johnstone D.E., Francis G., Greenberg B., Konstam M., et al. Prognostic significance of plasma norepinephrine in patients with asymptomatic left ventricular dysfunction. Circulation (1996) 94:690–697.[Abstract/Free Full Text]
  32. Cowie M.R., Wood D.A., Coats A.J., Thompson S.G., Suresh V., Poole-Wilson P.A., et al. Survival of patients with a new diagnosis of heart failure: a population based study. Heart (2000) 83:505–510.[Abstract/Free Full Text]
  33. Dries D.L., Exner D.V., Domanski M.J., Greenberg B., Stevenson L.W. The prognostic implications of renal insufficiency in asymptomatic and symptomatic patients with left ventricular systolic dysfunction. Journal of the American College of Cardiology (2000) 35:681–689.[Abstract/Free Full Text]
  34. Mahon N.G., Blackstone E.H., Francis G.S., Starling R.C. III, Young J.B., Lauer M.S. The prognostic value of estimated creatinine clearance alongside functional capacity in ambulatory patients with chronic congestive heart failure. Journal of the American College of Cardiology (2002) 40:1106–1113.[Abstract/Free Full Text]
  35. Lee D.S., Austin P.C., Rouleau J.L., Liu P.P., Naimark D., Tu J.V. Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. Journal of the American Medical Association (2003) 290:2581–2587.[Abstract/Free Full Text]
  36. Package insert, Nexus DxTM NT-proBNP Test Kit. (2003) Canadian Medical Device Licence #62767.
  37. Belsley D.A., Kuh E., Welsch R.E. Regression Diagnostics. (1980) New York: Wiley.

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