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European Journal of Heart Failure 2008 10(10):1033-1039; doi:10.1016/j.ejheart.2008.07.015
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© 2008 European Society of Cardiology

Quality-adjusted life year weights among elderly patients with heart failure

Urban Alehagena,*, Mikael Rahmqvistb, Thomas Paulssonc and Lars-Åke Levinb

a Department of Cardiology, Heart Centre, University Hospital of Linköping SE-581 85 Linköping, Sweden
b Center for Medical Technology Assessment, University of Linköping SE-581 83 Linköping, Sweden
c Department of Health Economics AstraZeneca Sverige AB, SE-151 85 Södertölje, Sweden

* Corresponding author. Tel.: +46 13 22 20 00. E-mail address: Urban.Alehagen{at}IHS.liu.se (U. Alehagen).


   Abstract
Top
 Abstract
1. Background
 2. Methods
 3. Results
 4. Discussion
 References
 
Background: When assessing health-related quality of life (HRQoL) in elderly patients with heart failure (HF), the process of obtaining quality-adjusted life year (QALY) weights is generally complicated and time-consuming.

Aim: To evaluate whether information regarding HRQoL and QALY weights can be derived directly from the established and widely used New York Heart Association (NYHA) functional classification system.

Methods: NYHA functional status was assessed independently both by the individual patients and by the examining cardiologist in 323 elderly patients with symptoms of HF recruited from primary care. HRQoL was evaluated using the SF-36 questionnaire and a time trade-off (TTO) scenario. The TTO technique generates direct QALY weights.

Results: Both the TTO technique and SF-36 values demonstrated a statistically significant correlation with NYHA functional status. The TTO values also correlated with all SF-36 dimensions. Increasing impairment was associated with statistically significant drops in both SF-36 values and TTO-based QALY weights. For patients in NYHA classes I–IV the QALY weights were 0.77, 0.68, 0.61, and 0.50, respectively. Thus in elderly patients, symptoms of HF have a major impact on perceived quality of life.

Conclusion: The results of the present study show that QALY weights, an important instrument in the health economic evaluation of treatment strategies, can be derived directly from NYHA classification in elderly HF patients.

Key Words: Heart failure • Elderly patients • Health related quality of life • QALY

Received January 16, 2008; Revised May 22, 2008; Accepted July 24, 2008


   1. Background
Top
 Abstract
 1. Background
2. Methods
 3. Results
 4. Discussion
 References
 
The incidence and prevalence of heart failure (HF) are increasing in Western populations, and the consequences of this condition are considerable for both the individual and society [1,2]. Studies have shown that HF affects quality of life (QoL) more profoundly than many other chronic diseases [3]. For society, the direct costs of HF constitute 1-2% of total health care expenditure [2,4,5].

The rapid development of new therapies for HF patients raises questions about the value of these treatments. For example, they may increase patients' health-related quality of life (HRQoL), but at a substantial cost and without a corresponding prolongation of life. To facilitate value judgments when comparing improvements in quality and quantity of life, these two attributes should ideally be combined in a single measure. The most widely used and accepted method of doing this is the quality-adjusted life year (QALY) approach. The value of one QALY is the value of spending one year in full health. In the QALY method, a HRQoL value, also called a utility weight, is assigned to each health state in each time period of life. The utility weights are distributed on a scale between 1, which corresponds to full health, and 0, representing death. Multiplying the utility weight by the length of time gives the health outcome expressed in QALYs [6].

QALY weights can be obtained in three principal ways. The first uses direct methods, such as time trade-off (TTO) or standard gamble (SG) questions [7], or a visual analogue scale (VAS) [8]. The second uses indirect methods, e.g. the EuroQol-5D (EQ-5D) questionnaire or the McMaster Health Utility Index (HUI), in which predefined states are given predefined utility weights [9,10]. The third method derives QALY weights from disease-specific descriptions/classifications or QoL instruments. Disease-specific QALY weights can be estimated by using transformation equations that transform QoL instrument values into QALY weights, or by associating predefined QALY weights with each of the different health states.

The New York Heart Association (NYHA) functional classification of HF is the most widespread and extensively used classification system relating HF symptoms to everyday activities. The NYHA classification consists of four categories based on functional status that range from no symptoms (class I) to severe at rest (class IV). The examining physician generally carries out the classification assessment. The NYHA functional classification has been utilised as the basis for QALY weight evaluations in some previous economic analyses [11-15]. These valuations have, however, been arbitrary estimates based on expert opinions, with no basis in empirical measures of patient valuations. Other studies have compared the relationship between the NYHA functional classification and QoL instruments, both high and more modest correlations have been found [16-19]. Lewis et al. [20] reported that HF patients were able to express preferences regarding improved health versus length of life as evaluated by TTO and SG values. Kirsch et al. [21] demonstrated the existence of a consistent relationship between the disease classifications and the QALY instrument by allowing members of the general public to assess their own NYHA classes and by using a TTO instrument associated with the EQ-5D health state valuation method. However, in patients with severe disease, the expected utility theory condition of constant proportionality could not be found. So far, no study has been published with an estimation of QALY weights based on self-assessments performed by HF patients.

The objective of this study was therefore to estimate QALY weights based on NYHA functional class as assessed both by the patients themselves and by a cardiologist, in an elderly population with symptoms of HF.


   2. Methods
Top
 Abstract
 1. Background
 2. Methods
3. Results
 4. Discussion
 References
 
2.1. Evaluation of NYHA class
Functional status was evaluated in all patients, based on their history. The patients were asked how far they could walk at normal pace before they needed to stop due to dyspnoea or tiredness. The walking distance was assessed in relation to some well-known places in the community, or from the patient's home.

This information was used to define the patients NYHA functional status; class I: no limitation, class II: minor limitation on ordinary physical activity; class III: marked limitation, have to stop after 200 m and class IV: symptoms at rest.

2.2. Patients
Patients with symptoms associated with HF who attended primary care clinics in a rural municipality in the southeast of Sweden were eligible to participate in the study. The design of the study has been described in detail in a previous report [22]. In summary, all patients with symptoms of dyspnoea, and/or peripheral oedema, and/or tiredness, who contacted primary care during 1995-1996, and in whom HF could not be ruled out as reason for the symptoms, were invited to participate in the study, which took place in 1996. Of the total population of 10, 300 in the municipality, 548 people were invited to participate in the study. Of these, 510 accepted and were examined by a cardiologist (UA). Of those examined, 323 agreed to complete a questionnaire concerning their HRQoL. These 323 patients constitute the study population in the present analysis.

The examining cardiologist recorded the history of each patient, performed a clinical examination, and categorised the patient's functional status according to the NYHA functional classification system. NYHA functional class III was sub-divided into IIIa (able to walk more than 200 m) and IIIb (not able to walk more than 200 m), as has been used in other clinical studies [23].

All patients also assessed their own functional status by themselves according to the same system (self-assessed NYHA; s-NYHA). The examining cardiologist was blinded to this information. In addition, all patients evaluated their QoL and answered a TTO question concerning their perceived state of health, without assistance from the cardiologist or nurse.

The order of the assessments, which was not randomised, was as follows; s-NYHA, SF-36 and lastly the TTO evaluation. All patients were given a copy of the questions and some short instructions on how to answer them, they were instructed to answer all questions at home on their own.

The HRQoL instrument used was the Medical Outcome Survey Short Form 36 (SF-36), one of the most widely used generic instruments [24]. SF-36 evaluates the following dimensions: Physical function (PF), Role physical (RP), Body pain (BP), General health (GH), Vitality (VT), Social function (SF), Role emotional (RE), and Mental health (MH).

The TTO question used was: "Imagine that you will live for another ten years in your present state of health. If you had the choice of living for a shorter time in full health, how many years of full health would correspond to the value of ten years in your present state of health?"

The investigation conforms to the principles outlined in the Declaration of Helsinki, and all participants gave written informed consent to participate in the study. The Ethics Committee of the University Hospital in Linköping approved the study protocol.

2.3. Doppler echocardiography
Doppler echocardiography to evaluate cardiac function was offered to all patients, of whom 312 patients agreed both to answer the HRQoL questionnaire and to undergo Doppler echocardiography Doppler echocardiographic examinations (Accuson XP-128c) to evaluate systolic and diastolic function, using both M-mode and 2D methodology, were performed with the patient in the left supine position. Systolic function, expressed as ejection fraction (EF), was determined semi-quantitatively [25-27] and patients were categorised into four classes as follows: EF<30%, EF 30-40%, EF 40-50% and EF>50% Normal systolic function was defined as EF>50%. Severely impaired systolic function was defined as EF<30%.

2.4. BNP analysis
To validate the patient's evaluation of s-NYHA functional status against more objective criteria of impaired cardiac function, we analysed the plasma concentration of B-type natriuretic peptide (BNP) as a measure of mainly left ventricular wall tension. All patients were fasting, seated, and had 30 min of rest before blood samples were taken. The samples were collected in pre-chilled plastic tubes containing EDTA (Terumo EDTA K-3), placed on ice, and centrifuged at 3000 g for 10 min at +4 °C. Plasma was then immediately frozen and stored at –70 °C until analysis.

BNP was measured using a non-extraction immunoradiometric technique (Shionogi, Osaka, Japan). The normal reference range in middle-aged adults as stated by the manufacturer is 0-5.3 pmol/L (0-18 ng/L). The detection limit at the laboratory was 1.2 pmol/L (zero+2 SD). The total inter-assay coefficient of variation was 9.3% (mean 12.4 pmol/L, n=10), 5.4% (mean 45.2 pmol/L, n=10). The intra-assay coefficient of variation was 3.3% (mean 17.4 pmol/L, n=7), 2.2% (mean 108.1 pmol/L, n=7).

2.5. Statistical methods
Descriptive data are presented as percentages, median, mean and standard deviation (SD). The Chi-square test was used for discrete variables, and Student's unpaired two-sided t-test was used for continuous variables. In all tests a p value less than 0.05 were considered statistically significant.

The plasma concentration of BNP was divided into quartiles. Each quartile was analysed against each s-NYHA functional class and chosen TTO value.

All data were analysed using generally available statistical analysis software packages (Statistica v 7.1, Statsoft Inc., Tulsa, OK, USA, and SPSS v 11, Chicago, IL, USA).


   3. Results
Top
 Abstract
 1. Background
 2. Methods
 3. Results
4. Discussion
 References
 
3.1. Patients
The population consisted of 323 elderly patients with symptoms associated with HF, who completed a questionnaire and underwent Doppler echocardiography (n=312), a clinical examination and blood sampling (315 patients completed the HrQoL instrument and provided blood samples). The baseline characteristics of the study population are described in Table 1. The non-respondents to the questionnaire (n=187) were also analysed. The non-respondents were older than the respondents, and larger proportion of them had diabetes. On the other hand, the respondents consumed significantly more cardiovascular related medication. Using mean+2 SD as a cut-off value for plasma concentration of BNP, to represent a pathologically increased plasma concentration, there was no difference between the respondents and the non-respondents. We therefore do not believe that the non-respondents represent a more diseased group, and hence that the respondents are representative of elderly patients with symptoms of heart failure.


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  		Table 1 Baseline characteristics of patients in the study population who completed or did not complete a quality of life inventory (n=510)

 
3.2. NYHA functional classification system
A comparison of the patient's s-NYHA classification and the cardiologist's NYHA classification is shown in Table 2.The cardiologist did not categorise any of the patients into NYHA functional class IV. However, eight of the patients evaluated themselves as belonging to class IV in their self-assessments (of these the cardiologist classified 6 as NYHA class III and 2 as NYHA class II). An analysis comparing the cardiologist's classification (NYHA class) and the patient's own classification of NYHA functional class (s-NYHA class) suggests that in patients with less functional impairment the two classifications corresponded well (Table 2). However, for patients with more severe disease, the cardiologist's classification corresponded less well with the patient's self-assessment.


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  		Table 2 Comparison between cardiologist's and patient's own classification according to NYHA functional class

 
From Figs. 1 and 2 it is clear that the perceived health of the patients, illustrated in the different dimensions of the SF-36, is more affected as the disease progresses, and is better evaluated by using the patient's own classification than using the cardiologist's. This can be seen in the RP and the PF dimensions where the differences between the different NYHA classes are more obvious in the s-NYHA compared to the NYHA classification.


Figure 01
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  		Fig. 1 Distribution of dimensions in the SF-36 according to cardiologist assessed NYHA functional classes (NYHA). Note: PF: Physical function, RP: Role physical, BP: Body pain; GH: General. Health; VT: Vitality, SF: Social function, RE: Role emotional, MH mental health.

 


Figure 02
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  		Fig. 2 Distribution of dimensions in SF-36 according to patient self-assessed NYHA functional classes (s-NYHA). Note: PF: Physical function, RP: Role physical, BP: Body pain; GH: General. Health; VT: Vitality, SF: Social function, RE: Role emotional, MH mental health.

 
The distribution of s-NYHA classes according to BNP quartiles shows that the patients who classified themselves as the functionally most impaired also had the highest plasma concentrations of BNP (Table 3). The distribution of NYHA functional classes in the patients with normal systolic and diastolic function on Doppler echocardiography (NYHA class I: 129/237 (54%), class II: 91/237 (38%), class III: 17/237 (7%) compared to the distribution in patients with an EF<40% (NYHA class I: 5/30 (17%), class II: 10/30 (33%), class III: 15/30 (50%) showed statistically significant differences.


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  		Table 3 Distribution of self-assessed NYHA functional classes (s-NYHA) within the four quartiles of plasma concentrations of BNP in the study population

 
3.3. SF-36 dimensions and NYHA functional class
The eight different scales of the SF-36 instrument were analysed across the different NYHA functional classes. The impact on the patients of the different dimensions analysed was greater for patients with more functionally impairment. The reductions in the scores of the SF-36 dimensions were considerable in NYHA classes II and III. There were statistically significant differences (p<0.01) between NYHA functional classes I and II for all dimensions except for the MH dimension. The differences between NYHA functional classes I and III were greater, and all differences obtained across the dimensions, including MH, were statistically significant (p<0.001). The influence of symptoms of HF was even more pronounced in the s-NYHA functional classes (Fig. 2). There was a homogenous trend towards greater impairment of the SF-36 dimensions evaluating physical states with decreasing NYHA functional class.

3.4. TTO weights and NYHA functional class
The relationship between mean TTO weights and NYHA functional class was analysed, with NYHA class I being used as reference. The analyses showed that patients reported lower TTO weights as NYHA functional class decreased. There was a statistically significant decrease in TTO weights in patients in NYHA functional classes II and III compared with those in NYHA functional class I (Table 4). The TTO weights in NYHA functional class III were an average of 0.15 units lower than those in NYHA class II. The trend was even more pronounced in the s-NYHA classification. Due to the small number of patients in s-NYHA functional class IV, we combined NYHA functional classes IIIb and IV. The self-assessed classification revealed a wider range of average TTO weights, with a range of 0.27 (mean TTO from 0.50 to 0.77) compared with the cardiologist's NYHA classification, in which the range was 0.19 (mean TTO from 0.56 to 0.75) (Table 4). The lowest average utility weight of 0.5 was found among patients who assessed themselves as belonging to s-NYHA class IIIb or IV.


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  		Table 4 Comparison of mean time trade-off (TTO) values across NYHA functional classes and self-assessed NYHA functional classes (s-NYHA), where functional class I serves as reference group

 
An analysis of the relationship between the different SF-36 dimensions and the TTO weights demonstrated statistically significant correlations between the different dimensions and the TTO weights. The strongest correlations were found between the General Health and Vitality dimensions and the TTO weights (Table 5).


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  		Table 5 Pearson correlation coefficients between the different SF-36 dimensions and the time trade-off (TTO) values

 

   4. Discussion
Top
 Abstract
 1. Background
 2. Methods
 3. Results
 4. Discussion
References
 
Heart failure is a serious condition with profound effects, resulting in negative influences on HRQoL. HF has a greater influence on the patient's perceived HRQoL than many other chronic diseases [3]. In this study we wanted to derive QALY weights from a simple but reliable method for measuring functional status in individual patients. We used NYHA class, which is a well-known and reliable method for assessing functional status and is frequently used in clinical practice all over the world. The NYHA classification could be criticized for inter-rater reliability. However, the fact that it is still in clinical use after having been introduced in 1928, suggests that it is still considered to be a useful tool for clinicians, and also for the scientists who have used it in a multitude of clinical studies.

We also estimated the QALY weights of each NYHA class using the HF patients' own TTO valuations, an estimation that, to the best of our knowledge, has not previously been performed in HF patients. The choice of NYHA functional class as the basis for the assessment of QALY weights is partly because it is used in routine clinical practice when evaluating HF patients. If the algorithm to be used is too complex or takes too much time, the instrument will not be used in clinical routine. We therefore believe that in spite of the insensitivity resulting from using the NYHA functional classification as base, the robust and simple algorithm favours its use in clinical practice, where time is crucial.

A comparison of TTO-based QALY weights for other disease states (asthma: 0.88, chronic renal failure: 0.52, angina: 0.76 [28], for minor stroke: 0.72 [29], and for cystic fibrosis 0.7 [30]) with the reported scores among patients with NYHA functional class III heart failure (0.56), demonstrated a major negative impact of the disease on the patients' valuation of their health state. Thus, a patient in NYHA functional class III values one year in that health condition as less than seven months with full health.

4.1. NYHA class as an indicator of functional impairment and the impact of heart failure
The NYHA functional classification system is one of the most widely used means of classifying the functional status of patients with HF. However, the relationship between the physician's classification and the patient's self-assessed classification has only recently been studied from a prognostic point of view in HF patients [31]. Therefore, we compared the evaluations performed by the patient and by the examining cardiologist. Results show that many patients who consider themselves as functionally impaired tend to categorise themselves as belonging to a higher NYHA functional class compared with the cardiologist's evaluation. They also tend to evaluate the consequences of their condition on the perceived HRQoL as having a greater impact on most of the dimensions measured by SF-36 compared with the evaluation performed by the cardiologist.

Table 4 illustrates the relationship between NYHA functional class and TTO weights. A decrease in TTO weights, as evaluated both by the cardiologist and the patients themselves, was observed as functional capacity decreased. To illustrate the relationship between NYHA functional classification and the wall tension of the left ventricle, as measured by the plasma concentration of BNP, we also analysed the plasma concentration of BNP in relation to NYHA functional class. Results are presented in Table 3, and show that as the wall tension of the left ventricle increases, functional class is affected, although this analysis indicates a more complicated relationship between perceived functional class and objective cardiac impairment. Both BNP and the NYHA functional class or functional status, have been shown to provide prognostic information in the same population as the present study [31,32]. The plasma concentration of BNP is not only influenced by wall tension in the myocardium, but also by decreased elimination as observed in patients with impaired renal function, resulting in increased plasma concentrations. Valvular diseases which result in increased wall tension will also increase the plasma concentration of BNP even in the absence of HF. On the other hand, the majority of HF drugs will decrease the plasma concentration of BNP, with the exception of initial treatment with beta blockers, which induces an increase in the plasma levels. In this study population there are therefore factors that could influence the plasma concentration of BNP.

Analysing the different dimensions of the SF-36 across the different NYHA functional classes, General Health was the dimension that was most affected as the patient experienced more symptoms of advanced HF.

4.2. Is the study population representative of elderly patients with heart failure?
Most information about the consequences of HF is based on clinical studies of populations aged around 60 years. The actual mean age of HF patients in the real world, however, is around 75 years [33,34]. Hence, we regard our study population, who had a mean age of 72 years, as representative of the HF patients in general, and thereby providing accurate information about HRQoL. Another important aspect concerning the external validity of the results is how to interpret those patients who did not respond to the QoL questionnaire. Therefore, an analysis of baseline data from both the respondents and non-respondents was carried out (Table 1). In the literature, non-respondents often represent an important part of the population with greater severity of disease than the respondents. In our study the non-respondents were older, and a larger proportion had diabetes. On the other hand, a greater percentage of the respondents were receiving cardiovascular medication.

Analysis of data for pharmacological treatment, number of patients classified as NYHA class III, and pathological increased plasma BNP levels, showed no indication that the non-respondent group represented a more diseased group. Thus, we believe that the study population is representative of elderly patients with symptoms associated with HF.

The next question is whether the study population, of which only 30 patients had an EF <40%, is representative of the HF population in general? If this diseased group is compared with a population of a corresponding age in the same municipality, but without any medication or signs of HF on Doppler echocardiography evaluated at the same time, the mean plasma concentration of BNP was 7.02 mmol/L in the non-diseased group. If this plasma concentration is then applied to the analysed population with symptoms of HF, 232 patients out of 323 had a plasma concentration above this mean value. We therefore conclude that our population is probably representative of a HF population in the community.

4.3. Limitations
The fact that the study population consisted of patients with a mean age of 72 years is an important factor that must be taken into account. The impact of HF on HRQoL and TTO choices, as indicated in this study, is therefore restricted to older patients with HF. Consequently, it cannot be extrapolated to a younger population without taking proper age concerns into account. Also, one important limitation is that not all patients had heart failure according to Doppler echocardiography.

4.4. Conclusion
In this study of elderly patients with symptoms of HF, we have shown that by applying the NYHA functional classification we can obtain relevant QALY weights for the individual patient. The statistically significant correlation between NYHA functional class and the different dimensions of the SF-36 instrument have validated the information. Thus, elderly patients with symptoms of HF have an impaired perceived quality of life, comparable with other chronic diseases or even worse. The QALY weights provide important information concerning the impact of HF on valuation of life as perceived by the patients. Furthermore, the QALY weights linked to the NYHA classification could provide policymakers with a tool for use in economic evaluations of the treatment of HF.


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

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