The Impact of Selecting a High Hemoglobin

REVIEW ARTICLE
The Impact of Selecting a High Hemoglobin
Target Level on Health-Related Quality of Life
for Patients With Chronic Kidney Disease
A Systematic Review and Meta-analysis
Fiona M. Clement, PhD; Scott Klarenbach, MD, MSc; Marcello Tonelli, MD, SM;
Jeffrey A. Johnson, PhD; Braden J. Manns, MD, MSc
Background: Treatment of anemia in chronic kidney
disease (CKD) with erythropoietin-stimulating agents
(ESAs) is commonplace. The optimal hemoglobin treatment target has not been established. A clearer understanding of the health-related quality of life (HQOL) impact of hemoglobin target levels is needed. We
systematically reviewed the randomized controlled trial
(RCT) data on HQOL for patients treated with low to intermediate (9.0-12.0 g/dL) and high hemoglobin target
levels (⬎12.0 g/dL) and performed a meta-analysis of all
available 36-item short-form (SF-36) RCT data.
Methods: We conducted a search to identify all RCTs
of ESA therapy in patients with anemia associated with
CKD (1966–December 2006). Inclusion criteria were (1)
30 or more participants, (2) anemic adults with CKD,
(3) epoetin (alfa and beta) or darbepoetin used, (4) a control arm, and (5) reported HQOL using a validated measure. All available SF-36 data underwent meta-analysis
using the weighted mean difference.
Results: Of 231 full texts screened, 11 eligible studies
were identified. The SF-36 was used in 9 trials.
Reporting of these data was generally incomplete. Data
from each domain of the SF-36 were summarized. Statistically significant changes were noted in the physical function (weighted mean difference [WMD], 2.9;
95% confidence interval [CI], 1.3 to 4.5), general
health (WMD, 2.7; 95% CI, 1.3 to 4.2), social function
(WMD, 1.3; 95% CI, −0.8 to 3.4), and mental health
(WMD, 0.4; 95% CI, 0.1 to 0.8) domains. None of the
changes would be considered clinically significant.
Conclusions: Our study suggests that targeting hemoglobin levels in excess of 12.0 g/dL leads to small and not
clinically meaningful improvements in HQOL. This, in
addition to significant safety concerns, suggests that targeting treatment to hemoglobin levels that are in the range
of 9.0 to 12.0 g/dL is preferred.
Arch Intern Med. 2009;169(12):1104-1112
A
Author Affiliations:
Departments of Community
Health Sciences and Medicine
and Centre for Health and
Policy Studies, University of
Calgary, Calgary, Alberta,
Canada (Drs Clement and
Manns); Department of
Medicine, Division of
Nephrology, University of
Alberta, Edmonton
(Drs Klarenbach and Tonelli);
and Institute for Health
Economics, Edmonton, Alberta
(Dr Johnson).
NEMIA IS A COMMON COMplication of chronic kidney disease (CKD) and is
associated with adverse
clinical outcomes and poor
health-related quality of life (HQOL).1-3
Treatment of anemia before the advent of
erythropoietin-stimulating agents (ESAs)
relied on routine blood transfusions. Although the main advantage of treatment
of anemia in CKD with ESAs once focused on preventing the need for blood
transfusions, over time, it has shifted to
encompass other clinical considerations.
Specifically, although the labeling for ESAs
in most countries refers to their ability to
improve anemia and reduce the need for
transfusions, 4 many studies have addressed the use of ESAs at varying doses
and their effect on survival, cardiovascular morbidity, or HQOL.5
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1104
The use of ESAs has become commonplace in most developed countries, and the
debate over their use now principally focuses on the optimal target hemoglobin
level.1,2,5 This debate has intensified over
the past 15 years, with the publication of
several large randomized controlled trials
(RCTs) testing the effect of using ESAs to
For editorial comment
see page 1100
achieve various hemoglobin targets.3,6
Many of these trials compared low to intermediate (hereinafter, low/intermediate) hemoglobin target levels, typically in
the 95 to 11.5 g/dL range, with high hemoglobin target levels, typically higher
than 13.0 g/dL. Perhaps unexpectedly,
many of these RCTs have raised important safety concerns with high hemoglo-
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bin target levels, with findings of
higher rates of adverse events, including mortality and vascular access thrombosis. 7-11 These concerns have led the US Food and Drug
Administration, among other regulatory agencies, to change the labeling for ESAs to target hemoglobin
levels lower than 12.0 g/dL.12 (To
convert hemoglobin to grams per liter, multiply by 10.0.)
Given high baseline mortality
rates and the difficulty in finding
therapies that improve survival in
patients with end-stage renal disease (ESRD),13 and the findings from
the Hemodialysis Study14 and Dialysis Clinical Outcomes Revisited
Study,15 HQOL improvement has become a focus of treatment of CKD.
Broadly, HQOL is defined as the way
a patient feels or functions, aspects
of which can improve after successful treatment of a condition.16 Minimally, measurement of HQOL includes assessment of functional
status, mental health or emotional
well-being, social engagement, and
symptom states.16 Although there are
many different scales that have been
used to measure HQOL, the 36item short-form instrument (SF36) is among the most commonly
applied instrument to measure
HQOL. It comprises 36 questions
that assess 8 domains of HQOL:
physical function, physical role,
pain, general health, vitality, social
function, emotional role, and mental health.17
Despite the safety concerns that
have been associated with normalization of hemoglobin,3,13 knowing
that patients with ESRD who are
treated with hemodialysis have very
poor baseline QOL has led some to
suggest that targeting hemoglobin
levels higher than 12.0 g/dL might
still be reasonable in some patients
with ESRD in an effort to improve
QOL.2,5 A clearer understanding of
the impact of higher-dose ESA on
HQOL will enable rational comparison of putative HQOL benefits with
potential safety issues. In this study,
we aimed to summarize the available data from RCTs on HQOL for
patients treated to different hemoglobin target levels and determine
the magnitude of HQOL differences. Given that most studies that
have measured HQOL in this area
have used the SF-36, we also conducted a meta-analysis of SF-36 data
for all RCTs comparing low/
intermediate and high hemoglobin
target levels.
METHODS
SEARCH STRATEGY
We conducted a comprehensive and exhaustive search to identify all RCTs of
ESA therapy in adults with anemia associated with CKD. No language restrictions were applied. MEDLINE (1966
through December 12, 2006), EMBASE
(1988 through December 12, 2006), all
evidence-based medicine reviews, and a
variety of other gray literature sources
(n = 48) were searched using different
search terms for ESA combined with
CKD search terms (eTable 1, http://www
.archinternmed.com, provides search
strategy used for MEDLINE; strategy
adapted for other search engines).
Each citation or abstract was independently screened by a subject specialist
and 1 other reviewer. Any trial
considered relevant by at least 1
reviewer was retrieved for further
review. The reference lists of included
trials and relevant reviews were also
scanned for pertinent trials. In addition, we contacted ESA manufacturers
in Canada and the authors of included
studies for information about further
studies.
STUDY SELECTION
The full text of each potentially relevant article was independently assessed by 2 reviewers for inclusion in the
review using predetermined eligibility
criteria. Studies were eligible for inclusion if they met the following 5 criteria: (1) it was a parallel RCT design with
at least 30 participants in each treatment group, (2) the population was limited to anemic adults (age ⱖ 18 years)
with CKD (including hemodialysisdependent and nonhemodialysis dependent), (3) epoetin (alfa and beta) or darbepoetin used, (4) the control arm was
either a different agent or hemoglobin
target, or no active treatment (eg, placebo), and (5) the study reported HQOL
using a validated measure defined as one
in which its reliability, internal consistency, and responsiveness had been published in the peer-reviewed literature. Because small studies are unlikely to
publish long-term outcomes or HQOL,
studies with less than 30 participants
were excluded to improve the efficiency of the literature search. Initial dis-
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1105
agreements on study selection were resolved through consensus.
DATA EXTRACTION
From all included studies, data were
extracted on trial characteristics
(country, design, sample size, duration of follow-up, objective, score
according to the criteria of Jadad et
al18 [hereinafter, Jadad score]), participants (age, sex, diabetic status, cardiovascular status, previous hematopoietic hormone use), illness severity
(hemoglobin levels, renal function,
dialytic modality), therapeutic regimens (type, dose, schedule, route of
administration, target hemoglobin
level), control regimens and cointerventions, and HQOL outcomes. Trial
quality was assessed using the Jadad
score.18
Given that the RCTs were conducted over an 18-year period, several
different HQOL measures were used by
the different studies. Moreover, some
studies used disease-specific measures,
and some used generic HQOL measures. As such, we first report qualitatively the results of our systematic
review.
STATISTICAL ANALYSIS
We planned a priori to combine the
results of HQOL measures for trials
that compared the use of ESAs targeting either a low/intermediate hemoglobin target level (ie, a hemoglobin
level of 9.0-12.0 g/dL) or high hemoglobin target level (ie, a hemoglobin
level ⬎12.0 g/dL). The a priori analysis plan was to combine all available
HQOL data. The primary outcome
was the change from baseline HQOL.
Because most HQOL instruments
report continuous data thus, a priori,
the weighted mean difference (WMD)
was to be used for each instrument
separately. However, owing to the
lack of standardized reporting and the
fact that few studies used similar
HQOL scales aside from the SF-36,
only the SF-36 data were suitable for
meta-analysis.
For this analysis, each domain of
the SF-36 was summarized separately.
When combining SF-36 domains for
base case analyses, we included information from all studies in which any
information for any SF-36 domain was
reported. Given that several studies
selectively reported information for
only 1 domain, we completed 2 sensitivity analyses as follows: (1) we combined data only for studies reporting all
domains of the SF-36, and (2) we
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from between-study variation.19 Where
possible, changes in HQOL for each
outcome measure were also compared
with the minimal clinically important
difference (MCID). For the SF-36, we
conservatively considered 5 points to
be the MCID.20,21
differences expected between trials, we
decided a priori to combine results
using a random-effects model. Statistical heterogeneity was quantified using
the I2 statistic. The I2 statistic approximates the percentage of total variation
(within- and between-study) resulting
included all studies in which any SF-36
data were reported; for domains that
were either not reported or reported as
“P⬎.05,” we assumed no change over
time. If there were multiple time points
reported per outcome, we included
only the last time point. Owing to the
RESULTS
2289 Citations identified from
electronic search and
broad screened
INCLUDED STUDIES
2062 Abstracts excluded:
2038 Not relevant
14 Not retrievable
10 No translator available
4 Citations identified from
other sources
Figure 1 shows the flowchart for trial
selection.Fromatotalof2289citations,
231 potentially relevant articles were
retrieved for review. Of these, 220 did
notmeettheselectioncriteriaandwere
excluded. In particular, 23 excluded
articles did not report HQOL, and 3
wereexcludedbecausetheydidnotuse
a validated instrument.7,9,10 There was
substantial initial agreement for study
inclusion (␬=0.86). A total of 11 primary articles met all 5 of the inclusion
criteria.3,6,8,11,13,22-27 Of these, 10 compared a low/intermediate target level
with a high hemoglobin target level,
and 1 compared placebo with a target
level of 9.5 to 11.0 g/dL and a target
level of 11.5 to 13.0 g/dL.22 Although
these target levels overlap our definition of low/intermediate (9.0-12.0
g/dL) and high (⬎12.0 g/dL), we classified the 9.5 to 11.0 g/dL level as low/
intermediate and the 11.5 to 13.0 g/dL
level as high.
231 Potentially relevant
studies retrieved
194 Studies excluded:
36 Not original human research
51 Not an RCT
12 Crossover
1 Children
3 No CKD
11 No relevant comparison
38 Sample size <30
25 Multiple publications
11 No relevant clinical outcome
6 No usable data reported
26 Eligible RCTs excluded:
23 No HQOL reported
3 No validated instrument used
11 Relevant studies
Figure 1. Flowchart of included studies. CKD indicates chronic kidney disease; HQOL, health-related
quality of life; RCT, randomized controlled trial.
Table 1. Included Study Characteristics
High Target Level Group
Low to Intermediate Target Level Group
RI
Follow-up
Jadad
Score a
Target Hb
Level, g/dL
No.
Mean
Age, y
Male, %
Target Hb
Level, g/dL
No.
Mean
Age, y
Male, %
HD
EPO vs EPO
vs placebo
6 mo
5
11.5-13.0
38
43
26
9.5-11.0
40
44
19
HD
HD
PD/HD
Predialysis
Predialysis
HD
Predialysis
Predialysis
Predialysis
Predialysis
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
EPO vs EPO
29 mo
48 wk
48 wk
24 mo
24 mo
96 wk
16 mo
24 mo
9 mo
15 mo
4
4
3
4
5
5
4
4
4
3
13.0-15.0
13.0-14.0
13.5-16.0
12.0-13.0
12.0-14.0
13.5-14.5
13.5
13.0-15.0
13.0-15.0
13.0-15.0
618
70
129
75
85
293
715
301
195
88
65
62
63
53
57
52
66
59
59
58
50
47
67
51
55
60
44
57
58
51
9.0-10.0
9.5-10.5
9.0-12.0
9.0-10.0
9.0-10.5
9.5-11.5
11.3
10.5-11.5
11.0-12.0
10.5-11.5
615
72
124
80
87
294
717
302
194
82
64
60
63
54
57
49
66
59
58
57
48
44
63
42
52
60
46
51
61
50
Study
Population
Canadian
Erythropoietin
Study Group22 b
Besarab et al13 c
Foley et al23
Furuland et al8 d
Roger et al27
Levin et al24
Parfrey et al25
Singh et al3 e
Drüeke et al6
Rossert et al11 f
Ritz et al26
Abbreviations: EPO, erythropoietin; Hb, hemoglobin; HD, hemodialysis; PD, peritoneal dialysis; RI, randomized intervention.
SI conversion factor: To convert hemoglobin to grams per liter, multiply by 10.0.
a The scoring system developed by Jadad et al.18
b The Canadian Erythropoietin Study Group22 also included a placebo arm with 40 patients; mean age, 48 years; 25% were male.
c Terminated early (intended to follow for 3 years): continuation was felt to be unlikely to show benefit and the higher mortality in the high target level group was
not statistically significant compared with the mortality in the low to intermediate target level group.
d Although protocol included predialysis CKD patients, quality of life was only measured in patients undergoing hemodialysis.
e Terminated early (intended to follow for 3 years): there was only a 5% chance that continuation would show benefit; adverse events and quality of life data
were considered.
f Terminated early (intended to follow for 3 years); there were safety concerns surrounding the occurrence of pure red cell aplasia.
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1106
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Table 2. Health-Related Quality-of-Life (HQOL) Outcomes
Time of
Assessment
Study
Canadian
Erythropoietin
Study Group22
Baseline
2 mo
6 mo
Besarab et al13
Baseline and
every 6 mo
Foley et al23
Baseline
24 wk
48 wk
Furuland et al8
Baseline
48 wk
1y
Roger et al27
Baseline
24 mo
Levin et al24
Baseline
Every 6 mo
Reported
HQOL
Instrument
Overall mean change
(1) KDQ
in HQOL instruments (2) SIP
from baseline to 6 mo (3) Time trade-off
Results
Subscale
Low
High
Notes
Physical
Fatigue
Relationships
Depression
Frustration
Global
1.6
1.4 (PLA: 0.4) Statistically significant
0.9
1.1 (PLA: 0.1)
differences between
0.6
0.6 (PLA: 0.1)
placebo and low treatment
0.4
0.7 (PLA: 0.1)
arms in physical, fatigue,
0.0
0.4 (PLA: 0.0)
relationships, and
−5.3
−7.8 (PLA: −2.9) depression
0.02
0.06 (PLA: 0.0)
Overall change per
SF-36
Physical function domain increase of 0.6
Not reported by treatment
percentage point
arm.
increase in hematocrit
Other 7 domains of SF-36
not reported
Overall mean change
(1) KDQ
Physical
1.17
1.10
SF-36 and HUI scores were
in KDQ from baseline (2) SF-36
Fatique
−0.01
0.25
reported as “unchanged
to 48 wk
(3) HUI (mark 2)
Relationships
0.20
−0.07
over time” (not reported
Depression
0.20
0.05
numerically or by treatment
Frustration
0.15
−0.07
arm)
Mean change from
KDQ
Physical
0.25
0.66
Statistically significant
baseline to 48 wk
Fatigue
−0.33
0.16
difference between
Relationships
0.0
0.0
treatment groups for
Depression
−0.40
0.0
physical symptoms and
Frustration
0.0
0.0
depression subscale
Mean change from
(1) Renal QOL profile Global
5
7
No statistically significant
baseline to 24 mo
(2) SF-36
Physical function
−7.3
−4.3
differences between
Physical role
15.8
2.7
treatment arms
Pain
−9.2
−8.2
General health
−4.1
0.9
Vitality
−4.6
−1.0
Social function
−10.9
−5.6
Emotional role
−5.9
5.9
Mental health
−1.0
−0.6
Mean change from
SF-36
Physical function
−9.3
−2.5
No statistically significant
baseline to 24 mo
Physical role
−4.1
−3.9
differences between
Pain
−4.2
−1.0
treatment arms
General health
−4.9
0.3
Vitality
−5.1
−2.7
Social function
−2.5
−4.7
Emotional role
−12.3
−3.7
Mental health
−0.5
1.8
(continued)
TRIAL CHARACTERISTICS
INSTRUMENTS
Table 1 summarizes the character-
A total of 10 instruments were used
to report HQOL in the 11 included
trials. An overview of the measures
used and the minimal clinically important difference cited for each
measure is provided in eTable 2
(http: //www.archinternmed.com).
The most commonly used instrument was the SF-36, administered in
9 of the 11 trials. Reporting of these
data was generally poor. There was
a wide variety of reporting formats,
with some trials reporting baseline
data and others reporting only
change from baseline. Only 5 trials
reported data on all domains and
scales measured.3,8,11,22,27
istics of included trials. The trials
ranged in size from 78 to 1432 patients. Five trials considered patients
with CKD undergoing hemodialysis,
whereas 6 considered those with CKD
who were not. Health-related quality
of life was the specified primary end
pointin2studies.8,22 Otherprimaryend
pointsconsideredweretimetofirstcardiovascular event or death,3,6,13 change
inleftventricularfunction,23-27 andrate
of glomerular filtration rate decline.11
The mean Jadad score was 4, indicating generally high-quality studies. Of
note, 3 of the 12 trials were terminated
early owing to futility (ie, the perception that use of the high hemoglobin
target level was unlikely to have led
to better outcomes if the trial were
completed). Patients were blinded to
the allocated hemoglobin target level
in only 2 of 11 studies.24,25
SUMMARY OF TRIAL
FINDINGS
The findings of each trial are summarized in Table 2. Most trials
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compared the mean change from
baseline in the measured HQOL instrument or domain between the
treatment groups. For studies comparing low/intermediate and high
target level groups, the differences
reported between groups were generally small, were noted on a minority of measured domains, and were
consistently below the cited minimal clinically important differences (eTable 2). In particular, the
magnitude of the between-group differences rarely exceeded the 5-point
threshold commonly considered
clinically important for the SF-36.20,21
META-ANALYSIS
OF SF-36 DOMAINS
Given that the SF-36 was the most
commonly used instrument, we undertook a WMD meta-analysis of each
domain, comparing low/intermediate and high target level hemoglobin
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Table 2. Health-Related Quality-of-Life Outcomes (Continued)
Study
Time of
Assessment
Results
HQOL
Instrument
Subscale
Low
High
Notes
Parfrey et al25
Baseline, 24,
36, 48, 60, 72,
84, and
96 wk
Mean change from
baseline to mean
follow-up value
(1) Functional
Assessment
of Chronic Illness
Therapy
(2) KDQOL
(3) SF-36
Global
Quality of social
interaction
Vitality
−3.21
0.03
−2.31
−1.0
0.8
1.21
Singh et al3
Baseline
36 mo
Mean change from
baseline to 36 mo
(1) KDQ
Linear Analogue
Self-assessment
(2) SF-36
Drüeke et al6
Baseline
1y
2y
Mean change from
baseline to 1 y
SF-36
Rossert et al11
Baseline
9 mo
Study
termination
Percentage with score
of full health
Mean score at 9 mo
(1) Katz Index
of ADLs
(2) SF-36
Baseline
15 mo
Mean change from
baseline to 15 mo
Global
1.1
Energy
15.5
Activity
13.3
Overall QOL
11.9
Physical function
2.1
Physical role
7.5
Pain
2.4
General health
1.8
Vitality
8.2
Social function
3.5
Emotional role
5.9
Mental health
2.4
Physical function
−2.1
Physical role
−6.6
Pain
−1.2
General health
−0.7
Vitality
−3.0
Social function
−2.1
Emotional role
Mental health
95% of patients had a score of 6 (no
limitation in ADLs) at baseline and
9 mo
Physical function
65
Physical role
58
Pain
66
General health
53
Vitality
53
Social function
81
Emotional role
71
Mental health
75
Physical function
−0.3
Physical role
Pain
General health
Vitality
Social function
Emotional role
Mental health
Statistically significantly
higher SF-36 vitality scores
in the high treatment arm
at 24, 36, 48, 60, and 72
wk
No other domains reported.
No significant differences in
KDQOL and FACIT-F
Statistically significant change
in SF-36 emotional role in
high treatment arm.
No statistically significant
change in any other
measure
Ritz et al26
Reported
SF-36
1.6
16.6
15.0
11.2
3.2
6.4
0.4
3.0
10.0
1.3
0.8
1.7
3.5
2.4
3.0
3.9
1.8
2.7
72
68
71
58
59
82
76
76
5.3
Statistically significant 6
domains of SF-36 reported
in high treatment arm
Difference maintained at 2 y
for general health and
vitality domains
2 SF-36 domains not reported
Statistically significantly
higher SF-36 vitality
domain for high treatment
arm
Statistically significant change
in SF-36 general health
domain in the high
treatment arm
Other 7 domains not reported
Abbreviations: ADLs, activities of daily living FACIT-F, Functional Assessment of Chronic Illness Therapy–Fatigue subscale; HUI, Health Utilities Index;
KDQ, kidney disease questionnaire; KDQOL, Kidney Disease Quality of Life; PLA, placebo; QOL, quality of life; SF-36, 36-item short-form instrument; SIP, sickness
impact profile.
groups. To calculate a WMD, either
both baseline and final scores or an
overall mean change is required.
As such, only 4 of the 9 trials that
measured SF-36 reported useable
data (Table 3). However, only the
Correction of Hemoglobin and
Outcomes in Renal Insufficiency
(CHOIR) study group3 reported all 8
domains; the Cardiovascular Risk Reduction in Early Anemia Treatment
With Epoetin Beta (CREATE) study
group6 published 6 domains, whereas
the Anemia Correction in Diabetes
(ACORD) study group26 and Parfrey
et al25 reported only 1 SF-36 domain.
All authors were contacted to obtain
additional data; 2 responded and pro-
vided unpublished data24,27 (Table 3).
Thus, 6 studies, including 3 with complete data on all SF-36 domains, were
included in the meta-analysis.
Figure 2 shows the forest plot of
all reported SF-36 domain data. The
WMDsrangedfrom−3.0(favoringthe
low intermediate target level arm) in
the emotional role domain to 3.2 (favoring the high target level arm) in the
vitality domain. A change that would
beconsideredclinicallysignificantwas
not found in any of the domains
(Table 4). Significant heterogeneity
was found in the physical role
(I2 =68.6%; P=.02), social function
(I2 =72.6%; P=.01), and mental health
(I2 =70.5%; P=.02) domains.
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SENSITIVITY ANALYSES
When only studies reporting all domains of the SF-36 were included,
smaller differences between arms
were noted, with the low/intermediate target level arm being favored
in more domains. When an assumption of no difference in the unreported domains is made, the mean
change in domain scores was similar to the base case.
COMMENT
Although we found small improvements in HQOL in 4 of 8 SF-36 do-
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Table 3. Mean SF-36 Domain Scores by Treatment Arm for Studies That Measured SF-36 Scores and Reported Any Data
for Any SF-36 Domain
Low to Intermediate Target Level Arm
Source
Physical
Function
Roger et al27
Baseline
Final
Change
Levin et al24
Baseline
Final
Change
Parfrey et al25
Baseline
Final
Change
Singh et al3
Baseline
Final
Change
Drüeke et al6
Baseline
Final
Change
Ritz et al26
Baseline
Final
Change
(n=80)
72.4
65.1
−7.3
(n=82)
66.6
57.7
−9.3
(n=294)
NR
NR
NR
(n=717)
42.4
44.5
2.1
(n=302)
NR
NR
−2.1
(n=82)
NR
NR
NR
Physical
Role
Pain
General
Health
Vitality
Social
Function
Emotional
Role
Mental
Health
39.2
55.0
15.8
80.7
71.5
−9.2
49.0
44.9
−4.1
52.8
48.2
−4.6
82.2
71.3
−10.9
25.4
31.3
−5.9
72.1
71.1
−1.0
57.5
51.9
−4.1
65.6
62.1
−4.2
52.5
47.8
−4.9
50.2
45.5
−5.1
78.3
76.3
−2.5
83.1
71.9
−12.2
70.8
70.6
−0.5
NR
NR
NR
NR
NR
NR
NR
NR
NR
54.7
52.4
−2.3
NR
NR
NR
NR
NR
NR
NR
NR
NR
32.5
40.0
7.5
58.0
60.4
2.4
42.6
44.4
1.8
36.6
44.8
8.2
63.7
67.2
3.5
57.4
63.3
5.9
70.2
72.6
2.4
NR
NR
−6.6
NR
NR
NR
NR
NR
−1.2
NR
NR
−0.7
NR
NR
−3.0
NR
NR
NR
NR
NR
−2.1
NR
NR
NR
NR
NR
NR
NR
NR
−0.33
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
High Target Level Arm
Source
Physical
Function
Roger et al27
Baseline
Final
Change
Levin et al24
Baseline
Final
Change
Parfrey et al25
Baseline
Final
Change
Singh et al3
Baseline
Final
Change
Drüeke et al6
Baseline
Final
Change
Ritz et al26
Baseline
Final
Change
(n=750)
63.3
59.0
−4.3
(n=80)
70.3
68.6
−2.5
(n=293)
NR
NR
NR
(n=715)
41.9
45.1
3.2
(n=301)
NR
NR
3.5
(n=88)
NR
NR
NR
Physical
Role
Pain
General
Health
Vitality
Social
Function
Emotional
Role
Mental
Health
46.6
49.3
2.7
71.1
62.9
−8.2
44.1
45.0
0.9
47.2
46.2
−1.0
72.3
66.7
−5.6
31.1
37.0
5.9
73.5
72.9
−0.6
55.4
50.0
−3.9
69.3
68.5
−1.0
54.5
54.6
0.3
54.6
51.7
−2.7
80.7
75.0
−4.7
80.0
74.3
−3.7
69.1
71.2
1.8
NR
NR
NR
NR
NR
NR
NR
NR
NR
54.1
55.3
1.2
NR
NR
NR
NR
NR
NR
NR
NR
NR
31.9
38.3
6.4
57.8
59.2
0.4
41.3
43.3
3.0
35.2
45.2
10.0
63.7
65.0
1.3
57.2
58.6
0.8
69.6
71.3
1.7
NR
NR
2.4
NR
NR
NR
NR
NR
3.0
NR
NR
3.9
NR
NR
1.8
NR
NR
NR
NR
NR
2.7
NR
NR
NR
NR
NR
NR
NR
NR
5.33
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Abbreviations: NR, nonreported data; SF-36, 36-item short-form instrument.
mains, the changes were well below
the threshold for a minimal clinically
important difference of a 5-point
change(allwere⬍3.2pointsona100point scale).21 It is often argued that
targeting a high hemoglobin target
level would be most likely to have an
impact on vitality scores, the domain
that captures the sentiment of “having more energy.” However, vitality
(REPRINTED) ARCH INTERN MED/ VOL 169 (NO. 12), JUNE 22, 2009
1109
scores were only 3.2 (95% confidence
interval [CI], 1.87-4.44) points higher
inthehightargetlevelgroupcompared
with the low/intermediate target level
group. Higher scores were observed
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Source
WMD (95% CI)
Physical Function
Roger et al27
% Weight
3.00 (0.02 to 5.98)
6.80 (–0.27 to 13.87)
1.10 (–1.35 to 3.55)
5.54 (2.04 to 9.04)
2.91 (1.29 to 4.53)
29.63
5.24
43.69
21.44
100
Physical Role
Roger et al27
Levin et al24
Singh et al3
Drüeke et al6
Subtotal (I 2 = 68.6%, P = .02)
–13.10 (–26.10 to 0.10)
0.20 (–12.81 to 13.21)
–1.10 (–5.45 to 3.25)
8.97 (1.43 to 16.50)
0.28 (–3.20 to 3.77)
7.19
7.18
64.25
21.38
100
Pain
Roger et al27
Levin et al24
Singh et al3
Subtotal (I 2 = 52.6%, P = .12)
1.00 (0.01 to 1.99)
3.20 (–4.59 to 10.99)
–2.00 (–4.84 to 0.84)
0.71 (–0.22 to 1.64)
87.85
1.42
10.72
General Health
Roger et al27
Levin et al24
Singh et al3
Drüeke et al6
Ritz et al26
Subtotal (I 2 = 30.2%, P = .22)
5.00 (0.04 to 9.96)
5.22 (–0.82 to 11.26)
1.20 (–0.72 to 3.12)
4.21 (1.22 to 7.21)
5.66 (–0.44 to 11.76)
2.71 (1.26 to 4.15)
8.50
5.73
56.84
23.31
Vitality
Roger et al27
Parfrey et al25
Levin et al24
Singh et al3
Drüeke et al6
Subtotal (I 2 = 0.0%, P = .66)
3.60 (0.03 to 7.17)
3.52 (1.31 to 5.73)
2.40 (–4.38 to 9.18)
1.80 (–0.51 to 4.11)
4.53 (1.67 to 7.39)
3.17 (1.89 to 4.44)
12.74
33.32
3.54
30.57
19.84
100
Social Function
Roger et al27
Levin et al24
Singh et al3
Drüeke et al6
Subtotal (I 2 = 72.6%, P = .01)
5.30 (0.04 to 10.56)
–2.20 (–10.21 to 5.81)
–2.20 (–5.41 to 1.01)
4.85 (1.08 to 8.62)
1.30 (–0.84 to 3.44)
16.51
7.11
44.31
32.07
100
0.00 (–12.99 to 12.99)
8.50 (–4.73 to 21.73)
–5.10 (–10.09 to 0.11)
–3.01 (–7.41 to 1.38)
11.44
11.04
77.51
100
0.40 (0.00 to 0.80)
2.30 (–1.75 to 6.35)
–0.70 (–2.60 to 1.20)
4.80 (1.77 to 7.82)
0.44 (0.06 to 0.83)
93.43
0.90
4.07
1.60
100
Levin et al24
Singh et al3
Drüeke et al6
Subtotal (I 2 = 44.8%, P = .14)
Emotional Role
Roger et al27
Levin et al24
Singh et al3
Subtotal (I 2 = 47.2%, P = .15)
Mental Health
Roger et al27
Levin et al24
Singh et al3
Drüeke et al6
Subtotal (I 2 = 70.5%, P = .02)
–26.1
0
Favors Low Hemoglobin
100
5.62
100
26.1
Favors High Hemoglobin
Figure 2. Forest plot of all reported 36-item short-form instrument domain data. CI indicates confidence interval; WMD, weighted mean difference.
inthehighhemoglobintargetlevelarm
in 3 domains (vitality, physical function, and general health) across all
studies. However, again, the improvements were very small and would not
be regarded as a clinically meaningful improvement (2.9 for physical
function, 2.7 for general health, and
3.2 for vitality).
Although improvements in
HQOL are commonly cited as a rea-
son to target a higher hemoglobin
level, numerous limitations of the
existing literature should be noted.
Health-related quality of life was not
reported in 26 of 37 identified RCTs,
and among the 11 RCTs that did
measure HQOL, 9 used the SF-36,
although only 1 study3 reported full
data on the SF-36 (although 2 additional authors provided full SF-36
data24,27). Given that patient blind-
(REPRINTED) ARCH INTERN MED/ VOL 169 (NO. 12), JUNE 22, 2009
1110
ing is potentially difficult in this type
of study, and that 9 of 11 studies
were open label, it is possible that
partial blinding of patients to their
assigned group might have contributed to the small changes noted in
these measures.
Our findings highlight the importance of distinguishing statistical significance from clinical significance. The minimal clinically
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Table 4. Results of Meta-analysis and Sensitivity Analyses
Scenario
Base Case:
Using All Available Data
Domain
Physical function
Physical role
Pain
General health
Vitality
Social function
Emotional role
Mental health
Only Using Studies That Reported
All SF-36 Domains
Assuming No Change in Unreported
SF-36 Domains
Studies, No.
WMD (95% CI)
Studies, No.
WMD (95% CI)
Studies, No.
WMD (95% CI)
4
4
3
5
5
4
3
4
2.9 (1.3 to 4.5)
0.3 (−3.2 to 3.8)
0.7 (−0.2 to 1.6)
2.7 (1.3 to 4.2)
3.2 (1.9 to 4.4)
1.3 (−0.8 to 3.4)
−3.0 (−7.4 to 1.4)
0.4 (0.1 to 0.8)
3
3
3
3
3
3
3
3
2.2 (0.4 to 4.0)
−2.1 (−6.0 to 1.9)
0.7 (−0.2 to 1.6)
2.0 (0.3 to 3.7)
2.3 (0.5 to 4.2)
−0.4 (−3.0 to 2.2)
−3.0 (−7.4 to 1.4)
0.4 (−0.0 to 0.8)
6
6
6
6
6
6
6
6
1.8 (0.5 to 3.1)
0.1 (−1.7 to 1.9)
0.5 (−0.7 to 1.4)
1.9 (0.7 to 3.1)
3.0 (1.8 to 4.3)
0.6 (−0.9 to 2.1)
−0.4 (−2.0 to 1.2)
0.4 (0.1 to 0.8)
Abbreviations: CI, confidence interval; SF-36, 36-item short-form instrument; WMD, weighted mean difference.
important difference is defined as the
smallest amount of benefit that patients can recognize and value.28
Thus, a clinically important change
is relevant and important to patients, whereas a statistical change
is simply a detectable change that
may or not be noticeable to patients. Given that most of these trials
were designed to measure differences in clinical outcomes, including survival, these RCTs may have
been powered to detect statistically
significant changes in measurements that are of no clinical relevance to patients.
If multiple time points were measured, our analysis considered the
latest time point reported. For some
domains of the SF-36, particularly
vitality, a short-term improvement
may be observed at the other time
points, such as 6 or 12 months.
However, the clinical relevance of
short-term small improvements that
are not sustained over longer periods of follow-up is unknown.
The use of ESAs has considerably altered the treatment of patients with anemia related to CKD.
Although the initial use of ESAs was
aimed at preventing the requirement for transfusion, much of the
subsequent research around them
has focused on determining whether
using them to achieve a high hemoglobin target level is associated with
clinical benefit. Despite concern regarding the safety of ESAs when targeted to a high hemoglobin level,
some guidelines continue to advocate that hemoglobin target levels in
excess of 12.0 g/dL may still be reasonable for selected patients; this
seems to be the result of expected improvements in HQOL.2,5 Our analyses do not substantiate the basis for
these guidelines. Our results continue to be very relevant because recent reports confirm that nearly 30%
of American patients who undergo
hemodialysis have a hemoglobin level
in excess of 12.0 g/dL.29
There were several strengths and
limitations of our study. We systematically reviewed the literature, including contacting manufacturers, to
ensure that we identified all relevant RCTs. Despite this, it should
be noted that many of the RCTs did
not measure HQOL, and among
those that did, selective reporting occurred, resulting in an incomplete
data set with which to rigorously assess HQOL. To account for this, we
conducted 2 sensitivity analyses, the
results of which suggest that our base
case analysis may overestimate the
actual treatment effect.
Our findings and the strength of
our conclusions are limited by the
available evidence. Given that HQOL
is one of the major theoretical benefits of ESA, the selective reporting
of certain domains, the variation in
instruments used to measure HQOL,
and the lack of directly measured
data on utility are major weaknesses of the available literature.
However, we were able to include
some unpublished data supplied by
the authors of the original studies,
thereby minimizing some of the reporting bias that may be present.
Last, there are methodological
limitations with meta-analyses. However, we conducted the review according to a prespecified protocol,
(REPRINTED) ARCH INTERN MED/ VOL 169 (NO. 12), JUNE 22, 2009
1111
used a well-defined comprehensive
literature search strategy designed by
an expert librarian, performed quality assessment and data extraction
with duplicate reviewers, and used
rigorous statistical methodology that
would be expected to reduce the extent of any bias.
Erythropoietin-stimulating agents
are an important aspect of treatment for patients with CKD, especially for those undergoing hemodialysis or who are at risk of
requiring blood transfusion without treatment. The cited goal of treatment to a higher hemoglobin target
level is often to improve HQOL.
However, our systematic review revealed a weak evidence base in support of that strategy, with poorly reported data and only 2 RCTs that
examined HQOL as the primary
study end point. Our study suggests that targeting a hemoglobin
level in excess of 12.0 g/dL leads to
small and not clinically meaningful
improvements in HQOL. This, in addition to considerable safety concerns, would suggest that targeting
treatment to hemoglobin levels that
are in the range of 9.0 to 12.0 g/dL
is reasonable.
Accepted for Publication: February 7, 2009.
Correspondence: Braden J. Manns,
MD,MSc,DepartmentofNephrology,
Foothills Medical Centre, 1403 29th
St NW, Calgary, AB T2N 2T9, Canada
(braden.manns@calgaryhealthregion
.ca).
Author Contributions: Study concept and design: Clement, Klarenbach, Tonelli, Johnson, and Manns.
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Analysis and interpretation of data:
Clement, Klarenbach, Tonelli, and
Manns. Drafting of the manuscript:
Clement and Manns. Critical revision of the manuscript for important
intellectual content: Clement, Klarenbach, Tonelli, Johnson, and Manns.
Statistical analysis: Clement and
Tonelli. Obtained funding: Manns.
Administrative, technical, and material support: Clement and Johnson.
Study supervision: Klarenbach,
Tonelli, and Manns. Methodologic
HQOL expertise: Johnson.
Financial Disclosure: None reported.
Funding/Support: Dr Clement is supported by a postdoctoral fellowship
award from the Canadian Health Services Research Foundation and from
the Alberta Heritage Foundation for
Medical Research (AHFMR). Dr
Johnson holds a Canada Research
Chair in Diabetes Health Outcomes
and holds a Health Scholar Award
from the AHFMR. Drs Manns and
Tonelli are supported by a Canadian
Institutes for Health Research (CIHR)
New Investigator Award. Drs Tonelli
and Klarenbach are supported by
Population Health Investigator awards
from the AHFMR. Dr Klarenbach is
supported by a Scholarship Award
from the Kidney Foundation of
Canada.
Additional Information: Two
eTables are available at http://www
.archinternmed.com.
Additional Contributions: Tamara
Durec, MLIS, designed the comprehensive literature search strategy.
We gratefully acknowledge the researchers who provided unpublished SF-36 data.
REFERENCES
1. Barrett BJ, Fenton SS, Ferguson B, et al; Canadian Society of Nephrology. Clinical practice guidelines for the management of anemia coexistent with
chronic renal failure. J Am Soc Nephrol. 1999;
10(suppl 13):S292-S296.
2. KDOQI; National Kidney Foundation. KDOQI clinical practice guidelines and clinical practice recommendations for anemia in chronic kidney disease.
Am J Kidney Dis. 2006;47(5)(suppl 3):S11-S145.
3. Singh AK, Szczech L, Tang KL, et al; CHOIR Investigators. Correction of anemia with epoetin alfa
in chronic kidney disease. N Engl J Med. 2006;
355(20):2085-2098.
4. US Food and Drug Administration. Procrit label,
Epogen label. 2007. http://www.fda.gov/cder/foi
/label/2007/103234s5122lbl.pdf. Accessed August 14, 2008.
5. KDOQI. KDOQI clinical practice guideline and clinical practice recommendations for anemia in chronic
kidney disease: 2007 update of hemoglobin target.
Am J Kidney Dis. 2007;50(3):471-530.
6. Drüeke TB, Locatelli F, Clyne N, et al; CREATE Investigators. Normalization of hemoglobin level in
patients with chronic kidney disease and anemia.
N Engl J Med. 2006;355(20):2071-2084.
7. Bahlmann J, Schoter KH, Scigalla P, et al. Morbidity and mortality in hemodialysis patients with
and without erythropoietin treatment: a controlled study. Contrib Nephrol. 1991;88:90-106.
8. Furuland H, Linde T, Ahlme´n J, Christensson AJ,
Strömbom A, Danielson U. A randomized controlled trial of haemoglobin normalization with epoetin alfa in pre-dialysis and dialysis patients.
Nephrol Dial Transplant. 2003;18(2):353-361.
9. Gouva C, Nikolopoulos P, Ioannidis JPA, Siamopoulos KC. Treating anemia early in renal failure
patients slows the decline of renal function: a randomized controlled trial. Kidney Int. 2004;66
(2):753-760.
10. Revicki DA, Brown RE, Feeny DH, et al. Healthrelated quality of life associated with recombinant human erythropoietin therapy for predialysis chronic renal disease patients. Am J Kidney
Dis. 1995;25(4):548-554.
11. Rossert J, Levin A, Roger SD, et al. Effect of early
correction of anemia on the progression of CKD.
Am J Kidney Dis. 2006;47(5):738-750.
12. Ongoing safety review erythropoiesis-stimulating
agents (ESAs) epoetin alfa (marketed as Procrit,
Epogen) [and] darbepoetin alfa (marketed as
Aranesp): update. US Food and Drug Administration. http://www.fda.gov/cder/drug/infopage/RHE
/default.htm. Accessed August 7, 2008.
13. Besarab A, Bolton WK, Browne JK, et al. The effects of normal as compared with low hematocrit values in patients with cardiac disease who
are receiving hemodialysis and epoetin. N Engl J
Med. 1998;339(9):584-590.
14. Eknoyan G, Beck GJ, Cheung AK, et al; Hemodialysis (HEMO) Study Group. Effect of dialysis dose
and membrane flux in maintenance hemodialysis.
N Engl J Med. 2002;347(25):2010-2019.
15. Suki WN, Zabaneh R, Cangiano JL, et al. Effects
of sevelamer and calcium-based phosphate binders on mortality in hemodialysis patients. Kidney
Int. 2007;72(9):1130-1137.
16. Jaeschke R, Singer J, Guyatt G. Measurement of
health status: ascertaining the minimal clinically
(REPRINTED) ARCH INTERN MED/ VOL 169 (NO. 12), JUNE 22, 2009
1112
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
WWW.ARCHINTERNMED.COM
©2009 American Medical Association. All rights reserved.
Downloaded From: https://jamanetwork.com/ on 09/09/2014
important difference. Control Clin Trials. 1989;
10(4):407-415.
Ware JE Jr, Sherbourne CD. The MOS 36-item
short-form health survey (SF-36), I: conceptual
framework and item selection. Med Care. 1992;
30(6):473-483.
Jadad AR, Moore RA, Carroll D, et al. Assessing
the quality of reports of randomized clinical trials:
is blinding necessary? Control Clin Trials. 1996;
17(1):1-12.
Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21
(11):1538-1558.
Wyrwich KW, Spertus JA, Kroenke K, Tierney WM,
Babu AN, Wolinsky FD; Heart Disease Expert Panel.
Clinically important differences in health status for
patients with heart disease: an expert consensus
panel report. Am Heart J. 2004;147(4):615-622.
Wyrwich KW, Tierney WM, Babu AN, Kroenke K,
Wolinsky FD. A comparison of clinically important differences in health-related quality of life for
patients with chronic lung disease, asthma, or heart
disease. Health Serv Res. 2005;40(2):577-591.
Canadian Erythropoietin Study Group. Association between recombinant human erythropoietin
and quality of life and exercise capacity of patients receiving haemodialysis. BMJ. 1990;300
(6724):573-578.
Foley RN, Parfrey PS, Morgan J, et al. Effect of
hemoglobin levels in hemodialysis patients with
asymptomatic cardiomyopathy. Kidney Int. 2000;
58(3):1325-1335.
Levin A, Djurdjev O, Thompson C, et al. Canadian randomized trial of hemoglobin maintenance to prevent or delay left ventricular mass
growth in patients with CKD. Am J Kidney Dis.
2005;46(5):799-811.
Parfrey PS, Foley RN, Wittreich BH, Sullivan DJ, Zagari MJ, Frei D. Double-blind comparison of full and
partial anemia correction in incident hemodialysis
patients without symptomatic heart disease. J Am
Soc Nephrol. 2005;16(7):2180-2189.
Ritz E, Laville M, Bilous RW, et al; Anemia Correction in Diabetes Study Investigators. Target level for
hemoglobin correction in patients with diabetes and
CKD: primary results of the Anemia Correction in
Diabetes (ACORD) Study. Am J Kidney Dis. 2007;
49(2):194-207.
Roger SD, McMahon LP, Clarkson A, et al. Effects of early and late intervention with epoetin alpha on left ventricular mass among patients with
chronic kidney disease (stage 3 or 4): results of
a randomized clinical trial. J Am Soc Nephrol. 2004;
15(1):148-156.
Barrett B, Brown D, Mundt M, Brown R. Sufficiently important difference: expanding the framework of clinical significance. Med Decis Making.
2005;25(3):250-261.
Collins AJ, Brenner RM, Ofman JJ, et al. Epoetin alfa
use in patients with ESRD: an analysis of recent US
prescribing patterns and hemoglobin outcomes. Am
J Kidney Dis. 2005;46(3):481-488.