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European Journal of Heart Failure 2005 7(2):243-251; doi:10.1016/j.ejheart.2005.01.012
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© 2005 European Society of Cardiology

The impact of chronic heart failure on health-related quality of life data acquired in the baseline phase of the CARE-HF study

Melanie J. Calverta,*, Nick Freemantlea and John G.F. Clelandb

a Department of Primary Care and General Practice, Primary Care Clinical Sciences Building, University of Birmingham Edgbaston, Birmingham B15 2TT, UK
b Department of Cardiology, University of Hull, Castle Hill Hospital Kingston upon Hull, UK

* Corresponding author. Tel.: +44 121 414 8595; fax: +44 121 414 6571. E-mail address: M.Calvert{at}bham.ac.uk


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
Aims: To assess the quality of life of patients with heart failure, due to left ventricular dysfunction (NYHA class III or IV), taking optimal medical therapy using baseline quality of life assessments from the CArdiac REsynchronisation in Heart Failure (CARE-HF) trial, and to evaluate the appropriateness of using the EQ-5D in patients with heart failure.

Methods and results: The quality of life of patients enrolled in CARE-HF was evaluated using the EQ-5D and Minnesota Living with Heart Failure Questionnaire. Response rates for the instruments were >90% and statistical modelling revealed an association between EQ-5D and Minnesota Living with Heart Failure scores. Heart failure is shown to have an important impact on all aspects of quality of life, but particularly on patients' mobility and usual activities, and leads to significant reductions in comparison with a representative sample of the UK population.

Conclusions: The impact of heart failure varies amongst patients but the overall burden of disease appears to be comparable to other chronic conditions such as motor neurone or Parkinson's disease. The EQ-5D appears to be an acceptable valid measure for use in patients with heart failure although further evidence of the responsiveness of this measure in such patients is required.

Key Words: CARE-HF • EQ-5D • Heart failure • Minnesota • Quality of life

Received August 19, 2004; Revised January 15, 2005; Accepted January 18, 2005


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Conclusions
 References
 
Understanding the impact of heart failure on patient's health-related quality of life (QoL) can provide valuable information to guide clinical decision-making. The World Health Organization defines quality of life as "an individual's perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns. It is a broad ranging concept affected in a complex way by the person's physical health, psychological state, personal beliefs, social relationships and their relationship to salient features of their environment" [1]. In a clinical setting, assessment of quality of life usually concentrates on health-related quality of life (QoL); the way in which physical, emotional and social well-being are affected by a disease or its treatment [2]. Assessment of QoL in patients with heart failure complements traditional measures of clinical effectiveness such as reduction in mortality and hospitalisations. Patients with heart failure experience numerous symptoms (including: dyspnea, oedema, fatigue, lack of appetite, and persistent cough) [3] but, without some means of formal assessment, clinicians may find it difficult to gauge how the disease or its treatment impacts on their patients' physical, emotional, and social well-being. The importance of QoL to these patients is highlighted by the fact that some patients may be willing to trade survival for improved QoL [4,5].

The impact of heart failure on patients' QoL has been evaluated through comparison with a sample of the general population and patients with chronic disease. Studies indicate that heart failure leads to significant impairment in all aspects of QoL and that patients with heart failure reported more severe physical impairment than those with chronic lung disease or arthritis [6–9]. Such studies provide a valuable insight into the burden of heart failure; however, the majority of patients in these studies were in NYHA class II or not on optimal medical therapy.

In this article we aimed to assess the impact of advanced heart failure (NYHA III or IV) on patients' QoL, using baseline results from patients enrolled in the CARE-HF (CArdiac REsynchronisation in Heart Failure) study [10]. Patients enrolled in the study were already receiving optimal medical therapy where indicated and tolerated. The burden of heart failure on QoL is evaluated through comparisons of the baseline EQ-5D assessments from CARE-HF with results from a sample of the UK general population [11,12] and from patients with other chronic diseases [13–17]. In addition we aim to provide a preliminary evaluation of the appropriateness of EQ-5D use in patients with heart failure.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Conclusions
 References
 
2.1. CArdiac REsynchronisation in Heart Failure (CARE-HF) trial
The rationale and design of the CARE-HF study have been reported [10]. In brief CARE-HF is an international, open-label randomised controlled trial designed to evaluate the effects of cardiac (bi-ventricular) resynchronisation on the mortality and morbidity of patients already receiving optimal medical therapy with chronic heart failure due to left ventricular systolic dysfunction and dysynchrony. Patients were enrolled at 82 clinical centres in Austria, Belgium, Denmark, Finland, France, Germany, Italy, the Netherlands, Spain, Sweden, Switzerland, and the United Kingdom between January 2001 and March 2003. Baseline evaluation prior to randomisation included assessment of patient demographics, medical history and QoL, a physical examination, blood tests, and an echocardiographic examination.

2.2. Quality of life assessment
The QoL of patients enrolled in the CARE-HF study was assessed comprehensively using generic (EQ-5D) [18] and disease-specific (MLWHF [19,20]) instruments at baseline (prior to randomisation) and at 3 months. The long-term effects of CRT on QoL will also be evaluated at 18 months and at the end of the study using the MLWHF.

The EuroQoL EQ-5D is a self-administered, validated, generic preference-based measure of health status that comprises a 5-question multi-attribute questionnaire and a visual analogue self-rating scale [18,21]. Respondents are asked to rate severity of their current problems (level 1=no problems, level 2=some/moderate problems, level 3=severe/extreme problems) for five dimensions of health: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Patients can therefore be classified into 243 (35) health states plus two further additional states (unconscious and dead). EQ-5D health states may be converted into an EQ-5Dindex score ranging from –0.594 to 1.0 (where 1 is full health and 0 is dead) using a set of weighted preferences produced from the UK population [22]. The EQ VAS is a visual analogue scale on which respondents are asked to rate their own health state relative to full health (score=100) or worst imaginable health state (score=0).

The MLWHF is a validated, disease-specific, self-administered questionnaire [19,20]. This instrument consists of 21 questions focussing on the impact of heart failure on QoL. Patients are asked to rate the extent to which their heart failure has prevented them from living as they wanted during the last month using questions rated on a scale of 0 (no effect) to 5 (very much). The questionnaire is scored by summating the responses to all 21 questions; thus resulting in a score from 0 to 105 with a higher score reflecting poorer quality of life. The results are commonly reported as a summary score rather than presenting responses to individual questions. In this report, the results from individual questions will also be presented to provide clinicians with more detailed information on the impact of heart failure on specific aspects of patients' QoL.

2.3. Statistical analysis
Analyses were performed using SAS V8.2 (SAS Institute, Cary NC) and StatsDirect V2.29 (StatsDirect Ltd.). The relationships between NYHA status, gender, age, and QoL were evaluated using a mixed linear model with an identity link, normal error and with clinical centres as random effects. Evaluation of the effect of country on the baseline EQ-5Dindex score was evaluated using a mixed linear model with an identity link, normal error, and with clinical centres as random effects. The relationship between the EQ-5Dindex and MLWHF score was evaluated using mixed modeling with clinical centres as random effects [23].


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Conclusions
 References
 
The baseline characteristics of the 813 patients enrolled in the study are shown in Table 1. The mean age of patients enrolled in the study was 65 (S.D.=10) years and 215 patients (26%) were female. 763 patients (94%) of patients were classified as NYHA class III and the remaining 50 (6%) as class IV.


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  		Table 1 Baseline demographic and clinical characteristics

 
3.1. Quality of life
3.1.1. Response rates for QOL baseline assessments
The baseline response rates for each of the QoL instruments are shown in Table 2. 740 (91%) completed all 5 items of the EQ-5D describing their current health status whilst 703 (86%) of the patients completed the visual analogue scale. Of the 64 patients with missing EQ-5D forms, 58 patients were in NYHA class III and 6 in NYHA class IV. 539 patients (66%) completed all 21 items of the MLWHF (506 patients in NYHA class III and 33 patients in NYHA class IV); however, a further 214 patients completed most of the questionnaire (with 135 patients missing only one item). A high proportion of missing responses was observed for items relating to working to earn a living and sexual function as shown in Fig. 5.


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  		Table 2 Response rates for QoL baseline assessments

 
3.1.2. Sensitivity of instruments in response to gender, age, and NYHA classification
Analysis of the relationship between gender, age and NYHA status and EQ-5Dindex score revealed a non-significant relationship between age and score, but a significant association between EQ-5Dindex score, gender and NYHA status. A model of the relationship between EQ-5Dindex score and gender (accounting for NYHA status), with clinical centres as random effects, indicates that on average females enrolled in the CARE-HF trial had a worse QoL than the male participants (regression coefficient –0.08; 95% CI –0.13 to –0.04, p=0.0004). This observed decrease in EQ-5Dindex score arises from a greater proportion of females reporting problems in each of the five dimensions. A non-significant increase in MLWHF score of 3.5 (95% CI –0.46 to 7.5, p=0.08) also indicated that female patients enrolled in the study appear to have reduced QoL compared to males (accounting for NYHA status). Both the EQ-5Dindex and MLWHF appeared to be sensitive to NYHA class. The mean EQ-5Dindex score for NYHA III patients was significantly higher than for NYHA IV patients (accounting for gender) with a mean difference of 0.17 (95% CI 0.08 to 0.25, p<0.0001). Similarly, the mean score for NYHA III patients that completed all questions on the MLWHF questionnaire was significantly lower than for NYHA IV patients with a mean difference of –14.0 (95% CI –6.8 to –21.1, p=0.0001), indicating that, as expected, on average, class IV patients experience a poorer QoL.

3.1.3. Evaluation of the relationship between EQ-5Dindex and MLWHF scores
The relationship between the MLWHF summary score and the EQ-5Dindex score was examined for those patients with complete data for both assessments at baseline (n=522). Mixed modelling revealed an association between MLWHF and EQ-5Dindex scores (p<0.0001) with a regression coefficient of –0.00795 (95% CI –0.00885 to –0.00706; Fig. 1) [23]. As expected, increasing MLWHF score was associated with a decrease in EQ-5Dindex score.


Figure 1
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  		Fig. 1 The relationship between EQ-5Dindex and MLWHF scores. Line indicates predicted EQ-5Dindex scores from the following model: EQ-5Dindex=0.9554–0.00795xMLWHF Score.

 
3.1.4. Comparison of the EQ-5Dindex scores of patients enrolled in the CARE-HF study with UK population norms and patients with other chronic disease
In order to assess the impact of chronic heart failure on QoL we compared the mean baseline EQ-5Dindex and EQ VAS results of patients enrolled in the CARE-HF study with a representative sample of the UK population stratified by age (Figs. 2 and 3, respectively) [11,12]. Since this comparison assumes that baseline EQ-5D scores from non-UK countries are comparable to UK data we evaluated the differences in baseline EQ-5Dindex score by country using a mixed model. The results from this model suggest that in the CARE-HF trial the non-UK baseline scores were comparable to scores obtained for UK patients (regression coefficient 0.034; 95% CI –0.04 to 0.11).


Figure 2
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  		Fig. 2 A comparison of UK general population ({blacksquare}) and CARE-HF baseline ({square}) EQ-5Dindex scores by age (95% CI are indicated).

 


Figure 3
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  		Fig. 3 A comparison of UK general population ({blacksquare}) and CARE-HF baseline ({square}) mean self-rated health status (EQ VAS scores) by age (95% CI are indicated).

 
The mean EQ-5Dindex and EQ VAS scores were significantly lower in the CARE-HF population than in the general population for all age groups, but unlike in the general population, it did not decrease with age. A more detailed comparison of CARE-HF QoL results with normative data from the UK general population stratified by age revealed that the proportion of patients reporting any problems was greater for CARE-HF patients in all 5 dimensions and for all age groups (Table 3) [12]. Heart failure appears to have a large impact on patients' usual activities since 76% of patients in CARE-HF reported problems in this dimension compared with 16% of the population sample. Further examination revealed that 15% of patients in CARE-HF perceived these problems as extreme (Table 4). Two-thirds of patients enrolled in CARE-HF reported mobility problems compared with 18% of the general population sample; however, only 1% of patients reported these as extreme. Over two-thirds of patients in CARE-HF reported pain/discomfort and 50% of patients reported anxiety/depression. Fewer patients (24%) reported problems washing or dressing themselves.


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  		Table 3 A comparison of UK general population and CARE-HF baseline assessments for EQ-5D health states

 


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  		Table 4 Numbers (percentages) of CARE-HF patients reporting problems in each EQ-5D dimension

 
The mean EQ-5Dindex score for the CARE-HF population is compared to mean scores from patients with other chronic conditions and mean normative values in Fig. 4 [13–17]. This comparison with selected published studies indicates that the overall QoL of patients enrolled in the CARE-HF study is similar to that experienced by patients with mild to moderate motor neurone disease, Parkinson's disease, patients assessed approximately 3 months after ischemic stroke, and patients with non-small cell lung cancer [14–17]. Studies selected for comparison included patients with a similar mean age to those enrolled in CARE-HF although this comparison is limited since differences in other patient demographics may also potentially impact on QoL in addition to the disease.


Figure 4
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  		Fig. 4 Forest plot showing the mean EQ-5Dindex score of patients enrolled in the CARE-HF study compared with the mean EQ-5Dindex scores from patients with other chronic disease [13–17] and a sample of the UK population [11]. The mean EQ-5Dindex score for patients enrolled in CARE-HF is indicated (dashed line). *As defined by the ALS Health State Scale [34].

 
3.1.5. Results from the disease-specific Minnesota Living with Heart Failure questionnaire
The responses from the 753 patients completing the MLWHF are summarised in Fig. 5. Most patients experienced fatigue, shortness of breath, and had difficulties in walking or climbing the stairs and many patients had to sit or lie down to rest during the day and had difficulties working around the house. Other activities were also limited due to the condition particularly recreational pastimes, sports hobbies, and sexual activities. Although some emotional concerns were expressed, the impact of heart failure on this dimension is less than that observed for the physical dimension. The mean summated score for all 21 questions, for those patients with complete data (n=539) was 45.4 (S.D.=21.2). Assignment of a zero to items missing at baseline, for those patients who completed a form (n=753), results in a mean MLWHF score of 44.1 (S.D.=21.2).


Figure 5
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  		Fig. 5 Assessment of baseline QoL in patients enrolled in CARE-HF: results from the Minnesota Living with Heart Failure questionnaire for those patients that responded (n=753).

 
3.1.6. Overall health and quality of life
Results from the EQ VAS ranged from 0 (worst imaginable health state) to 100 (best imaginable health state). The maximum range of response was also observed for the EQ-5D (from 11 111 to 33 333 corresponding to index scores of 1.0 and –0.594, respectively). Assignment of negative index scores indicates states worse than dead. Thirty-one patients with EQ-5D results (4.2%) had negative preference scores. Conversely, fifty-five patients (7.4%) were assigned index scores of 1 corresponding to full health.


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Conclusions
 References
 
4.1. The impact of heart failure on quality of life
This study has evaluated for the first time the QoL of a large sample of patients with advanced heart failure (NYHA III or IV) already receiving optimal medical therapy (where indicated and tolerated). Comparison of the EQ-5Dindex and EQ VAS scores from patients with heart failure enrolled in the CARE-HF study with a sample of the UK population revealed significant impairment in their overall QoL. The mean EQ-5Dindex scores of patients enrolled in CARE-HF were comparable to patients with other severe chronic conditions such as motor neurone [14] and Parkinson's disease [15] despite patients generally being on optimal medical therapy. The mean MLWHF score reported for patients enrolled in CARE-HF (45.4, S.D.=21.2) was greater, indicating poorer QoL, than the mean of 32.4 reported for patients with less severe heart failure enrolled in the Val-HeFT trial [24]. Patients enrolled in CARE-HF appear on average to have a better QoL than those enrolled in previous CRT studies such as MIRACLE (mean score 59, S.D.=20) or MUSTIC (mean score 51, S.D.=20) [25,26].

Whilst the impact of heart failure on QoL appears to be independent of age, which results in the largest impact of heart failure on QoL occurring in younger age groups compared to the general population, the QoL of patients with heart failure does appear to be associated with gender. On average female patients enrolled in CARE-HF reported a greater number of problems in all five dimensions of the EQ-5D. This is consistent with previous studies, which indicate that women with heart failure experience greater physical impairment and decreased QoL compared to men [27,28].

This study shows that heart failure leads to reductions in all 5 dimensions of health status assessed by the EQ-5D and in particular has a large impact on usual activities and physical functioning as has been shown previously [6,7]. Results from the EQ-5D show that the disease has an important impact on the ability of patients to perform their usual activities, with 76% of patients reporting problems in this dimension. This is consistent with results from the MLWHF, which indicate that at least 50% of patients felt that their disease made their recreational pastimes, sports or hobbies difficult. The MLWHF did not directly assess the impact of heart failure on pain and discomfort but the EQ-5D results indicate that over two thirds of patients suffered from at least moderate problems in this dimension. Half of the patients completing the EQ-5D also indicated feelings of anxiety and depression, however, interestingly, results from the MLWHF reveal that fewer patients regarded worry or depression as preventing them from living as they wanted.

Results from this study also indicate that the impact of heart failure on QoL is varied, with EQ-5Dindex scores ranging from states worse than dead to full health. It is however important to consider that since these scores, corresponding to the reporting of problems in the five dimensions of health, are based on tables of values derived from a UK population sample [22] that patients with negative scores may not actually perceive themselves to be in a state worse than dead. Responses to the EQ VAS which captures patients self-rated health status in a single response were also varied with some patients valuing their health as the "best imaginable" whilst others reported the "worst imaginable". This disability paradox may arise from a response shift due to patients adapting to their illness over time, or may be due to selective reporting bias with patients rating their QoL relative to others with the disease [29]. Alternatively patients may still feel they have a strong control over their bodies, minds and lives even if others may not perceive this as the case [30].

4.2. Is EQ-5D a valid measure for assessment of QoL in heart failure patients?
The EuroQol EQ-5D was not intended to provide an exhaustive assessment of the impact of heart failure and its treatment on QoL but to provide a simple rapid assessment of the QoL of patients enrolled in the study, to generate preference-based scores for use in cost–utility analysis and to allow comparisons to patients with other disease. The high response rates, sensitivity to NYHA status, and the statistically significant relationship between the MLWHF and EQ-5Dindex scores suggest that the EQ-5D may be an acceptable, valid measure for use in heart failure patients. Unlike for some other diseases, such as osteoarthritis [31], this measure appears to discriminate well between patients despite the "coarseness" of the levels. This may be because this progressive disease impacts on all aspects of QoL. However, further evaluation of the psychometric properties of the EQ-5D in heart failure patients is required.

4.3. Use of generic and disease-specific measures
Use of the EQ-5D alongside a disease-specific tool in the CARE-HF study provides links between the assessment of QoL in patients with heart failure in the CARE-HF study not only to both the QoL of the general population and patients with other diseases, but also to patients with heart failure in other studies. The disease-specific MLWHF complements data gathered with the EQ-5D since it provides more detailed information on factors affecting QoL specifically due to heart failure. The great majority of patients completed the EQ-5D but many patients did not complete one or more items of the MLWHF. The difference in missing data for these instruments may represent the trade off between depth of information and the burden of assessment. Missing data is a serious problem in QoL assessment and can prove particularly problematic when planned analyses assume availability of complete patient data for summating scales [32]. When missing data is observed, it is important to consider whether data is missing completely at random or whether the rate of missing data may be related to the patients QoL [2]. Reassuringly the number of missing forms for patients with different levels of symptoms was not significantly different, but some items in the MLWHF do not appear to be missing at random. Items relating to working for a living and sexual functioning were missing more frequently than other items. This may have arisen due to patients being retired or unemployed and thus perceiving the question as irrelevant. Patients with missing data relating to sexual function may have found this question too personal to answer or may not have been sexually active.

4.4. Limitations
A limitation of this study is that the patients assessed in this study are not a random sample of patients with severe heart failure. Patients enrolled in the study had chronic heart failure, were already receiving optimal medical therapy, had ventricular dyssynchrony and a LVEF≤35% [10]. In addition CARE-HF is an international study but we have used available normative data from a representative sample of the UK population to evaluate the burden of disease and have also made comparisons to disease-specific studies from the UK and USA and Italy [11–17]. Reassuringly a model of the relationship between EQ-5Dindex score and country suggests that UK and non-UK data are comparable, however the comparison is limited since differences in patient demographics may also potentially impact on QoL in addition to the disease. Furthermore a study comparing UK and Spanish time trade-off values for EQ-5D health states has demonstrated that although the general pattern of value assignation was similar, there were differences in values assigned to a number of health states [33].


   5. Conclusions
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusions
References
 
This study shows that despite intense pharmacological therapy many patients with heart failure still have major impairment in many aspects of their QoL. This study also revealed wide variability in the QoL of these patients. Such varied responses may not be expected by clinicians and highlights the potential use of routine QoL assessments in heart failure patients to identify patients concerns, facilitate communication, and to guide clinical decision-making.

Findings from this study also suggest that the EQ-5D may be an acceptable valid measure for use in heart failure patients although further evidence on the responsiveness of this measure in such patients is required. Based on preference scores generated from this measure we have shown that QoL is reduced markedly and to a similar extent as other serious chronic diseases.

Furthermore based on the observed relationship between the EQ-5Dindex and MLWHF scores and the observed 13 point decrease in MLWHF score in the MUSTIC trial [25] we predict that CRT may potentially lead to a 0.1 increase in EQ-5Dindex score. CARE-HF will provide us with an opportunity to evaluate whether this clinically important change in utility occurs in response to CRT and will also crucially evaluate the impact of CRT on morbidity and mortality.


   Acknowledgement
 
We thank Professor Luigi Tavazzi and Dr Anna Maria Zotti for their helpful comments and suggestions.


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

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