Quality of Life and Outcomes in African Americans with CKD

Abstract

Low health-related quality of life (HRQOL) has been associated with increased risk for hospitalization and death in ESRD. However, the relationship of HRQOL with outcomes in predialysis CKD is not well understood. We evaluated the association between HRQOL and renal and cardiovascular (CV) outcomes in 1091 African Americans with hypertensive CKD enrolled in the African American Study of Kidney Disease and Hypertension (AASK) trial and cohort studies. Outcomes included CKD progression (doubling of serum creatinine/ESRD), CV events/CV death, and a composite of CKD progression or death from any cause (CKD progression/death). We assessed HRQOL, including mental health composite (MHC) and physical health composite (PHC), using the Short Form-36 survey. Cox regression analyses were used to assess the relationship between outcomes and five-point decrements in MHC and PHC scores using measurements at baseline, at the most recent annual visit (time-varying), or averaged from baseline to the most recent visit (cumulative). During approximately 10 years of follow-up, lower mean PHC score was associated with increased risk of CV events/CV death and CKD progression/death across all analytic approaches, but only time-varying and cumulative decrements were associated with CKD progression. Similarly, lower mean MHC score was associated with increased risk of CV events/CV death regardless of analytic approach, while only time-varying and cumulative decrements in mean MHC score was associated with CKD progression and CKD progression or death. In conclusion, lower HRQOL is associated with a range of adverse outcomes in African Americans with hypertensive CKD.

Full text

CLINICAL RESEARCH www.jasn.org
Quality of Life and Outcomes in African Americans
with CKD
Anna Porter,* Michael J. Fischer,*
†
Xuelei Wang,
‡
Deborah Brooks,
§
Marino Bruce,
|
Jeanne Charleston,
¶
William H. Cleveland,** Donna Dowie,
††
Marquetta Faulkner,
‡‡
Jennifer Gassman,
‡
Leena Hiremath,
§§
Cindy Kendrick,
‡
John W. Kusek,
||
Keith C. Norris,
¶¶
Denyse Thornley-Brown,*** Tom Greene,
†††
and James P. Lash,* for the AASK Study Group
*Department of Medicine, University of Illinois Hospital and Health Sciences System and Jesse Brown Veterans Affairs
Medical Center, Chicago, Illinois;
†
Center for Management of Complex Chronic Care, Edward Hines Jr. Veterans
Affairs Hospital, Hines, Illinois;
‡
Department of Biostatistics and Epidemiology, Cleveland Clinic Foundation,
Cleveland, Ohio;
§
Department of Medicine, Medical University of South Carolina, Charleston, South Carolina;
|
Jackson State University and University of Mississippi Medical Center, Center for Health of Minority Males, Jackson,
Mississippi;
¶
Department of Medicine, Johns Hopkins University, Baltimore, Maryland; **Multidisciplinary Research
Center, Morehouse School of Medicine, Atlanta, Georgia;
††
Department of Medicine, Columbia University Medical
Center at Harlem Hospital, New York, New York;
‡‡
Department of Medicine, Meharry Medical College, Nashville,
Tennessee;
§§
Department of Medicine, Ohio State University Medical Center, Columbus, Ohio;
||
National Institute of
Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland;
¶¶
Department of
Medicine, Charles R. Drew University, Los Angeles, California; ***Department of Medicine, University of Alabama at
Birmingham, Birmingham, Alabama; and
†††
Department of Medicine, University of Utah, Salt Lake City, Utah
ABSTRACT
Low health-related quality of life (HRQOL) has been associated with increased risk for hospitalization and
death in ESRD. However, the relationship of HRQOL with outcomes in predialysis CKD is not well
understood. We ev aluated the association between H RQOL and renal and cardiovascular ( CV) outcomes in
1091 African Americans with hypertensive CKD enrolled in the African American Study of Kidney Disease
and Hypertension (AASK) trial and cohort studies. Outcomes included CKD progression (doubling of
serum creatinine/ESRD), CV events/CV death, and a composite of CKD progression or death from any
cause (CKD progression/death). We assessed HRQOL, including mental health composite (MHC) and
physical health composite (PHC), using the Short Form-36 survey. Cox regression analyses were used to
assess the relationship between outcomes and five-point decrements in MHC and PHC scores using
measurements at baseline, at the most recent annual visit (time-varying), or averaged from baseline to the
most recent visit (cumulative). During approximately 10 years of follow-up, lower mean PHC score was
associated with increased risk of CV events/CV death and CKD progression/death across all analytic
approaches, but only time-varying and cumulative decrements were associated with CKD progression.
Similarly, lower mean MHC score was associated with increased risk of CV events/CV death regardless of
analytic approach, while only time-varying and cumulative decrements in mean MHC score was associated
with CKD progression and CKD progression or death. In conclusion, lower HRQOL is associated with a
range of adverse outcomes in African Americans with hypertensive CKD.
J Am Soc Nephrol 25: 1849–1855, 2014. doi: 10.1681/ASN.2013080835
Received August 6, 2013. Accepted November 1, 2013.
Published online ahead of print. Publication date available at
www.jasn.org.
Correspondence: Dr. Anna Porter, Section of Nephrology, De-
partment of Medicine, 820 S. Wood Street (M/C 793), Chicago, IL
60612. Email: aporte3@uic.edu
Copyright © 2014 by the American Society of Nephrology
J Am Soc Nephrol 25: 1849–1855, 2014 ISSN : 1046-6673/2508-1849 1849
CLINICAL RESEARCH

Health-related quality of life (HRQOL) is diminished in
patients with CKD and those with ESRD receiving hemodi-
alysis compared with healthy individuals.
1–3
In patients
undergoing maintenance hemodialysis, low HRQOL is asso-
ciated with a greater inflammatory state, poor nutritional sta-
tus, increased hospitalization, and higher mortality.
4–8
Although the relationship between HRQOL and adverse out-
comes has been well studied in patients treated with hemodi-
alysis,
4,6,7
much less is known about the effect of HRQOL on
patients with predialysis CKD.
9–11
One exception is a small
Taiwanese study of patients with CKD that found low baseline
HRQOL scores to be associated with an increased risk of ESRD
and death. However, similar studies are lacking in diverse CKD
populations in the United States.
10
Compared with whites, African Americans have a higher
prevalence of CKD
12
and are at increased risk for ESRD.
13
Despite the magnitude of this health problem, HRQOL in
this population has not been well studied. Prior studies have
examined HRQOL among a cohort of African Americans with
CKD enrolled in a randomized clinical trial of two levels of BP
control targets and three antihypertensive drug regimens, the
African American Study of Kidney Disease and Hypertension
(AASK) trial. A cross-sectional analysis of African Americans
with hypertensive CKD enrolled in the AASK trial reported
that HRQOL scores, particularly the physical domain, were
lower than the general population mean.
14
However, the in-
fluence of HRQOL on clinical outcomes among this high-risk
population is unknown.
To improve our understanding of the influence of HRQOL
on health outcomes in adults with CKD, we examined the
association between HRQOL and CKD progression, cardio-
vascular (CV ) events, and all-cause dea th in a cohort of African
Americans with hypertensive CKD with over 10 years of
follow-up in the AASK trial and cohort studies.
RESULTS
Participants and Characteristics
Patients completed the Medical Outcomes Study 36-Item
Short Form (SF-36) quality of life (QOL) instrument at
baseline and annual visits. At baseline, 1088 of 1094 partic-
ipants (99.5%) had a mental health composite (MHC) score
(mean baseline MHC score, 47.7611.4). A total of 1085 of
1094 participants (99.2%) had a physical health composite
(PHC) score (mean baseline PHC score, 43.5610.9). Detailed
baseline demographic and clinical characteristics of the cohort
have been reported elsewhere.
14
In brief, at baseline, the mean
age6SD was 54.6610.7 years, 39% of patients were female,
the mean eGFR was 47.5613.9 ml/min per m
2
, and the me-
dian protein-to-creatinine ratio was 0.08 g/g.
Cumulative Incidence and Rates of Outcomes
During 8.8–12.2 years of follow-up, the numbers of CV events/
CV deaths, CKD progression events, and CKD progression
events/deaths were 223, 419, and 563, respectively. Patients
were censored at death. The rates of both CV events/CV death
and CKD progression/death were significantly higher in par-
ticipants with PHC scores in the lowest quartile than in those
with scores in the highest quartile (4.04 versus 2.21/100
person-years for CV events and 8.92 versus 6.14/100 person-
years for CKD progression/death) (Table 1). In contrast, the
rates for CKD progression did not differ significantly by PHC
quartiles (P.0.05). Moreover, none of the outcome rates varied
significantly by MHC quartiles (P.0.05) (Table 1). However,
an overall trend toward higher event rates in the lower quartiles
of PHC and MHC was observed.
Association between MHC Scores and Outcomes
In analyses of baseline, time-varying, and cumulative MHC
scores (Table 2), we observed that for each five-point decre-
ment in MHC, the risk for CV event/CV death was signifi-
cantly increased (hazard ratios [HRs], 1.08, 1.13, and 1.13,
respectively; P,0.05) after adjustment for other important
factors. Similarly, in fully adjusted analyses, both lower
time-varying and cumulative MHC score was associated
with CKD progression (for both: HR, 1.07; P,0.05) and the
composite outcome of CKD progression/death (HR, 1.09 and
1.08, respectively; P,0.05 for both) but not baseline score.
Association between PHC Scores and Outcomes
Lower PHC score was associated with increased risk for CV
events/CV death (Tables 3 and 4). In fully adjusted analyses,
the lowest baseline PHC quartile was associated with almost a
2-fold higher risk of CV events/CV death compared with the
highest quartile (HR, 1.94; P,0.05) (Table 4). For each five-
point decrement in time-varying and cumulative PHC scores,
the risk for the composite CV event increased, with HRs of
1.19 and 1.21, respectively (P,0.001) (Table 3). In fully ad-
justed analysis, both lower time-varying and cumulative PHC
scores were associated with increased risk of CKD progression
(HR, 1.12 and 1.10, respectively; P,0.05 for both), but base-
line PHC score was not. For each five-point decrease in base-
line, time-varying, and cumulative PHC scores, risk for the
composite outcome of CKD progression/death was increased,
with HRs of 1.06, 1.15, and 1.13 in fully adjusted analyses,
respectively (P,0.05).
DISCUSSION
HRQOL is an important patient-centered outcome, and poor
HRQOL is associated with adverse outcomes in a wide range of
chronic diseases, including ESRD.
4,5
Ours is the largest pro-
spective study of QOL in patients with predialysis CKD.
Among an exclusively African American cohort, we found
that decrements in summary scores of the mental and physical
components of the SF-36 (MHC and PHC) were consistently
associated with increased risk of CV events/CV death across
multiple methods of analysis. In addition, we found that lower
1850 Journal of the American Society of Nephrology J Am Soc Nephrol 25: 1849–1855, 2014
CLINICAL RESEARCH www.jasn.org

PHC and MHC scores were associated with CKD progression
in several analytic approaches (time-varying and cumulative
analyses).
Because CVD is a major cause of death and morbidity in
patients with CKD, a better understanding of the association
between HRQOL and CV outcomes is critically important.
15
The observed association between lower MHC and PHC
scores and an increased risk of CV events may be related to
several factors. As noted in studies of depression, poor mental
health may be associated with a range of physiologic abnor-
malities that contribute to CVD, including changes in platelet
function, dysregulation of the autonomic nervous system and
hypothalamic-pituitary-adrenal axis, endothelial dysfunction,
and inflammation.
16
The factors underlying the association
between poor physical health and CV outcomes are less c lear.
Similar to our findings, poor physical health has been shown
to be an independent predictor of adverse outcomes both in
the general population and in patients with ESRD.
17
Poor self-
reported physical health may be a proxy for significantly
greater disease burden, which may increase risk for adverse
CV outcomes. Alternatively, low PHC as well as MHC scores
may each be associated with poor self-care, resulting in non-
adherence to treatment regimens for CVD or its risk factors,
thereby increasing the risk of adverse CVD outcomes.
18
We also observed a relationship between worse MHC and
PHC scores and the ris kof C KD progression, although findings
varied by analytic approach. Because risk factors for CV events
and CKD progression risk are closely related,
19
it is reasonable
to speculate that the potential mechanisms discussed above
regarding the association between HRQOL and CV outcomes
could also potentially explain the association between HRQOL
and CKD progression. Alternatively, reverse causality may un-
derlie the stronger observed relationship between CKD pro-
gression and time-varying and cumulative HRQOL scores in
contrast to baseline scores. Mental and physical disease burden
may worsen in patients with declining kidney function, espe-
cially as they progress to ESRD.
2
Similar to our findings, in a
cohort of 423 Taiwanese patients with CKD, Tsai et al. ob-
served an association between low HRQOL and increased
rates of ESRD and death.
10
In contrast to our findings, they
Table 1. Cumulative incidence and rate of renal and cardiovascular events in MHC and PHC quartiles
Variable Patients (n)
CV Events/CV Deaths Doubling of Serum Creatinine/ESRD CKD Progression/Death
Events, n(%) Rate/100
Person-Years Events, n(%) Rate/100
Person-Years Events, n(%) Rate/100
Person-Years
By MHC quartiles
,40 268 58 (21.64) 3.62 117 (43.66) 6.74 153 (57.09) 8.81
40–50 255 56 (21.96) 3.43 93 (36.47) 5.00 125 (49.02) 6.72
50–57 276 56 (20.29) 3.21 96 (34.78) 5.01 135 (48.91) 7.04
.57 289 53 (18.34) 2.67 113 (39.10) 5.36 150 (51.90) 7.11
By PHC quartiles
,34 253 59 (23.32) 4.04 108 (42.69) 6.65 145 (57.31) 8.92
34–46 274 79 (28.83) 4.75 109 (39.78) 5.70 148 (54.01) 7.74
46–53 277 40 (14.44) 2.18 104 (37.55) 5.36 136 (49.10) 7.01
.53 281 44 (15.66) 2.21 97 (34.52) 4.55 131 (46.62) 6.14
Table 2. Association between MHC score and outcomes
Model CV Events/CV Deaths Doubling of Serum Creatinine/ESRD Progression of CKD/Death
HR (95% CI)
a
PValue HR (95% CI)
a
PValue HR (95% CI)
a
PValue
Baseline MHC (223 events/1088 patients) (419 events/1088 Patients) (563 events/1088 patients)
Model 1 1.08 (1.01 to 1.14) 0.02 1.05 (1.01 to 1.10) 0.03 1.05 (1.01 to 1.09) 0.01
Model 2 1.10 (1.03 to 1.16) 0.003 1.02 (0.97 to 1.06) 0.43 1.03 (0.99 to 1.07) 0.11
Model 3 1.08 (1.01 to 1.15) 0.02 1.01 (0.97 to 1.06) 0.55 1.02 (0.98 to 1.07) 0.24
Time-varying MHC (224 events/1093 patients) (422 events/1094 patients) (567 events/1094 patients)
Model 1 1.13 (1.06 to 1.20) ,0.001 1.10 (1.05 to 1.15) ,0.001 1.11 (1.07 to 1.15) 0.000
Model 2 1.14 (1.07 to 1.21) ,0.001 1.08 (1.04 to 1.13) ,0.001 1.10 (1.06 to 1.15) 0.000
Model 3 1.13 (1.06 to 1.20) ,0.001 1.07 (1.02 to 1.12) 0.01 1.09 (1.05 to 1.13) 0.000
Cumulative MHC (224 events/1093 patients) (422 events/1094 patients) (567 events/1094 patients)
Model 1 1.13 (1.05 to 1.21) 0.001 1.11 (1.05 to 1.16) ,0.001 1.11 (1.06 to 1.16) 0.000
Model 2 1.15 (1.07 to 1.24) ,0.001 1.08 (1.02 to 1.13) 0.01 1.09 (1.04 to 1.14) 0.000
Model 3 1.13 (1.05 to 1.22) 0.001 1.07 (1.01 to 1.13) 0.02 1.08 (1.03 to 1.14) 0.001
Model 1: adjusted for randomized group; model 2: model 1 plus adjustment for age, sex, baseline eGFR; model 3: model 2 plus adjustment for age, sex, baseline
eGFR, urinary protein-to-creatinine ratio and history of CVD. 95% CI, 95% confidence interval.
a
HRs expressed as a 5-point decrement in MHC score.
J Am Soc Nephrol 25: 1849–1855, 2014 Quality of Life and Outcomes 1851
www.jasn.org CLINICAL RESEARCH

found that baseline measures of HRQOL were predictive of
progression to ESRD. This discrepancy may relate to differ-
ences in study populations, HRQOL instruments, and follow-
up time.
Because we did not follow participants after reaching ESRD
to ascertain death, our study included a composite outcome of
CKD progression or death. Similar to CKD progression, most
of our analytic approaches revealed a significant relationship
between lower MHC and PHC scores and an increased risk
of CKD progression or death. This is also consistent with
the findings of the study by Tsai et al., in which low baseline
HRQOL was associated with an increased risk of death.
10
Fur-
thermore, poor HRQOL is associated with increased mortal-
ity rates in patients with ESRD, further underscoring the
importance of this association.
4,6,7
Our study has several limitations. First,
our cohort included only African Ameri-
cans with hypertensive CKD, which may
limit generalizability to patients with other
causes of CKD and other racial/ethnic
groups. However, because African Ameri-
cans with hypertensive CKD are a large
population at particularly high risk of pro-
gression to ESRD, the findings of this study
have relevance to an important segment of
the CKD population in the United
States.
13,20
Second, although this study
was a prospective observational analysis,
we cannot assess causality between
HRQOL and the obser ved outcomes. How-
ever, observational studies are powerful
tools to assess epidemiologic relationships,
and we capitalized on complementary an-
alytic techniques to robustly examine the
relationship of HRQOL to clinically rele-
vant outcomes.
21
Third, despite robust
risk adjustment, our study is subject to residual bias and con-
founding, as are other observational studies. Finally, these ob-
servations were made within the context of a randomized
clinical trial and during a subsequent related observational
study with a defined level of BP control, which may limit gen-
eralizability of these findings to the community setting.
In conclusion, low HRQOL measures were associated with
increased risk of CKD progression andCV events in a large cohort
of African American patients with CKD. These findings suggest
that measurement of HRQOL has an important prognostic value
for CKD patients in the clinical setting. Our findings underscore
the need for future studies to build on these results with carefully
designed translational studies to determine the mechanisms
linking HRQOL and adverse outcomes and for interventions to
potentially improve HRQOL and clinical outcomes.
Table 3. Association between PHC score and outcomes
Model CV Events/CV Deaths Doubling of Serum Creatinine/ESRD Progression of CKD/Death
HR (95% CI)
a
PValue HR (95% CI)
a
HR (95% CI)
a
PValue HR (95% CI)
a
Baseline PHC See Table 4 (418 events/1085 patients) (560 events/1085 patients)
Model 1 ––1.07 (1.02 to 1.12) 0.003 1.08 (1.03 to 1.12) 0.000
Model 2 ––1.06 (1.01 to 1.11) 0.01 1.07 (1.03 to 1.11) 0.001
Model 3 ––1.05 (1.00 to 1.10) 0.07 1.06 (1.01 to 1.10) 0.010
Time-varying PHC (224 events/1091 patients) (421 events/1091 patients) (564 events/1091 patients)
Model 1 1.20 (1.12 to 1.28) 0.000 1.15 (1.10 to 1.20) 0.000 1.18 (1.13 to 1.23) 0.000
Model 2 1.20 (1.13 to 1.28) 0.000 1.15 (1.10 to 1.20) ,0.001 1.17 (1.13 to 1.22) 0.000
Model 3 1.19 (1.11 to 1.27) 0.000 1.12 (1.06 to 1.17) ,0.001 1.15 (1.10 to 1.19) 0.000
Cumulative PHC (224 events/1091 patients) (421 events/1091 patients) (564 events/1091 patients)
Model 1 1.22 (1.13 to 1.31) 0.000 1.14 (1.08 to 1.20) ,0.001 1.16 (1.11 to 1.21) 0.000
Model 2 1.23 (1.14 to 1.32) 0.000 1.13 (1.07 to 1.20) ,0.001 1.15 (1.10 to 1.21) 0.000
Model 3 1.21 (1.13 to 1.30) 0.000 1.10 (1.04 to 1.17) 0.001 1.13 (1.07 to 1.18) 0.000
Model 1: adjusted for randomized group; model 2: model 1 plus adjustment for age, sex, baseline eGFR; model 3: model 2 plus adjustment for age, sex, baseline
eGFR, urinary protein-to-creatinine ratio and history of CVD. 95% CI, 95% confidence interval.
a
HRs expressed as a five-point decrement in PHC.
Table 4. Association between baseline PHC and CV events/CV death
Model per Baseline PHC Score CV Events/CV Deaths (222 Events/1085 Patients)
HR (95% CI) PValue
Model 1
,34 1.96 (1.30 to 2.95) 0.001
34–46 2.18 (1.49 to 3.19) 0.000
46–53 1.00 (0.65 to 1.55) 1.000
.53 1.0
Model 2
,34 2.08 (1.37 to 3.14) 0.001
34–46 2.26 (1.54 to 3.32) 0.000
46–53 1.03 (0.66 to 1.59) 1.000
.53 1.0
Model 3
,34 1.94 (1.28 to 2.94) 0.002
34–46 2.15 (1.45 to 3.17) 0.000
46–53 1.02 (0.66 to 1.58) 1.000
.53 1.0
Model 1: adjusted for randomized group; model 2: model 1 plus adjustment for age, sex, baseline
eGFR; model 3: model 2 pl us adjustment for age, sex, baseli ne eGFR, urinary protein-to -creatinine ratio
and history of CVD. 95% CI, 95% confidence interval.
1852 Journal of the American Society of Nephrology J Am Soc Nephrol 25: 1849–1855, 2014
CLINICAL RESEARCH www.jasn.org

CONCISE METHODS
Study Design
We conducted a longitudinal analysis of African Americans with
hypertensive CKD to examine the association of HRQOL with
progression of CKD, occurrence of CV events, and death over a
period of approximately 10 years. As previously reported, AASK had
two phases: a randomized clinical trial conducted from 1995 to 2001
followed by a quasi-observational cohort study.
22,23
The AASK trial
included 1094 African Americans ages 18–70 years with hypertensive
CKD (GFR, 20–65 ml/min per 1.73 m
2
) who were randomly assigned
to one of two levels of BP control and to one of three different drug
regimens to examine the effect of BP control on CKD progression.
23
Individuals who did not develop ESRD dur ing the trial were invited to
join the cohort study. The latter was initiated in April 2002, at which
point the 691 enrolled patients were switched from randomized therapy
to ramipril and received standard protocol-driven BP management
(,130/80 mmHg).
22
Baseline and follow-up HRQOL measurements
were available for 1091 participants, who make up the final analytic
cohort for these analyses. All study participants provided written in-
formed consent, and the institutional review boards of the participating
centers approved the study.
Variables and Data Sources
Patients provided demographic and clinical information at enroll-
ment. Variables included age, sex, marital status, income, insurance
status, level of education, and comorbid medical conditions. eGFR
was calculated using a formula derived from data from study
participants.
24
Urine protein-to-creatinine ratio was also assessed at
baseline for each participant.
22
HRQOL was measured annually with the Medical Outcomes
SF-36, which is a generic questionnaire for QOL.
25,26
The survey
includes individual scale scores of the following eight domains: phys-
ical functioning, role-physical, bodily pain, general health, vitality,
social functioning, role-emotional, and mental health. These eight
scales can be combined as summary measures: PHC and MHC. The
mean score for PHC and MHC is 50 in the general population, and
lower scores are consistent with worse PHC and MHC.
Outcomes
The primar y outcomes were (1) progression of CKD (defined as dou-
bling of serum creatinine from baseline or development of ESRD),
(2) a CV composite consisting of CV events or CV death, and (3)a
composite outcome of progression of CKD or all-cause death. ESRD
was defined by the initiation of dialysis or receipt of a kidney trans-
plant. CV events were myocardial infa rction, new-onset or worsened
coronary heart disease, new-onset or worsened congestive heart fail-
ure, new-onset or worsened peripheral artery disease, and stroke.
Each CV event was adjudicated by a subgroup of study investigators
unaware of treatment assignment (trial phase).
27
Statistical Analyses
Event cumulative incidences by percentages and event rates were
characterized as per 100 person-years, and both were reported overall
and by quartiles of MHC and PHC scores. Cox proportional hazards
regression analyses were used to assess the association between
baseline MHC and PHC scores and each of the outcomes in iterative
models. Model 1 adjusted solely for randomized group; model 2
adjusted additionally for age, sex, and baseline eGFR; and model 3
adjusted additionally for proteinuria and history of CV disease.
Additionally, time-dependent Cox regression was used to relate the
hazard ratio for the same outcomes to the most recent assessment
preceding each follow-up time point (i.e., time-varying) and the cu-
mulative average of assessments preceding each follow-up time point
(i.e., cumulative) among participants with at least one MHC or PHC
during follow-up. The sample sizes for the time-dependent analyses
(n=1094 for MHC and 1091 for PHC) exceeded the sample size for
analyses of baseline MHC and PHC (n=1088 for MHC and 1085 for
PHC) because the former analyses included patients with missing
baseline MHC and PHC scores as long as they had at least one
follow-up SF-36 measurement.
The assumption of proportional hazards in the Cox regression
models was checked using Schoenfeld residuals for all included
covariates. Significant violations of the proportional haza rds assump-
tion were found for baseline eGFR with the CKD progression/ESRD.
Therefore, a linear interaction term between baseline eGFR and
follow-up time was added to the corresponding models.
The assumption of linearity in the Cox regression models was
checked using restricted cubic smoothing splines for all included
covariates. Baseline PHC was found to have a significant nonlinear
relationship with the CV composite outcome. Therefore, baseline
PHC was categor ized into quartiles. The effect of baseline PHC on the
CV composite outcome was prese nted as the hazard ratio between the
first (lowest), second, and third quartile group versus the fourth
quartile group (highest), respectively. The effect of baseline PHC on
the CV composite outcome was also presented as a nonparametric
smoothing curve wherein the HR and its 95% confidence interval
between the hazard of CV composite outcome when PHC was at a
certain level and the haz ardof CV composite outcome when PHC was
46 (median level) was plotted.
ACKNOWLEDGMENTS
AASK was supported by grants to each clinical center and the
coordinating center from the National Institute of Diabetes and Di-
gestive and Kidney Diseases (NIDDK). In addition, AASK was sup-
ported by the Of ficeo f Research in Minority Health (n ow the National
Center on Minority Health and Health Disparities) and the following
institutional grants from the National Institutes of Health: M01-
RR00080, M01-RR00071, M01-00032, P20-RR11145, M01-RR00827,
M01-RR00052, 2P20-RR11104, RR029887, and DK2818-02. King
Pharmaceuticals provided monetary support and antihypertensive
medicationstoeachclinicalcenter.Pfizer, Inc., AstraZeneca
Pharmaceuticals, GlaxoSmithKline, Forest Laboratories, Pharmacia,
and Upjohn also donated antihypertensive medications. J.P.L. was
supported by NIDDK K24-DK092290. The project described was
supported by Award Number KM1CA156717 (A.P.) from the
National Cancer Institute. The content is solely the responsibility
J Am Soc Nephrol 25: 1849–1855, 2014 Quality of Life and Outcomes 1853
www.jasn.org CLINICAL RESEARCH

of the authors and does not necessarily represent the official views
of the National Cancer Institute or the National Institutes of
Health.
The authors would like to thank the AASK Collaborative Research
Group which includes the following institutions: Case Western Re-
serve University (Principal Investigators, Jackson T. Wright, Jr.,
Mahboob Rahman; Study Coordinator, Renee Dancie, Louise
Strauss); Emory University (Principal Investigator, Janice Lea; Study
Coordinators, Beth Wilkening, Arlene Chapman, Diane Watkins);
Harbor-UCLA Medical Cent er (Principal Investigator, Joel D. Kopple;
Study Coordinators, Linda Miladinovich, Jooree Choi, Patricia
Oleskie, Connie Secules); Harlem Hospital Center (Principal In-
vestigator, Velvie Pogue; Study Coordinator, Donna Dowie, Jen-Tse
Cheng); Howard University (Principal Investigator, Otelio Randall,
Tamrat Retta; Study Coordinators, Shichen Xu, Muluemebet Ketete,
Debra Ordor, Carl Tilghman); Johns Hopkins University (Steering
Committee Chair, Lawrence Appel; Principal Investigators, Edgar
Miller, Brad Astor; Study Coordinators, Charalett Diggs, Jeanne
Charleston, Charles Harris, Thomas Shields); Charles R. Drew Uni-
versity (Principal Investigators, Keith Norris, David Martins; Study
Coordinators, Melba Miller, Holly Howell Laurice Pitts); Medical
University of South Carolina (Principal Investigator, DeAnna Cheek;
Study Coordinator, Deborah Brooks); Meharry Medical College
(Principal Investigators, Marquetta Faulkn er, Olufemi Adeyele; Study
Coordinators, Karen Phillips, Ginger Sanford, Cynthia Weaver);
Morehouse School of Medicine (Principal Investigators, William
Cleveland, Kimberly Ch apman; Study Coordinators, Winifred Smith,
Sherald Glover); Mount Sinai School of Medicine and University of
Massachusetts (Principal Investigators, Robert Phillips, Michael
Lipkowitz, Mohammed Rafey; Study Coordinators, Avril Gabriel,
Eileen Condren, Natasha Coke); Ohio State University (Principal
Investigators, Lee Hebert, Ganesh Shidham; Study Coordinators,
Leena Hiremath, Stephanie Justice); University of Chicago (Principal
Investigators, George Bakris, James Lash; Study Coordinators, Linda
Fondren, Louise Bagnuolo, Janet Cohan, Anne Frydrych); University
of Alabama, Birmingham (Principal Investigators, Stephen Rostand,
Denyse Thornley-Brow n; Study Coordinator, Beverly Key); University
of California, San Diego (Principal Investigators, Francis B. Gabbai,
Daniel T. O’Connor; Study Coordinator, Brenda Thomas) ;Univers ity
of Florida (Principal Investigators, C. Craig Tisher, Geraldine Bichier;
Study Coordinators, Cipriano Sarmiento, Amado Diaz, Carol
Gordon); University of Miami (Principal Investigators, Gabriel
Contreras, Jacques Bourgoignie, Dollie Florence-Green; Study Co-
ordinators, Jorge Junco, Jacqueline Vassallo); University of Michigan
(Principal Investigators, Kenneth Jamerson, Akinlou Ojo, Tonya
Corbin; Study Coordinators, Denise Cornish-Zirker, Tanya Graham,
Wendy Bloembergen); University of Southern California (Principal
Investigators, Shaul Massry, Miroslav Smogorzewski; Study Coor-
dinators, Annie Richardson, Laurice Pitts).
DISCLOSURES
K.N. has consulted with Amgen, Pfizer, Merck, King Pharmaceuticals, and
Abbott; has received grants from the National Institutes of Health and King
Pharmaceuticals; and has received honoraria from Amgen.
REFERENCES
1. Unruh M, Benz R, Greene T, Yan G, Beddhu S, DeVita M, Dwyer JT,
Kimmel PL, Kusek JW, Martin A, Rehm-McGillicuddy J, Teehan BP,
Meyer KB; HEMO Study Group: Effects of hemodialysis dose and
membrane flux on health-related quality of life in the HEMO Study.
Kidney Int 66: 355–366, 2004 PubMed
2. Walters BAJ, Hays RD, Spritzer KL, Fridman M, Carter WB: Health-
related quality of life, depressive symptoms, anemia, and malnutrition
at hemodialysis initiation. Am J Kidney Dis 40: 1185–1194, 2002
3. Porter A, Fischer MJ, Brooks D, Bruce M, Charleston J, Cleveland WH,
Dowie D, Faulkner M, Gassman J, Greene T, Hiremath L, Kendrick C,
Kusek JW, Thornley-Brown D, Wang X, Norris K, Unruh M, Lash J:
Quality of life and psychosocial factors in African Americans with hy-
pertensive chronic kidney disease. Transl Res 159: 4–11, 2012
4. Mapes DL, Lopes AA, Satayathum S, McCullough KP, Goodkin DA,
Locatelli F, Fukuhara S, Young EW, Kurokawa K, Saito A, Bommer J,
Wolfe RA, Held PJ, Port FK: Health-related quality of life as a predictor
of mortality and hospitalization: The Dialysis Outcomes and Practice
Patterns Study (DOPPS). Kidney Int 64: 339–349, 2003 doi: 10.1046/
j.1523-1755.2003.00072.x
5. Lopes AA, Bragg-Gresham JL, Satayathum S, McCullough K, Pifer T,
Goodkin DA, Mapes DL, Young EW, Wolfe RA, Held PJ, Port FK; World-
wide Dialysis Outcomes and Practice Patterns Study Committee: Health-
related quality of life and associated outcomes among hemodialysis pa-
tients of different ethnicities in the United States: the Dialysis Outcomes
and PracticePatterns Study (DOPPS). Am J Kidney Dis 41: 605–615, 2003
6. Knight EL, Ofsthun N, Teng M, Lazarus JM, C urhan GC: The association
between mental health, physical function, and hemodialysis mortality.
Kidney Int 63: 1843–1851, 2003
7. Lowrie EG, Curtin RB, LePain N, Schatell D: Medical outcomes study
short form-36: A consistent and powerful predictor of morbidity and
mortality in dialysis patients. Am J Kidney Dis 41: 1286–1292, 2003
8. Kalantar-Zadeh K, Kopple JD, Block G, Humphreys MH: Association
among SF36 quality of life measures and nutrition, hospitalization, and
mortality in hemodialysis. JAmSocNephrol12: 2797–2806, 2001
9. Mujais SK, Story K, Brouillette J, Takano T, Soroka S, Franek C,
Mendelssohn D, Finkelstein FO: Health-related quality of life in CKD
Patients: Correlates and evolution over time. Clin J Am Soc Nephrol 4:
1293–1301, 2009
10. Tsai Y-C, Hung C-C, Hwang S-J, Wang SL, Hsiao SM, Lin MY, Kung LF,
Hsiao PN, Chen HC: Quality of life predicts risks of end-stage renal
disease and mortality in patients with chronic kidney disease. Nephrol
Dial Transplant 25: 1621–1626, 2010
11. Fukuhara S, Yamazaki S, Marumo F, Akiba T, Akizaw a T, Fujimi S, Haruki
S, Kawaguchi Y, Nihei H , Shoji T, Maeda T: Health-related quali ty of life
of predialysis patients with chronic renal failure. Nephron Clin Pract
105: c1–c8, 2007
12. Centers for Disease Control and Prevention (CDC): Prevalence of
chronic kidney disease and associated risk factors—United States,
1999-2004. MMWR Morb Mortal Wkly Rep 56: 161–165, 2007
13. Klag MJ, Whelton PK, Randall BL, Neaton JD, Brancati FL, Stamler J:
End-stage renal disease in African-American and white men. 16-year
MRFIT findings. JAMA 277: 1293–1298, 1997
14. Kusek JW, Greene P, Wang S-R, Beck G, West D, Jamerson K, Agodoa
LY, Faulkner M, Level B: Cross-sectional study of health-related quality
of life in African Americans with chronic renal insufficiency: The African
American Study of Kidn ey Disease and Hypertension Trial . Am J Kidney
Dis 39: 513–524, 2002
15. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney
disease and the risks of death, cardiovascular events, and hospitaliza-
tion. NEnglJMed351: 1296–1305, 2004
16. Lett HS, Blumenthal JA, Babyak MA, Sherwood A, Strauman T, Robins C,
Newman MF: Depression as a risk factor for coronary artery disease: Evi-
dence, mechanisms, and treatment. Psychosom Med 66: 305–315, 2004
1854 Journal of the American Society of Nephrology J Am Soc Nephrol 25: 1849–1855, 2014
CLINICAL RESEARCH www.jasn.org

17. Walter LC, Brand RJ, Counsell SR, Palmer RM, Landefeld CS, Fortinsky
RH, Covinsky KE: Deve lopment and validation of a prognosti ci ndex for
1-year mortality in older adults after hospitalization. JAMA 285: 2987–
2994, 2001
18. Fischer MJ, Kimmel PL, Greene T, Gassman JJ, Wang X, Brooks DH,
Charleston J, Dowie D, Thornley-Brown D, Cooper LA, Bruce MA,
Kusek JW, Norris KC, L ash JP; AASK Study Group: Elevated depre ssive
affect is associated with adverse cardiovascular outcomes among Af-
rican Americans with chronic kidney disease. Kidney Int 80: 670–678,
2011
19. Menon V, Gul A, Sarnak MJ: Cardiovascular risk factors in chronic kid-
ney disease. Kidney Int 68: 1413–1418, 2005
20. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, Van Lente
F, Levey AS: Prevalence of chronic kidney disease in the United States.
JAMA 298: 2038–2047, 2007
21. Greene T: Randomized and observational studies in nephrology: How
strong is the evidence? Am J Kidney Dis 53: 377–388, 2009
22. Appel LJ, Middleton J, Miller ER 3rd , Lipkowitz M, Norris K, Agodoa LY,
Bakris G, Douglas JG, Charle ston J, Gassman J, Greene T, Jamerso n K,
Kusek JW, Lewis JA, Phillips RA, Rostand SG, Wright JT: The rationale
and design of the AASK cohort study. J Am Soc Nephrol 14[Suppl 2]:
S166–S172, 2003
23. Wright JT Jr, Bakris G, Greene T, Agodoa LY, Appel LJ, Charleston J,
Cheek D, Douglas-Baltimore JG, Gassman J, Glassock R, Hebert L,
Jamerson K, Lewis J, Phillips RA, Toto RD, Middleton JP, Rostand SG;
African American Study of Kidney Disease and Hypertension Study
Group: Effect of blood pressure lowering and antihypertensive drug
class on progression of hypertensive kidney disease: Results from the
AASK trial. JAMA 288: 2421–2431, 2002
24. Lewis J, Agodoa L, Cheek D, Greene T, Middleton J, O’Connor D, Ojo
A, Phillips R, Sika M, Wright J Jr; African-American Study of Hyper-
tension and Kidney Disease: Comparison of cross-sectional renal
function measurements in African Americans with hypertensive
nephrosclerosis and of primary formulas to estimate glomerular filtration
rate. Am J Kidney Dis 38: 744–753, 2001
25. Ware JE Jr, Sherbourne CD: The MO S 36-item short-form health surve y
(SF-36). I. Conceptual framework and item selection. Med Care 30:
473–483, 1992
26. McHorney CA, Ware JE Jr, Lu JF, Sherbourne CD: The MOS 36-item
Short-Form Health Survey (SF-36): III. Tests of data quality, scaling as-
sumptions, and reliability across diverse patient groups. Med Care 32:
40–66, 1994
27. Norris K, Bourgoigne J, Gassman J, Hebert L, Middleton J, Phillips RA,
Randall O, Rostan d S, Sherer S, Toto RD, Wright JT Jr, Wang X, Greene
T, Appel LJ, Lewis J; AASK Study Group: Cardiovascular outcomes in
the African American Study of Kidney Disease and Hypertension
(AASK) Trial. Am J Kidney Dis 48: 739–751, 2006 doi: 10.1053/j.
ajkd.2006.08.004
J Am Soc Nephrol 25: 1849–1855, 2014 Quality of Life and Outcomes 1855
www.jasn.org CLINICAL RESEARCH