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European Journal of Heart Failure 2007 9(1):68-74; doi:10.1016/j.ejheart.2006.05.001
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© 2006 European Society of Cardiology

Unexplained week-to-week variation in BNP and NT-proBNP is low in chronic heart failure patients during steady state

Morten Schoua,*, Finn Gustafssonb, Per H. Nielsena, Lene H. Madsena, Andreas Kjaerc,d and Per R. Hildebrandta

a Department of Cardiology and Endocrinology, Clinic E, Frederiksberg University Hospital Ndr. Fasanvej 57'59, DK-2000-Frederiksberg, Denmark
b Department of Cardiology, The Heart Centre, Rigshospitalet University Hospital DK-2100-Copenhagen, Denmark
c Department of Clinical Physiology and Nuclear Medicine, The PET Centre Rigshospitalet University Hospital, DK-2100-Copenhagen, Denmark
d Cluster for Molecular Imaging, University of Copenhagen DK-2200 Copenhagen, Denmark

* Corresponding author. Tel.: +45 38 16 43 24; fax: +45 38 16 43 59. morten.schou{at}fh.hosp.dk


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
Background: The usefulness of brain-natriuretic-peptide (BNP) and N-terminal-pro-brain-natriuretic-peptide (NT-proBNP) for monitoring of chronic heart failure (CHF) patients has been questioned because of high levels of unexplained variation.

Aims: Week-to-week total variance (CVT), unexplained variation (CVI), reference change values (RCV), index of individualities (IOI) and number of samples (N) with week-to-week intervals needed to estimate the underlying homeostatic set point (15%) for BNP and NT-proBNP were calculated in pre-specified stable CHF patients.

Methods and results: We measured plasma concentrations of BNP and NT-proBNP, clinical and laboratory variables in 20 CHF patients with a 7-days interval. Only patients considered to be in steady state were included. The CVI was 15% (BNP) and 8% (NT-proBNP). CVT was 16% (BNP) and 8% (NT-proBNP) and RCV was 43% (BNP) and 23% (NT-proBNP). IOI was 0.14 for BNP and 0.03 for NT-proBNP and N was 1 for BNP and 1 for NT-proBNP.

Conclusions: Our data demonstrate that unexplained variation of BNP and NT-proBNP is low in CHF patients during steady state, which is a prerequisite for the use of these peptides for monitoring of the disease.

Key Words: BNP • NT-proBNP • Unexplained variation • Reference change value • Chronic heart failure

Received December 27, 2005; Revised March 7, 2006; Accepted May 2, 2006


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
Brain-natriuretic-peptide (BNP) and N-terminal-pro-brain-natriuretic-peptide (NT-proBNP) are prognostic markers in chronic heart failure patients (CHF) [1] and can be used to rule out heart failure in patients presenting with acute [2,3] or chronic dyspnoea [4,5]. However, the usefulness of BNP and NT-proBNP for monitoring disease progression has been questioned because of reported high intra-individual variance (CVI) (unexplained variation) and high reference change values (RCV) (critical difference) [6,7].

Total (CVT)-and intra-individual variances and reference change values of BNP and NT-proBNP should be calculated during steady state conditions [8]. If this is not done, variation in BNP and NT-proBNP may reflect physiological/pharmacological changes, e.g. a decrease in plasma concentrations following an increase in vasodilator therapy [9] or during up-titration of AII-blockers [10], and as such lead to false-high determinations of total variance. In some previous studies of temporal peptide variation in CHF, it is not entirely clear that steady state conditions were present [6,7]. Therefore, we defined a number of strict criteria to describe the steady state situation for a CHF patient, as follows. The patient should be considered euvolaemic by a physician, have stable heart failure symptoms and have stable cardiovascular and laboratory variables, no acute secondary stimuli for BNP/NT-proBNP secretion/metabolism/clearance [11-13] no acute changes in medication [10,14-17] and have no short term progression of heart failure (see inclusion and exclusion criteria, Table 1). Hence unexplained variation and derived measurements of variability can be calculated.


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  		Table 1 Inclusion and exclusion criteria (steady state model)

 
The index of individuality (IOI=(intra-individual variance+analytical variance)/inter-individual variance) [18-20] for BNP and NT-proBNP are unknown in CHF patients. A low IOI (<0.48) reflects strong individuality [19] indicating that an individual patient has his or her own level of BNP and NT-proBNP despite intra-individual variation. A biologically significant change (RCV) from this level will then indicate improvement or deterioration [20]. A high IOI (>1.4) indicates that CHF patients should be monitored according to population based reference intervals [19].

Finally, if intra-individual and analytical variance of a specimen (e.g. BNP or NT-proBNP) is known, the number of samples (N) to estimate the homeostatic set point (def.: the level a specimen varies around) can be calculated [21]. N is unknown for BNP and NT-proBNP in CHF patients, but its value is of interest if BNP and NT-proBNP evolve as commonly used surrogate endpoints like NYHA-class and left ventricular ejection fraction.

The aims of the present study were to calculate week-to-week unexplained variation (intra-individual variance) and derived statistical variables (CVT, RCV, IOI and N) for BNP and NT-proBNP in pre-specified stable (steady state) CHF patients.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
2.1. Protocol and patients
Twenty CHF patients were recruited from our heart failure clinic [22] during an 8-month period. The experimental protocol was approved by the Ethics Committee of Copenhagen (KF 01-272493) and informed consent was obtained according to the Helsinki Declaration.

During an 8-month period all patients (896 visits) were screened by the nurses in the heart failure clinic. All patients selected by the nurses underwent a physical examination with the investigator and a checklist was used for the inclusion and exclusion criteria. The inclusion and exclusion criteria are listed in Table 1. Six patients initially deemed eligible by the heart failure nurse were subsequently excluded by the physician investigator (1 due to hyperkalaemia, 1 due to urinary tract infection, 1 due to a rapid increase in plasma creatinine, 1 due to changes in diurnal rhythm, 1 due to malignant disease and 1 due to up-titration of spironolactone). All included patients had a blood sample drawn, and were scheduled for another consultation a week later at the same time of day, where a second blood sample was drawn. Patients were required to be in the same position (upright seated for at least 10 min) during blood sampling to minimise pre-analytical variation (time and posture) in BNP and NT-proBNP levels [21]. On both study days (Day 0 and Day 7) patients took the same heart failure medication in the morning to maintain steady state, and during the visits clinical data, weight (electronic) and blood pressure (oscillometric) and heart rate (palpatory) were noted.

Heparin-(NT-proBNP) and EDTA (BNP)-anticoagulated blood was collected by vene-puncture. Blood was centrifuged within 30 min after sampling at 3000 rpm for 10 min. NT-proBNP was analysed (double determination) on the same day within 2 h of sampling. Plasma samples for BNP were stored at –80 °C immediately after sampling. All samples for BNP were analysed (double determination) on 1 day at the end of the study. Plasma concentrations of BNP were analysed by ADVIA Centaur BNP-analysis (Bayer, Leverkusen, Germany) [23] and Elecsys 2010 NT-proBNP (Roche Diagnostics, Basel, Switzerland) [24].

Plasma concentrations of sodium, potassium, albumin (Integra 700, Diamond Diagnostics, Holliston, USA) and creatinine [25] (Heparin-anticoagulated blood) and haemoglobin and haematocrit (Sysmex XE 2100 TOA Medical Electronics, Kobe, Japan) (EDTA-anticoagulated blood) were also analysed on the same day at Day 0 and 7.

2.2. Statistics and calculation algorithms
Statistical variables were calculated according to Fraser and Harris [21] for each patient (n=20, double determination of each sample for each patient at Day 0 and Day 7)) and presented as median, mean and range. Percent-changes were calculated as (LevelDay7–LevelDay0)/LevelDay0*100%. CVT (=SD/mean,) was calculated as the week-to-week total-variation-coefficient. CVA (=SD/mean) was calculated as the mean of the intra-assay-variation-coefficients at Day 0 and Day 7. CVI was calculated as (CVT2–CVA2)1/2. IOI was calculated as (CVA2+CVI2)1/2/CVG (interindividual variance) by variance component models. Reference change values (RCV) were calculated as 21/2*Z*(CVA2+CVI2)1/2; Z is the z-statistic, which depends on the probability selected for statistical significance. N was calculated as (Z*CA+I/D); Z is the number of standard deviates required for the stated probability under the normal curve, and D is the desired percentage closeness to the homeostatic set point. Impression goals were calculated as 0.5*CVI and inaccuracy goals as 0.25*(CVI2+CVG2)1/2. Bartlett's test was used to test for variance homogeneity.

Week-to-week total-variation-coefficients (=SD/mean) were calculated for all cardiovascular variables and blood tests, and parametric (paired t-tests) and non-parametric (Wilcoxon signed rank test) (BNP and NT-proBNP) were used to evaluate values at Day 0 vs. Day 7. The Kolmogorov-Smirnov test and histograms were used to assess Gaussian distribution.

A P value<0.05 was considered significant. Analyses were made using Statistical Analysis Software (SAS 9.1, Cary, NC, USA).


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
3.1. Patients characteristics (n=20)
The characteristics of all 20 patients included in the study are presented in Table 2.


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  		Table 2 Patient characteristics

 
Changes in clinical and laboratory values Day 0 to Day 7 (Table 3). Week-to-week total variance (median) for all variables was between 1% and 6%, demonstrating that the patients were in steady state regarding their cardiovascular variables and volume status (Table 3). Week-to-week total variance of BNP and NT-proBNP were 16% and 8%, respectively. Individual plasma concentrations of BNP and NT-proBNP at Day 0 and Day 7 did not differ (P<0.34 for BNP and P<0.79 for NT-proBNP). Week-to-week total variation of BNP and NT-proBNP as functions of plasma concentrations are presented in Fig. 1, no linear relationships were observed (BNP: R=–0.12, P<0.62; NT-proBNP: R=–0.27, P<0.26). Percent-changes are presented in Tables 4 and 5. By multiple linear regression, variation in MAP, eGFR, PV, weight and HR could not explain variation in BNP (β=β-coefficient, CI=confidence interval) (βMAP: –1.341, 95%-CI: –3.4-0.4; βeGFR: –0.219, 95%-CI: –0.2-0.8; βPV: –1.490, 95%-CI: –5.4-2.4; βweight: 10.20, 95%-CI: –21-42; βHR: –0.038, 95%-CI: –1.6-1.5; adjusted R2: –0.127; P=0.72) and NT-proBNP (βMAP: –2,068, 95%-CI: –3.9-(–0.2); βeGFR: –0.253, 95%-CI: –2.2-1.7; βPV: –0.986, 95%-CI: –4.4-2.5; βweight: 14.07, 95%-CI: –14-42; βHR: 0.459, 95%-CI: –0.9-1.8; adjusted R2:0.095; P=0.28). By simple linear regression, variation in plasma volume could not predict variation in BNP (β: –1.304; 95%-CI: –4.5-1.8; adjusted R2: –0.013; P=0.40) and NT-proBNP (β: –1.383; 95%-CI: –4.8-1.7; adjusted R2: 0.006; P=0.36). Two patients had NT-proBNP levels <125 pg/ml5 and BNP levels <18 pg/ml4. Their systolic heart failure diagnosis was re-evaluated by repeated echocardiography (BNP/NT-proBNP levels were blinded for the sonographer). In both cases LVEF was found to be <0.45.


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  		Table 3 Cardiovascular variables, estimated GFR (eGFR), weight, plasma volume-changes (PV-changes), blood tests at Day 0 and Day 7

 


Figure 01
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  		Fig. 1 Relationship between plasma concentrations and week-to-week total variance (CVT) for NT-proBNP and BNP. (BNP: R=–0.12, P<0.62; NT-proBNP: R=–0.27, P<0.26).

 


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  		Table 4 Percent-changes, total (CV-T)-, analytical (CV-A)-intra-individual (= unexplained) (CV-I)- and between-subjects (CV-G)-variances

 


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  		Table 5 Influence of double determination of the same sample on statistical variables (median (mean) [range])

 
3.2. Statistical data
Data are presented in Tables 4 and 5 and Fig. 1. Week-to-week total variation of BNP (R=–0.12, P<0.62) and NT-proBNP (R=–0.27, P<0.26) were not correlated to plasma concentrations (Pearson Correlation) (Fig. 1). By Bartlett's test CVT of BNP and NT-proBNP showed variance in homogeneity (P<0.04 for BNP and P<0.03 for NT-proBNP).


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
The main finding of this study is that week-to-week unexplained variation (intra-individual variance) of BNP and NT-proBNP in pre-specified stable (steady state) CHF patients is 15% and 8%, respectively.

4.1. Week-to-week variances
The data demonstrate that week-to-week unexplained variation of BNP and NT-proBNP is low during steady state conditions in CHF patients. Previously, these values have been reported to be 40% and 35%, respectively, by Bruins et al. [6] (43 stable CHF patients and 1 week interval) and 50% and 33%, respectively, by Wu et al. [7] (12 apparently healthy subjects and 2 weeks interval). We observed a smaller range than Bruins et al. [6]. The explanations for this discrepancy may be that stability in our patients was very precisely defined implying that patients were in steady state, as well as differences in study design. The week-to-week total and intra-individual-variances calculated by Bruins et al. [6] were averages of 6 consecutive weeks. It may, therefore, be argued that clinically stable patients in the ambulatory setting vary more than our pre-specified stable patients. However, we think that unexplained variation should be defined as error in a biological system [26] and the total variance reported by Bruins et al. [6] and Wu et al. [7] should be denoted clinical variation rather than total variance, because it reflects the sum of analytical variance, intra-individual variance and relevant minor physiological/pharmacological changes. Whether the physician should react to these physiological changes is at present unknown.

Total variance of BNP and NT-proBNP is distributed in a skewed manner (variance in homogeneity) (see median and range, Table 4 and Fig. 1). For the physician it is important to be familiar with the distribution, because it explains why plasma concentrations of BNP and NT-proBNP may behave unpredictably (CVT>30% in 0-20% of the cases), even when the patients are treated correctly. However, because we only have 2 observations for each patient, the skewed distribution can reflect: 1) that all patients generally vary little, but on occasion substantially or, 2) that most patients vary little and a few vary substantially. Minute-to-minute plasma concentrations of BNP can be described by a nonlinear dynamic model in a repetitive pattern in CHF patients [27]. If week-to-week plasma concentrations of BNP and NT-proBNP also can be described in this way, the first theory might explain our results. However, we know from other biological systems that patients can vary either little or substantially and that variation carries prognostic information [28-30]. Therefore, based on knowledge from other biological systems the latter theory might explain our results. This is in accordance with the results by Bruins et al. [6] who showed that CHF patients with high plasma concentrations of BNP (>350 pg/ml) had decreased total variance of BNP, but this was not the case for NT-proBNP. From our results it cannot be concluded whether patients with high levels of BNP and NT-proBNP have decreased total variance of the peptides.

4.2. Index of individuality
We report IOI for the first time in CHF patients. IOI was 0.14 for BNP and 0.03 for NT-proBNP reflecting strong individuality of both peptides (Table 4) [19]. Wu et al. [7] reported IOI values of 1.8 for BNP and 0.9 for NT-proBNP, in healthy subjects. A high IOI (>1.4) indicates that population based reference intervals are useful [18] or that a repeat test will decrease the number of true and false positives [19]. The low IOI's (<0.48) [20] found in our study demonstrate that each patient varied little compared with the whole CHF population, suggesting that patients have their own BNP/NT-proBNP level despite intra-individual variation. Hence CHF patients may vary around a certain homeostatic set-point ("dry BNP/NT-proBNP") during steady state and a rapid (hours-days) increase (= critical difference) to a new BNP/NT-proBNP level ("wet BNP/NT-proBNP") may indicate decompensation, whereas a slow (weeks-years) increase may indicate progression of the CHF disease or comorbidity.

4.3. Reference change values (critical differences)
RCV (median) was 43% for BNP and 23% for NT-proBNP (Table 4). Bruins et al. [6] reported these values to be 113% and 98%, and Wu et al. [7] found 132% and 92%. RCV depends on analytical and intra-individual variance [21,31]. Primarily, lower intra-individual variance explains the lower RCV in our patients. Our data, therefore, suggest that BNP-changes greater than 43% and NT-proBNP-changes greater than 23% can be considered biologically significant. Theoretically, type 1 errors are avoided if the physician reacts to these changes, but the risk of a type 2 error still exists (power: 50%) [8]. Generally, to avoid type 2 errors it has therefore been suggested that 1.5*RCV (65% for BNP and 35% for NT-proBNP) should be considered biologically significant (power: 80%) [8]. Therefore, a reference change value can be regarded as a power function [8] and the Percent-change in BNP and NT-proBNP a physician should react on may rely on the outcome of ongoing clinical trials where different BNP/NT-proBNP-monitoring concepts are tested. Thus, based on our data, we hypothesise that a 43-65%-change in BNP and a 23-35%-change in NT-proBNP can be considered to be biologically significant.

4.4. Homeostatic set point
Plasma concentrations of BNP and NT-proBNP will vary even under steady state conditions. However, the number of samplings with week-to-week intervals to identify a patient's true levels (homeostatic set points) of BNP and NT-proBNP can be calculated according to the formula by Fraser and Harris [21] (see Methods). Our data demonstrate that a patient's true BNP level can be identified with one sample within ±15% with 75% confidence. A patient's true NT-proBNP level can be identified with one sample within ±15% with 95% confidence (Table 4). If double determination is performed the confidence increases to 85% for BNP (Table 5).

4.5. BNP and NT-proBNP analyses
From Table 5 it can be seen that double determination of the same sample of BNP and NT-proBNP only affects the values and ranges to a minor extent. This finding is explained by the low analytical variances of both peptides (Table 4). Consequently, based on our results, single determination of the same blood sample of BNP and NT-proBNP is sufficient in daily clinical routine. Furthermore, both Bayer's BNP-analysis (ADVIA Centaur) [23] and Roche's NT-proBNP-analysis (Elecsys 2010) [24] fulfil the analysis criteria for a new blood test-analysis [32]. This was also the case in our project (inaccuracy and impression goals are reached, Table 4), even though we observed low intra-individual variances, increasing the requirements to the analyses.

4.6. Limitations
NT-proBNP was analysed on different days and analytical variance for NT-proBNP is therefore confounded by between-run variance [21]. BNP samples were frozen at –80 °C and analysed on a single day. This study was consequently not designed to identify a difference between BNP and NT-proBNP concerning unexplained variation. Due to the strict inclusion criteria the number of patients included in the study was modest and we have only 2 observations for each patient. Consequently, the results should be interpreted with some caution. Sodium and fluid intake was not fixed in our patients. Therefore, sodium and fluid intake induced variation in plasma volume could be responsible for the unexplained variation in BNP and NT-proBNP [33]. However, neither variation in plasma volume nor variation in cardiovascular and renal variables could predict variation in BNP and NT-proBNP, making this explanation unlikely. Furthermore, it could be argued that a 7-day interval between the measurements of BNP and NT-proBNP might be too short, and that our data may be autocorrelated [34]. If variation of BNP and NT-proBNP are time-dependent longer intervals between measurements might result in increasing variation and higher reference change values. However, we chose to investigate this interval because a previous publication [6] suggested that problems with profound variation began within a week. Monthly-unexplained variation based on repeated measurements during steady state should be determined in future studies. Finally, this study was designed to calculate unexplained variation and different statistical variables for BNP and NT-proBNP during strictly defined steady state criteria for monitoring purposes. Consequently, our data do not identify variation of BNP and NT-proBNP in daily clinical practice (clinical variation).

4.7. Perspectives
Our results are relevant for physicians who plan to set up monitoring studies and the calculated reference change values should be tested in future studies. In addition, our calculated IOI's support that monitoring of CHF patients using individual BNP and NT-proBNP levels is indeed meaningful as used for instance in the BATTLESCARRED Study [35] and could be useful in the clinical setting depending of the outcome of the ongoing clinical trials. Using natriuretic peptides in this fashion would parallel the use of HgbA1C for monitoring of diabetic patients [36], where unexplained variation is also well described [30,37]. Finally, our steady state model may be useful in future studies dealing with unexplained variation of BNP and NT-proBNP in CHF patients.

4.8. Conclusions
Week-to-week unexplained variation (intra-individual variance) of BNP and NT-proBNP is 15% and 8%, respectively, in pre-specified stable CHF patients. Our data demonstrate that unexplained variation of BNP and NT-proBNP is low in CHF patients during steady state, which is a prerequisite for the use of these peptides in monitoring of the disease.


   Acknowledgement
 
Morten Schou is supported by research grant 200207135A-321 from the Copenhagen Hospital Corporation. The excellent technical assistance by Elsa Larsen, Panum Institute, Copenhagen University, and Vibeke Holm, Dept. of Clinical Chemistry, Frederiksberg University Hospital, is acknowledged. The excellent assistance in the heart failure clinic by the nurses Hanne Bartholdy, Anne Marie Jensen, Birgitte Carlsen and Louise Fly is also acknowledged. A special thank to Lene Theil Skovgaard, Dept. of Biostatistics, Panum Institute, Copenhagen University, for statistical assistance.


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

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