Download Faller H, Störk S, Schowalter M, Steinbüchel T, Wollner V, Ertl G

Journal of Psychosomatic Research 63 (2007) 533 – 538
Short communication
Is health-related quality of life an independent predictor of survival in
patients with chronic heart failure?☆
Hermann Faller a,⁎, Stefan Störk b , Marion Schowalter a , Thomas Steinbüchel a ,
Verena Wollner b , Georg Ertl b , Christiane E. Angermann b
a
Institute of Psychotherapy and Medical Psychology, University of Würzburg, Würzburg, Germany
Department of Internal Medicine I, Center of Cardiovascular Medicine, University of Würzburg, Würzburg, Germany
b
Received 11 January 2007; received in revised form 4 June 2007; accepted 19 June 2007
Abstract
Objective: The aim of this study was to examine whether the
physical and mental components of health-related quality of life
(HRQoL) are independent predictors of survival in patients with
chronic heart failure (CHF). Methods: A cohort of 231 outpatients
with CHF was followed prospectively for 986 days (median;
interquartile range=664–1120). Generic HRQoL was measured
with the Short Form-36 Health Survey (SF-36), disease-specific
HRQoL was measured with the Kansas City Cardiomyopathy
Questionnaire, and depression was measured with the selfreported Patient Health Questionnaire. Results: Both generic
and disease-specific HRQoL were predictive of survival on
univariate analyses. After adjustment for prognostic factors such
as age, gender, degree of left ventricular dysfunction, and
functional status, only the mental health component of SF-36
and the disease-specific HRQoL remained significant. When
depression was included, both measures also lost their predictive
power. Conclusion: Our data suggest that the prognostic value of
patients' HRQoL reflects confounding with the severity of disease
and comorbid depression.
© 2007 Elsevier Inc. All rights reserved.
Keywords: Chronic heart failure; Depression; Health-related quality of life; Prognosis; Survival
Introduction
Chronic heart failure (CHF) is associated with a high
mortality risk [1] and severely compromises patients' healthrelated quality of life (HRQoL) [2,3]. Conflicting evidence
exists as to whether HRQoL has, in itself, prognostic power
on the prediction of mortality risk. Some [4–8], but not
all [9], studies have found that self-reported HRQoL
independently predicted poorer survival in patients with
heart failure. Thus, the question on whether patients'
subjective health perceptions capture additional prognostic
information beyond the information gained from more
☆
There are no conflicts of interest.
⁎ Corresponding author. Institute of Psychotherapy and Medical
Psychology, University of Würzburg, D-97070 Würzburg, Germany.
Tel.: +49 931 312713; fax: +49 931 316080.
E-mail address: [email protected] (H. Faller).
0022-3999/07/$ – see front matter © 2007 Elsevier Inc. All rights reserved.
doi:10.1016/j.jpsychores.2007.06.026
objective indicators of disease severity, such as left
ventricular ejection fraction (LVEF) and degree of physician-rated disease severity, remains unresolved. Moreover,
patients' HRQoL is associated with depression [10], and
depression has also been found to predict survival [11–13].
Thus, the prognostic value of patient-reported HRQoL may,
at least in part, reflect confounding by depression. If this
were the case, the predictive power of HRQoL should be
diminished or even lost after adjustment for depression. The
current prospective cohort study compares the relative
prognostic value of HRQoL, quantitative assessments of
left ventricular function, degree of physician-rated disease
severity, and depression in CHF patients.
We sought to clarify the following questions: (a) Is
HRQoL predictive of reduced survival in patients with
CHF after adjusting for established important biomedical variables known to affect survival? (b) If so, does
this association hold after including depression as an
additional covariate?
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H. Faller et al. / Journal of Psychosomatic Research 63 (2007) 533–538
participate in voluntary psychometric assessment. The
study was approved by the Ethics Committee of the
University of Würzburg (Würzburg, Germany). All subjects
provided written informed consent. The diagnosis of CHF
was confirmed by clinical, laboratory, and echocardiographic criteria. Left ventricular dimensions and fractional
shortening were measured by M-mode echocardiography,
and diastolic filling characteristics were assessed by
Doppler techniques. Patients were eligible to participate
in the INH if they had CHF with either impaired left
ventricular systolic function (fractional shortening, b24%)
or preserved left ventricular function (left ventricular
fractional shortening, ≥24%), with abnormal diastolic
filling characteristics on Doppler echocardiography, in
addition to typical signs and symptoms of CHF (at least
one of the following: raised jugular venous pressure,
peripheral edema, third heart sound, and pulmonary
congestion at clinical examination or chest X-ray).
Patients' generic HRQoL was measured using the Short
Form-36 Health Survey (SF-36) [14]. The SF-36 is a widely
used international standardized tool that contains eight
subscales (physical function, role—physical, bodily pain,
general health, vitality, role—emotional, social function, and
mental health), as well as two summary scales (physical
health, Subscales 1–4; mental health, Subscales 5–8). Scores
may range from 0 to 100, with higher scores indicating
better HRQoL. Due to restrictive prescriptions for the
handling of missing data when computing for SF-36 physical
health and mental health summary scales, the sample size
for analyses covering the SF-36 scales was considerably
reduced (n=192).
Table 1
Descriptive statistics of the study participants (n=231)
Age (years) [mean (S.D.)]
Female gender (%)
NYHA functional class (%)
I/II
III/IV
Ischemic etiology of heart failure (%)
Ejection fraction (%) [mean (S.D.)]
Comorbidities/risk factors (%)
Obesity a
Hypercholesterolemia b
Diabetes
Hypertension c
Renal dysfunction
Medication (%)
Angiotensin-converting enzyme inhibitor
Aldosterone antagonist
Diuretic
Beta blocker
64 (13)
29.4
25.3/44.1
24.9/5.7
42.8
44 (15)
40.2
60.3
29.3
57.6
12.4
71.2
28.8
79.5
68.6
P values refer to chi-square test and Student's t test, as appropriate.
a
b
c
Body mass index N30 kg/m2.
Total cholesterol N200 mg/dl or on lipid-lowering drugs.
Blood pressure N140/90 mmHg or on antihypertensive drugs.
Method
Between June 2002 and December 2003, the prospective
cohort study “Interdisciplinary Network for Heart Failure”
(INH) Würzburg consecutively recruited all patients
presenting with CHF of any etiology and severity at two
Würzburg University medical centers (N=1054). The
present subsample (n=231; participation rate=22%)
includes subjects who gave written informed consent to
Table 2
HRQoL in the total cohort and in subgroups, by severity of depression
Total sample (n=231)
SF-36
Physical function
Role—physical
Bodily pain
General health
Vitality
Social function
Role—emotional
Mental health
PCS
MCS
KCCQ
Physical limitation
Symptoms
Self-efficacy
Quality of life
Social limitation
Functional status
Clinical summary score
No depression
(n=162)
Minor depression
(n=38)
Major depression
(n=31)
Mean
S.D.
Range
Mean
S.D.
Mean
S.D.
Mean
S.D.
P
47.4
28.8
62.2
43.8
42.5
67.2
48.0
60.6
36.1
44.3
28.3
41.0
29.6
16.9
22.0
27.5
46.7
19.9
10.6
11.5
0–100
0–100
0–100
5–97
0–100
0–100
0–100
16.0–100
10.5–61.0
21.1–66.7
53.7
37.6
68.2
47.2
50.6
74.6
58.7
66.9
38.1
48.0
27.0
43.7
27.8
16.8
19.6
24.9
45.3
17.7
10.5
9.7
37.9
6.9
52.6
39.4
26.6
53.6
30.6
49.7
32.5
37.7
27.0
21.2
28.8
14.2
16.0
21.1
43.9
17.3
9.6
11.0
26.6
10.7
42.9
30.8
21.1
45.0
15.5
42.0
29.8
32.9
23.4
27.6
28.8
13.3
13.1
30.2
35.7
16.4
8.8
9.6
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
b.001
63.3
68.5
71.3
56.6
58.3
66.1
61.8
24.0
24.6
22.4
25.7
27.6
22.1
21.7
6.3–100
0–100
0–100
0–100
4.2–100
2.8–100
2.8–100
68.6
75.9
74.8
64.7
65.1
72.5
68.7
22.4
21.6
20.9
23.4
25.1
19.6
19.2
51.4
55.7
61.8
41.9
42.1
54.4
47.9
20.9
22.4
25.5
20.1
23.2
20.0
16.8
50.6
45.9
64.9
32.8
42.2
47.8
42.6
26.1
22.0
21.8
20.2
30.4
21.6
20.1
b.001
b.001
.001
b.001
b.001
b.001
b.001
P values are derived from the comparison of patients with no depression versus patients with minor depression versus patients with major depression
(ANOVA).
H. Faller et al. / Journal of Psychosomatic Research 63 (2007) 533–538
535
Fig. 1. Quality of life scores (mean values), by NYHA functional class. All differences between NYHA functional classes are significant at Pb.001 [analysis of
variance (ANOVA)]. KCCQ, Kansas City Cardiomyopathy Questionnaire clinical summary score.
screening instruments when evaluated against the Structured Clinical Interview for the International Classification
of Diseases, Tenth Revision [18] or the Diagnostic and
Statistical Manual of Mental Disorders, Fourth Edition as
reference standard [19].
The outcome variable was time from study entry to allcause death. Follow-up assessment of patient survival was
performed in October 2005 at a median follow-up time of
986 days (interquartile range=664–1120). No patient was
lost to follow-up. Kaplan–Meier probabilities of survival
were computed. Cox proportional hazards regression was
used to determine the relationship between HRQoL and
survival. First, the SF-36 physical health component score
(PCS) and mental health component score (MCS), as well as
the KCCQ clinical summary score, were analyzed individually for their predictive value on univariate analyses,
respectively. Second, in multivariable models, biomedical
predictor variables [age, gender, LVEF, and New York Heart
Patients' disease-specific HRQoL was assessed using the
self-reported Kansas City Cardiomyopathy Questionnaire
(KCCQ). This newly developed tool was designed for
patients with CHF and has demonstrated very good
reliability and validity coefficients for both the original US
version [15] and the German version [16]. It covers the
following domains: physical function, symptoms (frequency
and severity), self-efficacy, quality of life (psychological
well-being), and social limitation. A clinical summary scale
integrating all subscales, with the exception of self-efficacy,
is also available. Scores may range from 0 to 100, with
higher scores indicating better health status.
Depression was measured using the German version of
the Patient Health Questionnaire depression module PHQ-9
[17–19]. This nine-item self-report screening tool allows for
the probable diagnosis of a current episode of major or minor
depression using its categorical algorithm. The PHQ-9
diagnosis of depression compared favorably to other
Table 3
Cox proportional hazards regression with survival as dependent variable and HRQoL indicators as predictors, with and without adjustment for other prognostic
factors (n=231)
SF-36 PCS
P
Univariate analysis
HRQoL measure
b.001
Multivariate analysis (Model A)
HRQoL measure
.19
Age
.27
Gender
.24
LVEF
.14
NYHA functional class
b.001
Multivariate analysis (Model B)
HRQoL measure
.29
Age
.18
Gender
.30
LVEF
.17
NYHA functional class
b.001
Major depression
.14
Minor depression
.86
SF-36 MCS
HR
95% CI
0.93
0.90–0.96
0.98
1.02
1.50
0.99
3.00
0.98
1.02
1.44
0.99
2.88
1.77
0.93
P
KCCQ clinical summary score
HR
95% CI
P
HR
95% CI
.009
0.97
0.94–0.99
b.001
0.97
0.96–0.98
0.94–1.01
0.99–1.06
0.76–2.97
0.97–1.01
1.98–4.56
.04
.14
.45
.04
b.001
0.97
1.02
1.29
0.98
3.11
0.94–1.00
0.99–1.06
0.67–2.47
0.96–1.00
2.11–4.57
.049
.012
.33
.13
b.001
0.99
1.03
1.33
0.99
2.66
0.97–1.00
1.01–1.06
0.75–2.36
0.97–1.00
1.81–3.91
0.95–1.02
0.99–1.06
0.72–2.85
0.97–1.01
1.89–4.38
0.83–3.77
0.39–2.21
.15
.13
.46
.07
b.001
.37
.81
0.98
1.03
1.28
0.98
3.04
1.45
0.90
0.95–1.01
0.99–1.06
0.66–2.48
0.96–1.00
2.04–4.52
0.64–3.34
0.38–2.13
.16
.007
.36
.15
b.001
.14
.60
0.99
1.04
1.31
0.99
2.67
1.71
0.81
0.97–1.01
1.01–1.07
0.74–2.34
0.97–1.01
1.81–3.92
0.84–3.48
0.38–1.74
Model A: adjusted for age, gender, ejection fraction, and NYHA functional class.
Model B: Model A, with additional adjustment for depression (major depression vs. no depression; minor depression vs. no depression).
536
H. Faller et al. / Journal of Psychosomatic Research 63 (2007) 533–538
Association (NYHA) functional class] were added to the
respective HRQoL scales. Thus, in the second models, we
tested HRQoL against indicators of disease severity. Third,
depression was additionally controlled for by also including
depression in the multivariable models. HRQoL variables
were included as continuous variables. The assumption of
proportional hazards was checked by plotting log-minus-log
functions. Pb.05 (two sided) was considered significant.
SPSS 14.0 software (SPSS, Inc., Chicago, IL) was used.
Results
KCCQ clinical summary score remained significant (Table 3,
middle panel, Model A). The SF-36 PCS, however, lost its
predictive power after adjusting for the abovementioned
prognostic factors.
To further clarify this issue, we included a measure of
depression (PHQ-9) in the analyses. On univariate analysis,
major depression, as compared to no depression, had proven
predictive of shorter survival (HR=3.3; 95% CI=1.8–6.1;
Pb.001). After the inclusion of major depression as an
additional covariate, the SF-36 MCS also lost its predictive
value (Table 3, bottom panel, Model B). Thus, the mental
health component of HRQoL appears to reflect, at least in
part, patients' comorbid depression.
Descriptive statistics
The descriptive statistics of the study cohort are presented
in Table 1. The mean age was 64 years (S.D.=13); 71% were
male and 73% were married. CHF etiologies were as
follows: coronary heart disease, 43%; dilated cardiomyopathy, 22%; hypertension, 14%; other diseases, in 21%. One
hundred twenty-one (52%) patients suffered from systolic
heart failure (mean ejection fraction=33.0%), and 108 (47%)
suffered from nonsystolic heart failure (mean ejection
fraction=56.5%). The distribution of NYHA Functional
Classes I/II/III/IV was 25%/44%/25%/6%. The median time
since the diagnosis of CHF was 42 months (interquartile
range=6–90).
The distribution of HRQoL measures in our sample of
CHF outpatients is given in Table 2. Compared to low levels
of the SF-36 physical health and mental health summary
scores, the KCCQ clinical summary scale covers a broader
range of scores (Fig. 1).
According to the PHQ-9, 31 (13%) patients suffered from
probable major depression and 38 (17%) suffered from
minor depression at the time of study inclusion. HRQoL was
significantly and substantially reduced across all dimensions
in patients with either major or minor depression compared
to those without depression (Table 2).
Survival analysis
At the time of follow-up, 59 (26%) patients had died.
The results of the univariate analyses for both generic
and disease-specific HRQoL indicators are presented in
Table 3 (top panel). The SF-36 PCS and MCS, as well as
the KCCQ clinical summary score, were predictive of
survival. To convey an idea of the magnitude of the
effect, we graded the KCCQ clinical summary score by
10-point categories, since 10-point steps are deemed to be
clinically significant. As the univariate hazard ratio (HR) of
1.40 [95% confidence interval (95% CI)=1.24–1.59;
Pb.001] shows, a 10-point decrease in the KCCQ clinical
summary score confers an increase of approximately 40%
in mortality.
After entering age, gender, LVEF, and NYHA functional
class in the regression model, both the SF-36 MCS and the
Discussion
The aim of our study was to clarify the prognostic value
of patient-reported HRQoL. Both generic (SF-36) and
disease-specific (KCCQ) measures of HRQoL were predictive of survival on univariate analyses, consistent with
previous research [4–9]. After adjustment for established
prognostic factors indicative of disease severity and
mortality risk, such as age, left ventricular dysfunction,
and NYHA functional class, however, only the mental
component of generic HRQoL and the disease-specific
measure remained predictive, whereas the physical component lost its prognostic power. This result is consistent with
previous research showing that the KCCQ summary score
remained predictive of survival even after controlling for
NYHA functional class [7]. Another study found that the
KCCQ was predictive of a combined endpoint of death or
hospitalization after adjusting for numerous clinical prognostic factors, albeit not NYHA functional class [20].
We therefore conclude that the prognostic value of the
physical component of generic HRQoL demonstrated on
univariate analysis may result from confounding with
disease severity captured particularly by NYHA functional
class status. This conclusion is, however, somewhat limited
by the subjective nature of the NYHA functional class
ratings. Patients' subjective perceptions of their functional
state, although assessed by attending physicians, may have
influenced their physicians' judgements. As a consequence,
including NYHA functional class in the model might have
led to an overcorrection that unduly suppressed the effects of
the HRQoL measures. Thus, although ratings by physicians
and patients may well consider different aspects of the
impact of heart failure on daily living [21,22], NYHA
functional class ratings by physicians are likely to more
reliably reflect disease-related physical functioning rather
than the degree of left ventricular dysfunction.
While the generic SF-36 component scores were far
below normal in our sample [3], the disease-specific KCCQ
summary scores were more widely distributed across the
possible range of the scale. This reflects better differentiation
of the KCCQ between subgroups according to measures of
H. Faller et al. / Journal of Psychosomatic Research 63 (2007) 533–538
the clinical severity of CHF such as NYHA functional
class [17].
After the inclusion of depression as an additional
covariate, the mental component of generic HRQoL, as
well as the disease-specific HRQoL measure, was no longer
significant. This indicates confounding by comorbid depression, as shown by the strong effect of depression on HRQoL.
Another way of interpreting these results is that depression
may mediate the influence of HRQoL on survival. As both
depression and HRQoL were measured at the same time
point, this issue cannot be further resolved. However,
regarding the possibly bidirectional association between
depression and HRQoL, several pathways may be considered. Lower HRQoL scores may reflect a more severe
burden of disease, which, in itself, may contribute to the
development of depression. Conversely, depressed patients
are likely to experience more pronounced functional
impairment, which may result in higher NYHA functional
class ratings. Furthermore, both depression and burden of
disease may result from interrelated biological mechanisms
such as proinflammatory cytokine secretion [23] or common
genetic vulnerability [24].
Limitations
Certain limitations need to be considered in the
interpretation of the present findings. We investigated a
heterogeneous cohort of patients with CHF across all NYHA
functional classes with preserved, as well as reduced,
ejection fraction. Considering the number of events and the
relatively small sample size of this investigation, we
refrained from more detailed analyses of confounders. A
further limitation is that self-reports of depression were not
confirmed by a structured interview. However, excellent
sensitivity (98%) and specificity (80%) of the PHQ-9, in
particular regarding major depression, have been well
established [19]. It should be noted that the 95% CIs of the
HRQoL predictor variables barely crossed the 1.0 value after
adjustment for NYHA functional class and depression,
respectively. The finding that these parameters thus lost their
predictive value may be a consequence of insufficient power.
Conclusion
While patients' self-reported HRQoL is predictive of
survival on univariate analysis, it may lose part of its
predictive value when either more objective and physicianbased measures of disease severity and left ventricular
functional impairment or measures of depression are taken
into account. However, these results will have to be
corroborated by larger studies. Nevertheless, it is important
to evaluate patients' HRQoL not only to identify patients
with increased mortality risk but also to assess the
effectiveness of treatment and to monitor the course of the
537
disease, as these measures are easily obtained. Finally, our
results confirm the findings of other authors that depression
is a prognostic factor in the mortality of patients with CHF
[11–13]. As presented elsewhere, we found that major
depression was associated with a doubled mortality risk even
after adjustment for important prognostic factors, such as
age, gender, etiology, type and degree of left ventricular
dysfunction, and functional status [25]. Although we tested
the predictive power of HRQoL and major depression
beyond that accounted for by established prognostic factors,
the observational design of our study precludes any causal
interpretation.
Acknowledgments
This study was supported, in part, by the Ernst and Berta
Grimmke Foundation (Düsseldorf, Germany) and by an
educational grant from Merck (Darmstadt, Germany).
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