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European Journal of Heart Failure 2008 10(4):404-411; doi:10.1016/j.ejheart.2008.02.018
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© 2008 European Society of Cardiology

Prognostic value of sequential measurements of amino-terminal prohormone of B-type natriuretic peptide in ambulatory heart failure patients

Deddo Moertl*, Alexandra Hammer, Martin Huelsmann, Richard Pacher and Rudolf Berger

Department of Cardiology, Medical University of Vienna Waehringer Guertel 18-20, A-1090 Vienna, Austria

* Corresponding author. Tel.: +43 1 40400 4614; fax: +43 1 40400 4216. E-mail address: deddo.moertl{at}meduniwien.ac.at (D. Moertl).


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
Background: We evaluated the prognostic value of sequential NT-proBNP values in ambulatory heart failure patients after discharge, investigating whether the current value or the recent percent change is more important.

Methods and results: In 166 patients, NT-proBNP was measured at discharge from heart failure hospitalisation and three months later. The combined endpoint of death or heart failure rehospitalisation was evaluated after a maximum of 18 months or at follow-up closure. During a mean observation time of 14±4 months, 63 patients (38%) reached the endpoint. In multiple Cox analysis, NT-proBNP three months after discharge (NT-proBNP-3Mo) and NT-proBNP percent change (NT-proBNP-%change) were the only independent predictors of the endpoint among various clinical and laboratory variables. After definition of a high- (n = 83, 57% endpoints) and a low-NT-proBNP patient subgroup (n = 83, 19% endpoints) according to the median NT-proBNP-3Mo (1751 pg/ml), NT-proBNP-%change was the strongest predictor in the high-NT-proBNP subgroup. In the low-NT-proBNP subgroup, NT-proBNP-3Mo was the only independent predictor.

Conclusions: In ambulatory heart failure patients, the prognostic value of sequential NT-proBNP measurements depends on the magnitude of the current NT-proBNP value. Recent percent changes in NT-proBNP provide important prognostic information in patients with high NT-proBNP but not in patients with low NT-proBNP.

Key Words: Chronic heart failure • Prognosis • Natriuretic peptides

Received May 1, 2007; Revised December 18, 2007; Accepted February 28, 2008


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
For chronic heart failure, a widespread disease of increasing incidence [1] and poor prognosis [2], natriuretic peptides have been established as diagnostic markers [3] and as markers for the severity of heart failure [4]. Furthermore, several studies have shown that natriuretic peptides determined at a single time point are excellent prognostic markers for the prediction of adverse outcome in chronic heart failure [5].

However, severity of heart failure and the associated risk for adverse outcome may change over time. Therefore, patients may develop from low-risk patients to high-risk patients due to progression of disease. Similarly, high-risk patients may convert to low-risk patients due to effective therapy in the ambulatory setting. Accordingly, as an expression of changes in the severity of heart failure and prognosis, natriuretic peptides may rise or fall over time, as well.

Estimation of the severity of heart failure and the prognosis in an individual patient is commonly focused on measurement of the most current natriuretic peptide levels. This often generates sequential values of natriuretic peptides during the course of disease. Although there are a few data showing that changes in natriuretic peptides also reflect changes in prognosis in heart failure patients, there is a paucity of data on how to interpret sequential measurements of natriuretic peptides. In particular, the question of whether only the most recent value or also the change over time is of prognostic importance is not fully understood. For example, controversial data exist on repeated measurements during heart failure hospitalisations. While some authors have propagated natriuretic peptides at discharge as the most powerful prognostic parameter [6,7], others report that percent change during hospital stay is more important [8]. In ambulatory heart failure patients, some data on sequential measurements of natriuretic peptides exist [9,10]. However, whether percent change over time or the last available absolute value has more prognostic power still needs to be clarified in order to optimize the usage of repeated measurements of natriuretic peptides in clinical patient management.

Therefore, this study evaluates sequential values of amino-terminal prohormone of B-type natriuretic peptide (NT-proBNP) in ambulatory heart failure patients. We hypothesized that the percent change in NT-proBNP over three months adds independent prognostic information to the last available value of NT-proBNP. Furthermore, we hypothesized that the prognostic relation between percent change and the last available value of NT-proBNP depends on the magnitude of the most recent NT-proBNP level.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
2.1. Study design, inclusion and exclusion criteria
This prospective study was designed to evaluate sequential values of NT-proBNP in ambulatory heart failure patients after discharge. Recruitment period was between July 2003 and September 2004. All patients discharged from nine Viennese hospitals with a primary diagnosis of chronic heart failure were eligible. Inclusion criteria were hospitalisation due to decompensated heart failure and either a cardiothoracic quotient >0.5 or an ejection fraction ≤40% (echocardiographic, radionuclide ventriculography, or left ventricular angiography).

2.2. Protocol
After obtaining written informed consent, blood samples for analysis of NT-proBNP were taken and the patient was discharged as scheduled. After discharge, therapeutic optimization according to heart failure guidelines [11] was performed by a heart failure specialist. Three months after discharge, blood samples were taken again for analysis of NT-proBNP.

The study complied with the Declaration of Helsinki and the protocol was approved by the institutional ethics committee.

2.3. Outcome
The outcome variable was the combined endpoint of death or heart failure rehospitalisation.

2.4. Data collection
Baseline characteristics and blood samples at discharge and after three months were acquired by a study physician. Outcome data were acquired by an independent data collector via telephone contact with the patients and their caregivers and via the official central electronic registration data base of Austria (Zentrales Melderegister). The observation period started at the second blood sampling 3 months after discharge. The maximum follow-up time for each patient was 18 months; end of follow-up was July 2005.

2.5. Measurement of natriuretic peptides
All blood samples were collected into glass tubes containing EDTA as anticoagulant and centrifuged within 1 h. The resulting plasma was frozen in plastic tubes at –80 °C until analyzed. For analysis, plasma was defrosted and natriuretic peptide levels were determined in a blinded fashion. NT-proBNP was determined with a Roche Diagnostics radioimmunoassay on an Elecsys 2010 analyser.

2.6. Statistical analysis
Categorical data are presented as numbers (percent) and continuous variables as means±standard deviation. Comparisons between groups were performed using Student's t-test for unpaired data. Changes in continuous parameters between discharge and three months later were tested for statistical significance using the Student’s test for paired data. In order to assess and compare the prognostic values of different parameters Cox proportional hazard regression analyses using different models were performed. At first, univariate analysis was performed testing the following parameters: NT-proBNP at baseline; various baseline characteristics (age, sex, the presence of diabetes mellitus, coronary artery disease, atrial fibrillation, ICD, and the duration of heart failure history); systolic blood pressure, heart rate, plasma sodium concentration, glomerular filtration rate, body mass index, and the presence of edema at baseline and at three months, respectively; New York Heart Association functional class, paroxysmal nocturnal dyspnoea, and orthopnoea at 3 months. Then, only significant univariate predictors of the endpoint were entered in a multiple Cox regression model (Cox model 1). In addition to Cox-model 1, Cox-model 2 contained NT-proBNP at three months. In addition to Cox-model 2, Cox-model 3 contained percent change in NT-proBNP from baseline to three months. The models were built stepwise, and the p-value for entering and staying in the model was set at 0.05. To compare the event-free survival between patient groups, Kaplan-Meier analysis was performed using the log-rank test for statistical differences. To describe the relative prognostic value of sequential NT-proBNP in addition to conventional variables, partial proportion of explained variation was calculated as previously described [12]. As a cut-off value for dichotomization of NT-proBNP the median NT-proBNP at three months was defined. Since natriuretic peptide levels were not normally distributed they were loge transformed for analyses. The resultant distributions of the loge transformed values were tested for normality using the Shapiro-Wilks test yielding a W-value of 0.992 for NT-proBNP at discharge and a 0.986 for NT-proBNP at three months. GFR was calculated using the Cockroft-Gault formula. A value of p<0.05 was considered statistically significant. Analyses were performed using SAS Version 9.1.


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
3.1. Patient characteristics and outcome
A total of 175 patients were recruited for the study. Of these, nine patients died before the second blood test at 3 months, therefore a total of 166 patients were included in the analysis. No patient was lost to follow-up. Patient characteristics at baseline and three months after discharge are presented in Table 1.


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  		Table 1 Baseline demographics, clinical characteristics, and medication

 
Within the first three months, beta-blocker and angiotensin converting enzyme inhibitor (ACE-I) / angiotensin receptor blocker (ARB) doses were increased by 19±35% (p<0.0001) and 26±48% (p<0.0001) of target dose, respectively [13]. The proportion of patients with an increase in either ACE-I/ARB or beta blocker dosage within the first three months was 69% (114 of 166). In these patients NT-proBNP decreased from 4134±5025 pg/ml to 3109±3909 pg/ml (p<0.0001), whereas no significant change in NT-proBNP (discharge: 4087±6312 pg/ml, 3 months: 3532±2949 pg/ml, p=0.05) could be noted in all other patients.

Mean observation time was 14±4 months, and ranged from 4 to 18 months. In this period, 63 (38%) patients reached the combined endpoint: 50 patients had a hospitalisation for heart failure worsening and for 13 patients death was the first event. The total number of deaths was 29 (17%).

3.2. Prognostic value of sequential NT-proBNP measurements
Significant univariate predictors of death or heart failure hospitalisation (Table 2) were NT-proBNP at three months ({chi}2=41.5, p<0.0001), percent change of NT-proBNP ({chi}2=30.5, p<0.0001), NT-proBNP at discharge ({chi}2=11.7, p<0.001), GFR at three months ({chi}2=9.4, p<0.01), NYHA class at three months ({chi}2=8.7, p<0.01), age ({chi}2=7.6, p<0.01), GFR at discharge ({chi}2=7.6, p<0.01), the presence of orthopnoea at three months ({chi}2=6.8, p<0.01), serum sodium level at 3 months ({chi}2=5.5, p<0.05) , and paroxysmal nocturnal dyspnoea at three months ({chi}2=4.2, p<0.01). Using multiple Cox regression analysis, model 1 (NT-proBNP at 3 months and percent change of NT-proBNP excluded) revealed that NT-proBNP at discharge ({chi}2=11.5, p<0.001) and NYHA class ({chi}2=5.5, p<0.05) at three months were independent predictors of the combined endpoint. When NT-proBNP at three months was also entered into the model (model 2) it became the only independent predictor ({chi}2=41.5, p<0.0001).


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  		Table 2 Univariate predictors of mortality and heart failure re-hospitalisation in 166 patients 3 months after discharge from heart failure hospitalisation

 
The results of model 2 showing that discharge NT-proBNP loses its prognostic importance when NT-proBNP at three months is added to the model, are confirmed by Kaplan-Meier analysis with 4 patient subgroups according to NT-proBNP values at discharge and three months later using the respective median values as cut-off points (discharge: 2514 pg/ml, 3 months: 1751 pg/ml, Fig. 1): Patients with supra-median NT-proBNP at discharge and three months later (high-high, event rate: 56% [36 of 64]), patients with infra-median NT-proBNP at both time points (low-low, event rate: 19% [12 of 64]), patients with supra-median at discharge and infra-median NT-proBNP three months later (high-low, event rate: 21% [4 of 19]), and patients with infra-median at discharge and supra-median NT-proBNP three months later (low-high, event rate: 58% [11 of 19]). There were significant differences in outcome between the low-high and the low-low subgroup (p=0.0018) and the high-low vs. high-high subgroup (p=0.0128). However, no difference in outcome was found between the high-high and low-high subgroup (p=0.9759), and between the low-low and high-low subgroup (p= 0.8813). This indicates that both in patients with high and in patients with low NT-proBNP at three months, discharge NT-proBNP did not provide significant additional prognostic information.


Figure 01
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  		Fig. 1 Kaplan-Meier curves for death or heart failure hospitalisation of patients subgrouped according to the median values of NT-proBNP at discharge (median=2514 pg/ml) and at three months after discharge (median=1751 pg/ml): high-high: supra-median NT-proBNP at both time points, low-low: infra-median NT-proBNP at both time points, high-low: supra-median NT-proBNP at discharge and infra-median NT-proBNP three months later, low-high: infra-median NT-proBNP at discharge and supra-median NT-proBNP three months later.

 
To investigate if relative changes of NT-proBNP are also important predictors of events, percent change of NT-proBNP since discharge was introduced into the Cox model (model 3, Table 3). Again, absolute NT-proBNP at 3 months was the strongest predictor of events but percent change was also an independent predictor.


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  		Table 3 Multiple Cox regression analysis to predict mortality and heart failure re-hospitalisation in 166 patients 3 months after discharge from heart failure hospitalisation

 
3.3. Prognostic value of sequential measurements of NT-proBNP in relation to the magnitude of NT-proBNP
To further analyse if the prognostic importance of absolute values and relative changes of NT-proBNP depend on the magnitude of NT-proBNP level, we divided the patient population into a low- (n=83, 19% endpoints) and a high-NT-proBNP group (n=83, 57% endpoints) according to the cut-off value of 1751 pg/ml NT-proBNP at three months. In the subgroup of patients with low NT-proBNP the only univariate and therefore independent predictor was NT-proBNP at three months ({chi}2=5.2, p<0.05). In patients with high NT-proBNP, percent change of NT-proBNP ({chi}2=25.3, p<0.0001) and NT-proBNP at three months were univariate predictors ({chi}2=19.2, p<0.0001) and both remained independent predictors in the multiple Cox regression analysis (percent change of NT-proBNP: {chi}2=25.9, p<0.0001, NT-proBNP at three months: {chi}2=6.6, p<0.01).

This finding is further confirmed by Kaplan-Meier analysis (Fig. 2): In the high-NT-proBNP group patients with an increase in NT-proBNP (event rate 73%, 29 of 40) had a significantly worse prognosis than patients with a decrease (event rate 42%, 18 of 43, p=0.0062). In contrast, in the low-NT-proBNP group, percent change of NT-proBNP had no additional prognostic value (increase of NT-proBNP: event rate=24%, 4 of 17, (decrease of NT-proBNP: event rate=18%, 12 of 66, p=0.7079).


Figure 02
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  		Fig. 2 Kaplan-Meier curves for death or heart failure hospitalisation of patients subgrouped according to the median value of NT-proBNP three months after discharge (supra-median: ≥1751 pg/ml, infra-median: <1751 pg/ml) and according to a rise or a fall of NT-proBNP within three months after discharge (increased: rise in NT-proBNP, decreased: fall in NT-proBNP). n.s.=not significant.

 
3.4. Additive prognostic importance of NT-proBNP
In the total patient population, proportions of explained variation to predict the endpoint were 1.9% for percent change and 7.7% for NT-proBNP at three months, respectively, in addition to 23.1% of all background variables as listed in Table 2. In the high-risk group, percent change added 3.9% to the proportion of explained variation of 30.6% by the background variables. In the low-risk group, NT-proBNP at three months added 14.4% to the proportion of explained variation of 31.8% by the background variables.


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
To the best of our knowledge, this is the first study to investigate whether the latest available value or the previous percent change of natriuretic peptides is the better prognostic marker in ambulatory heart failure patients. The main finding of this study is that the optimal mode of interpretation of repeated NT-proBNP measurements (usage of current NT-proBNP alone versus previous percent change) depends on the magnitude of the most recent NT-proBNP level: In patients with low NT-proBNP three months after discharge the relative change since discharge has no additional prognostic power. In contrast, in patients with high NT-proBNP the relative change since discharge is the most important predictor of adverse outcome. Therefore, the prognostic value of high NT-proBNP levels three months after discharge can be increased through combination with its percent change since discharge, whereas the prognostic value of a low NT-proBNP cannot be improved by taking previous changes into account.

Since disease severity and the associated risk can change over time, recent measurements of natriuretic peptides predict adverse outcomes more accurately than previous measurements. This has been reported previously both in the hospital [6-8,14-16] as well as in the ambulatory setting [17-19]. Our data confirm these findings, showing that NT-proBNP three months after discharge is a better prognostic marker than NT-proBNP at discharge. Extrapolation of these findings suggests that future NT-proBNP measurements, for example another three months later, might predict future events even more accurately. Therefore, patterns in natriuretic peptides that most likely reflect future natriuretic peptide levels might have the highest prognostic accuracy. These considerations might help to explain why we found that the percent change was a better prognostic marker than the recent absolute value in patients with high NT-proBNP but not in patients with low NT-proBNP. In patients with a currently high NT-proBNP, recent percent changes might reflect a trend that will continue in the near future, i.e. recent increases might predict future increases and recent decreases might predict future decreases, therefore predicting future NT-proBNP and associated risk. In contrast, in patients with low NT-proBNP, recent percentage changes might have less power to predict future NT-proBNP values since there is a high chance that these values will be low in any case. If NT-proBNP was already low three months before, this reflects stable low risk; if NT-proBNP values were high before and have decreased, this reflects improvement in disease state and risk during the previous three months.

4.1. Course of natriuretic peptides in hospitalised patients
These considerations are also in agreement with studies investigating sequential natriuretic peptides in patients hospitalised for decompensated heart failure. Most of these studies clearly demonstrate that percent change of natriuretic peptides during recompensating therapy in hospital is a stronger prognostic marker than measurements at discharge. Therefore, changes in natriuretic peptides reflect the response to recompensating therapy, which is obviously an important prognostic factor [6,8,14].

4.2. Course of natriuretic peptides in ambulatory heart failure patients
In our study, the recompensated, "dry" state at discharge after heart failure hospitalisation is the baseline situation for evaluation of repeat measurements of natriuretic peptides in the ambulatory setting. In these ambulatory "dry" patients, changes in natriuretic peptides reflect different pathophysiological processes than in acutely decompensated patients, namely progression/regression of disease instead of acute decompensation/recompensation. Nevertheless, as regards the improved prognostic value of natriuretic peptides after treatment, the hospitalised, recompensated patient at discharge is probably similar to the ambulatory patient after treatment optimization.

Maeda et al. reported that BNP three months after, but not before, treatment optimization was an independent predictor of mortality in chronic heart failure [18]. This is due to the fact that the full potential benefit and thereby prognostic impact of chronic heart failure treatment is apparent only after treatment optimization [20,21]. Accordingly, in our study a higher uptitration of medication resulted in a significant reduction in NT-proBNP. However, not all patients respond to heart failure therapy, and this non-response is associated with worse prognosis and high natriuretic peptides and explains the importance of sequential NT-proBNP measurements in ambulatory patients.

Various analyses in ambulatory patients have reported that changes in natriuretic peptides more accurately correlate with prognosis than baseline values. Retrospective analyses from the Valsartan in Heart Failure Trial (Val-HeFT) showed that changes in BNP within four months were associated with corresponding changes in morbidity and mortality [9,17] and that change in BNP over four months was a stronger prognostic marker than baseline BNP [17]. Bettencourt et al. also found that a change in NT-proBNP over 12 months was a stronger predictor of mortality than the baseline value. Unfortunately, none of these publications compared the prognostic importance of changes in natriuretic peptide values versus follow-up values. However, we believe that such a comparison is of high clinical relevance. In patient management, natriuretic peptide values are repeatedly determined because it has been demonstrated that the more recent the measurement, the higher its prognostic value. Therefore, we focussed on the question of whether the values determined in the past should be also taken into account. We found that in patients with higher NT-proBNP (reflecting higher risk) percent change is the strongest prognostic marker, whereas it does not add prognostic information to the recent values in patients with lower NT-proBNP (reflecting lower risk). This finding might assist in the decision process of activating or postponing advanced treatment strategies.

4.3. Limitations
The prognostic significance of sequential NT-proBNP measurements is probably time-dependent, i.e. it may change with the duration of time between the two measurements. The time interval of three months for sequential NT-proBNP measurements is arbitrary and it is not known whether shorter or longer time intervals would influence the prognostic value. It is expected that therapeutic optimization will have been achieved and treatment success or failure recognised, three months after discharge, which makes this a good time point for re-evaluation, as previously shown [17,18]. Longer time intervals might delay recognition of treatment failure and thereby also delay appropriate measures to rescue the patient (for example evaluation for transplantation). With shorter time intervals, beta-blocker therapy which transiently increases natriuretic peptides 6 weeks after initiation [22], might impair the prognostic accuracy of repetitive measurements of natriuretic peptides at significantly shorter time intervals than three months.

Our study was not designed to define therapeutic goals or to describe effects of risk assessment on patient outcome. Therefore, further studies are required to evaluate how assessing/monitoring NT-proBNP changes over time can improve patient outcomes.

4.4. Conclusion
In ambulatory heart failure patients, the prognostic value of sequential measurements of NT-proBNP depends on the magnitude of the current NT-proBNP value. In patients with high NT-proBNP, recent percent changes add significant prognostic information. In contrast, in patients with low NT-proBNP, past NT-proBNP values and past changes do not add significant additional prognostic information. However, further studies are required to evaluate whether assessing/monitoring NT-proBNP changes over time can improve patient outcomes.


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

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The prognostic value of repeated measurement of N-terminal pro-B-type natriuretic peptide in patients with chronic heart failure due to left ventricular systolic dysfunction
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