Prevalence and prognostic effect of sarcopenia
in breast cancer survivors: the HEAL Study
Adriana Villaseñor & Rachel Ballard-Barbash &
Kathy Baumgartner & Richard Baumgartner &
Leslie Bernstein & Anne McTiernan &
Marian L. Neuhouser
Received: 27 March 2012 /Accepted: 7 July 2012 /Published online: 4 October 2012
#Springer Science+Business Media, LLC 2012
Purpose This study aimed to determine the prevalence of
sarcopenia and examine whether sarcopenia was associated
with overall and breast-cancer-specific mortality in a cohort
of women diagnosed with breast cancer (stages I–IIIA).
Methods A total of 471 breast cancer patients from western
Washington State and New Mexico who participated in the
prospective Health, Eating,Activity, and Lifestyle Study were
included in this study. Appendicular lean mass was measured
using dual X-ray absorptiometry scans at study inception, on
two standard deviations below the young healthy adult female
mean of appendicular lean mass divided by height squared
(<5.45 kg/m2). Total and breast-cancer-specific mortality data
were obtained from Surveillance Epidemiology and End
Results registries. Multivariable Coxproportional hazardmod-
els assessed the associationsbetween sarcopenia and mortality.
Results Median follow-up was 9.2 years; 75 women were
classified as sarcopenic, and among 92 deaths, 46 were
attributed to breast cancer. In multivariable models that
included age, race-ethnicity/study site, treatment type,
comorbidities, waist circumference, and total body fat per-
centage, sarcopenia was independently associated with
overall mortality (hazard ratio (HR)02.86; 95 % CI, 1.67–
4.89). Sarcopenic women had increased risk of breast-
cancer-specific mortality, although the association was not
statistically significant (HR01.95, 95 % CI, 0.87–4.35).
Conclusion Sarcopeniaisassociatedwithanincreased riskof
overall mortality in breast cancer survivors and may be asso-
ciated with breast-cancer-specific mortality. The development
of effective interventions to maintain and/or increase skeletal
muscle mass to improve prognosis in breast cancer survivors
warrants further study.
Implications for Cancer Survivors Such interventions may
help breast cancer patients live longer.
Keywords Sarcopenia.Appendicular leanmass.
Research between body composition and cancer outcomes
usually focuses on the prognostic effects of excess body fat
A. Villaseñor (*):M. L. Neuhouser
Cancer Prevention Program, Division of Public Health Sciences,
Fred Hutchinson Cancer Research Center,
1100 Fairview Avenue North, M4-B402,
Seattle, WA 98109-1024, USA
A. Villaseñor:A. McTiernan:M. L. Neuhouser
School of Public Health, Department of Epidemiology,
University of Washington,
Seattle, WA, USA
Applied Research Program, Division of Cancer Control and
Population Sciences, National Cancer Institute,
Bethesda, MD, USA
K. Baumgartner:R. Baumgartner
Department of Epidemiology and Population Health,
University of Louisville,
Louisville, KY, USA
Division of Cancer Etiology, Department of Population Sciences,
Beckman Research Institute, City of Hope,
Duarte, CA, USA
Epidemiology Program, Division of Public Health Sciences,
Fred Hutchinson Cancer Research Center,
Seattle, WA, USA
J Cancer Surviv (2012) 6:398–406
[1, 2], yet emerging evidence supports severe depletion of
skeletal muscle (sarcopenia) as an important predictor of cancer
sarcopenia is associated with poor muscle strength, functional
impairment, and disability [10–15]. Sarcopenia prevalence esti-
mates range from 5 to 13 % among persons aged 60–70 years
and from 11 to 50 % in persons over 80 years of age [9, 10]. Of
interest, individuals diagnosed with some forms of cancer may
experience a marked and progressive weight loss, primarily of
skeletal muscle, resulting in severe depletion of skeletal muscle
to tumor progression related to survival [3–5]. Prado et al.
reported associations between sarcopenia and poor prognostic
outcomes in breast, gastrointestinal, and lung cancers. Com-
pared to patients without sarcopenia, those with sarcopenia
had a 2.6-fold greater risk of developing a secondary malig-
nancy (hazard ratio (HR)02.6; 95 % confidence interval (CI),
1.2–5.6 ), greater rates of chemotherapy toxicity (p00.036,
of 7 months; HR04.2; 95 % CI, 2.4–7.2) .
Obese women (defined as body mass index (BMI)
≥30.0 kg/m2), have greater rates of morbidity and mor-
tality than non-obese women (i.e., BMI <30.0 kg/m2) [1, 2].
Furthermore, research suggests that simultaneous occurrence
of excess body fat and sarcopenia exacerbates the risk of
developing multiple health-related problems [19–22]. In
health-fragile populations, such as cancer patients, obese indi-
viduals with sarcopenia have greater rates of functional im-
pairment, treatment failure, and treatment toxicity and
consequentially shorter time to tumor progression than obese
patients without sarcopenia [4, 5, 19]. In a cohort of over-
a strong association between sarcopenia and overall mortality
(HR02.1; 95 % CI, 1.1–3.5). Whether sarcopenia has an
impact on survival that is independent of excess body fat is
unknown since evidence linking sarcopenia to cancer progno-
sis is limited. No previous studies have focused on associa-
tions of sarcopenia with breast cancer mortality. Here, we
report on the prevalence of sarcopenia, assessed by appendic-
ular lean mass relative to height and the association with
overall and breast-cancer-specific mortality in a cohort of
women diagnosed with invasive breast cancer (stages I-IIIA).
We also examine the influence of individual and breast cancer
clinical characteristics on sarcopenic status.
Materials and methods
The Health, Eating, Activity, and Lifestyle (HEAL) Study is
a cohort study of women diagnosed with breast cancer
designed to examine physical activity, eating habits, weight
patterns, diet, hormones, and other prognostic factors for
breast cancer. The methods for this multicenter, multiethnic
prospective cohort study have been described elsewhere
. In brief, using local Surveillance Epidemiology and
End Results (SEER) registries of New Mexico (University
of New Mexico, UNM), Los Angeles, CA, USA (University
of Southern California), and western Washington (Fred
Hutchinson Cancer Research Center, FHCRC), we identi-
fied and enrolled 1,183 women, >18 years of age, diagnosed
with in situ or stage I–IIIA primary incident breast cancer
within 12 months of their diagnoses. Participants completed a
self-report questionnaire and an in-person interview at study
inception. A subset of participants enrolled at UNM study site
clinical visit, including anthropometric measurements and a
whole-body dual-energy X-ray absorptiometry (DXA) scan.
There wereno additional eligibility criteriafor participation in
anthropometric measurements. Annual data collected from
SEER registries and abstracted medical records were used to
follow each participant and determine health related out-
comes, and mortality due to breast cancer or other causes.
diagnosed with invasive breast cancer, had a baseline DXA
scan,andwerefreefromany disease recurrence, new primary,
or death up to 9 months following study inception. Written
informed consent was obtained from each participant. The
study was performed with the approval of the Institutional
Review Boards of the participating institutions in accordance
with an assurance filed with and approved by the US Depart-
ment of Health and Human Services.
Body composition measurements
Anthropometric measurements Using standardized meth-
ods, body weight, height, and waist circumference were
measured with subjects wearing light indoor clothing or a
hospital gown without shoes, at the baseline clinical visit
[23, 24]. Trained staff conducted anthropometric measures
twice, and the average was used in the analysis (Pearson’s
correlation coefficients, r00.99) . BMI was calculated
as weight in kilograms divided by the square of height in
Fat and lean soft tissue measurements We used DXA to
quantify whole- and regional-body composition, at baseline
(New Mexico site: Lunar model DPX; Lunar Radiation
Corporation, Madison, WI, USA; Washington site: Hologic
QDR 1500, Hologic, Inc., Bedford, MA, USA). The DXA
scan provided measures of total body fat tissue (nonbone,
muscle-free) and lean soft tissue in kilograms (nonbone,
fat-free). Lean soft tissue mass was separated into trunk
and appendicular components. Appendicular lean mass
J Cancer Surviv (2012) 6:398–406399
was calculated as the sum of lean soft tissue mass in
the arms and legs and represents the primary proportion
of skeletal muscle mass in the body [9, 25]. Total body
fat percentage was calculated as the weight of total
body fat tissue divided by total body weight. DXA provides
a highly reproducibleand accuratemeasure for body fat tissue
and lean soft tissue mass, and is a validated and accepted
method for assessing body composition [25, 26].
specific mortality from the date of initial data collection
through December 31, 2007. Deaths were classified using
International Classification of Diseases, 10th Revision
of interest, overall mortality, was initiated on the dateof initial
data collection and ended on the date of death. Nondeceased
patients were censoredonDecember31.2007.The secondary
end point of interest, breast-cancer-specific mortality, was
defined using ICD-10 code C50 . In analyses of breast
cancer deaths, women dying from other causes were censored
December 31, 2007.
We collected standardized information on demographic
characteristics, medical history, physical activity, lifestyle
habits, and medication use. Breast cancer stage at diagnosis
was obtained from the SEER registry records, and breast
cancer treatment data were obtained from participants’ medi-
cal records and SEER.
Our analytic goals were to describe the prevalence of sarco-
penia in this cohort of breast cancer survivors and charac-
terize the association of sarcopenia with overall and breast-
cancer-specific mortality. An appendicular lean mass index
was calculated as appendicular lean mass (kilogram) divided
by height (meter) squared . Sarcopenia was defined as
two standard deviations (SD) below the mean appendicular
lean mass index among young healthy female (<5.45 kg/m2)
[8, 28] and has been shown to be associated with poor
function and increased mortality in older age groups [29,
30]. Differences in participant, treatment, and disease-
related characteristics, by sarcopenic status, were evaluated
using ANOVAs for continuous variable and/or the chi-
squared statistic for categorical variables. We used the
Kaplan–Meier technique to construct survival curves and
to calculate 5- and 10-year survival rates . We employed
Cox proportional hazards models to estimate the age-
adjusted and multivariable HR and 95 % CI for death due
to any cause and breast-cancer-specific deaths by sarcopenic
status. Age at diagnosis (years) was used as the time metric
for all regression analysis. We tested and confirmed non-
violation of the proportionality assumption based on a
graphical approach (i.e., log(−log) plots)  and the
goodness-of-fit test using Schoenfeld residuals .
Covariates were examined for inclusion in the final mul-
tivariate model based on a list of known or suspected a priori
predictors of mortality and sarcopenia from published liter-
ature [8–10]. Variables were retained in the final model if
they were associated with sarcopenia, associated with mor-
tality in nonsarcopenic survivors and had altered the risk
estimate of the model containing sarcopenia plus age by at
least 10 %. Because the two study sites had distinct race/
ethnic composition, we generated an adjustment variable for
race–ethnicity/study site . All models included age,
race–ethnicity/study site, waist circumference, body fat per-
centage, physical activity, breast cancer stage at diagnosis,
and treatment type. For overall mortality, we further adjust-
ed for Charlson comorbidity index score . For the
breast-cancer-specific mortality models, we further adjusted
for tamoxifen use. Interactions were tested by adding a
product term for sarcopenic status and each of the following
covariates: BMI, menopause, and adjuvant tamoxifen use.
Statistical tests were performed using Stata (version 11.1;
StataCorp LP, College Station, TX, USA) software. All
tests were two-sided, and statistical significance was set at
Among the 471 women included in this analysis, 75 (16 %)
were sarcopenic, with 38 % of these women classified as
obese (total body fat percentage, ≥38 %) and 61 % as not
obese (<38 %) . The medians, 5th and 95th percentiles,
and the ranges are given for age at diagnosis and weight,
height, waist circumference, BMI, total body fat percentage,
appendicular lean mass, and height-adjusted appendicular
lean mass assessed at baseline (Table 1). Sarcopenic women
tended to be older at diagnosis, have lower total body
weight, smaller waist circumference, and lower BMI com-
pared to nonsarcopenic women. As defined, sarcopenic
women had a lower amount and narrower range of appen-
dicular lean mass and, as anticipated, a lower amount and
narrow range of total body fat percentage.
Sarcopenia was more common in women who were
postmenopausal and were diagnosed with earlier disease
stage (Table 2). No differences in prevalence of sarcopenia
were found across race–ethnicity/study site, physical activ-
ity categories, alcohol use, smoking status, comorbidity
index scores, disease treatment, or tamoxifen use.
400 J Cancer Surviv (2012) 6:398–406
Between the initial clinic visit and December 31, 2007,
92 deaths occurred of which 46 were due to breast cancer.
The median length of follow-up was 9.2 years (ranging
between 0.5 and 10.9 years). Results for overall mortality
and breast-cancer-specific mortality were similar. Sarcope-
nia was associated with an increased risk of overall mortal-
ity and breast-cancer-specific mortality, although the latter
relationship did not reach statistical significance. Figure 1
illustrates the unadjusted overall survival rates by sarco-
penic status. The overall 5-year survival rate among sarco-
penic women was 85.3 % and among nonsarcopenic women
was 92.9 %; comparable 10-year figures were 67.6 and
83.8 %, respectively (log-rank p00.0019, data not shown).
In age-adjusted analysis, sarcopenia was associated with
increased risk of any death (Table 3) (HR01.90; 95 % CI,
1.17–3.08). Next, we examined a series of potential con-
founders in a sequential manner (models 1–5). Following
adjustment for age, race–ethnicity/study site, waist circum-
ference, comorbidity index score, and treatment (model 1),
we found sarcopenia to be strongly associated with an
increased risk of overall mortality (HR02.44; 95 % CI,
1.44–4.15). Based on strong evidence that excess body fat
has an adverse prognostic effect, we were interested in how
the addition of adiposity, modeled as total body fat percent-
age (model 2) or BMI categories (model 3), would alter the
association between sarcopenia and overall mortality [2, 16,
23, 35]. Sarcopenia remained independently predictive of
overall mortality regardless of adiposity measure used (total
body fat percentage: HR02.86; 95 % CI, 1.67–4.89; BMI:
HR02.29; 95 % CI, 1.34–3.90). We were also interested in
exploring whether additional factors known to affect surviv-
al, specifically stage at diagnosis (model 4) and physical
activity (model 5), would alter the sarcopenia–survival rela-
tionship [36–38]. We found the sarcopenia–mortality rela-
tionship did not markedly change following inclusion of
either covariate, after adjusting for adiposity (total body fat
Using a similar approach, we examined factors associated
with sarcopenia and breast-cancer-specific mortality. Figure 2
illustrates the unadjusted breast-cancer-specific survival
curves by sarcopenic status. The 5-year breast-cancer-
specific survival rates were approximately 94.2 % regardless
of sarcopenic status, and the 10-year breast-cancer-specific
survival rates were 86.5 % in sarcopenic women and 90.5 %
in nonsarcopenic women (log-rank p00.38, data not shown).
In age-adjusted analysis, sarcopenia was associated with an
increased risk of death due to breast cancer (Table 4) (HR0
1.65; 95 % CI, 0.78–3.52); with only nine deaths among the
75 sarcopenic women, the association did not reach statistical
significance. With the addition of potential confounding var-
iables (multivariable model) compared to the age-adjusted
model, we did not find a meaningfully change to the
conclusionthat sarcopeniawas modestly,but statisticallynon-
significantly associated with breast-cancer-specific mortality
(HR01.95; 95 % CI, 0.87–4.35).
In this prospective cohort study of breast cancer survivors,
we found a substantial prevalence of sarcopenia (15.9 %),
given the relatively young age distribution of this cohort.
Notably, sarcopenia was present in breast cancer survivors
across the distribution of BMI <30 kg/m2. Furthermore, we
found that sarcopenia was an independent predictor of poor
survival. Sarcopenic women were almost three times more
likely to die from any cause (HR02.86; 95 % CI, 1.67–4.89)
and almost two times more likely to die from breast-cancer-
specific cause (HR01.95; 95 % CI, 0.89–4.35), regardless
of adiposity, compared to women without sarcopenia. Our
Table 1 Baseline anthropometry and body composition of breast cancer survivors by sarcopenic status (N0471)
Distribution of sarcopenia
No sarcopenia (N0396)Sarcopenia (N075)
Min5th percentile Median 95th percentile MaxMin5th percentile Median 95th percentile Max
Waist circumference (cm)
Body mass index (kg/m2)
Total body fat mass (%)
Appendicular lean mass (kg)
Appendicular lean mass
Min minimum, Max maximum
J Cancer Surviv (2012) 6:398–406401
Table 2 Associations of participant and disease characteristics by sarcopenic status
Body composition phenotypesP valuea
Number PercentNumber PercentNumber Percent
Age at diagnosis (years)
Adiposity, body fat percentage
Not obese: <38 %
Obese: ≥38 %
Body mass index (kg/m2)
Non-Hispanic white/New Mexico
Other/Washington and New Mexico
Moderate/vigorous physical activity, 7+h/week
Alcohol intake, 2+ beverages/day
Current Smoker (%)
Charlson comorbidity Score
Surgery and radiation
Surgery and chemotherapy
Chemotherapy and radiation
Not all sum to 100 % due to missing values
aP value represents test for variation across specific characteristics
402J Cancer Surviv (2012) 6:398–406
observation suggests that depleted skeletal muscle mass
may partially explain the variation seen in relation to sur-
vival, regardless of adiposity, compared to women without
To date, four other studies evaluated the adverse effects
of depleted skeletal muscle mass in individuals diagnosed
with cancer; all reported similar results. In the single study
of breast cancer, Prado et al. reported that sarcopenia was
independently associated with a higher incidence of
treatment induced toxicity and a shorter time to tumor
progression among metastatic breast cancer patients (N055),
independent ofadiposity.In2007,Pradoetal. noteda
strong positive association between low skeletal muscle mass
and chemotherapy toxicity in colon cancer patients treated
with 5-FU and leucovorin (N062). In a separate study, Prado
et al.  reported that in patients with gastrointestinal cancer
or lung cancer (N0250), obese patients with sarcopenia had
an increased risk of mortality (HR04.2; 95 % CI, 2.4–7.2)
when compared to obese nonsarcopenic patients. Further, Tan
et al.  reported that sarcopenia was an independent predic-
tor of mortality among overweight/obese pancreatic cancer
patients (N0111) (HR02.07; 95 % CI, 1.23–3.50). While the
methods of body composition analysis differed between our
study (DXA scan) and studies by Prado et al. and Tan et al.
(CT scans), both approaches showed that sarcopenia was
strongly associated with adverse prognostic factors (treatment
Time since study enrollment (years)
No Sarcopenia Sarcopenia
Overall Survival (proportion)
Fig. 1 Overall survival curves of breast cancer survivors with and
Table 3 Hazard ratios and 95 % CIs for risk of death from any cause
with sarcopenia (N0471)
Models of association
of sarcopenic status and
death from any cause
HR95 % CIP valuea
Death, any cause
1.90 1.17 3.08
2.44 1.44 4.15
2.86 1.67 4.89
2.29 1.34 3.90
2.86 1.67 4.90
2.77 1.61 4.77
HR hazard ratio, 95 % CI 95 % confidence interval, BMI body mass
index, Mod/Vig moderate/vigorous
Model 1 adjusts for age, race/ethnicity with center site, treatment,
Charlson comorbidity score, and waist circumference. Model 2 adjusts
for model 1 covariates plus body fat percentage. Model 3 adjusts for
model 1 covariates plus BMI. Model 4 adjusts for model 1 covariates
with body fat percentage plus tumor stage. Model 5 adjusts for model 1
covariates with body fat percentage plus physical activity
aP value associated with change in likelihood seen in nested models
including and excluding additional model group variables for model 1
Time since study enrollment (years)
Breast Cancer-Specific Survival (proportion)
Fig. 2 Breast-cancer-specific survival curves of breast cancer survi-
vors with and without sarcopenia
Table 4 Hazard ratios and 95 % CIs for risk of death from breast
cancer with sarcopenia (N0471)
Models of association
of sarcopenic status and
death from breast cancer
HR95 % CI
Death, breast cancer
HR hazard ratio, 95 % CI 95 % confidence interval
aModel adjusted for age, race/ethnicity with center site, treatment,
tamoxifen use, disease stage, and waist circumference
J Cancer Surviv (2012) 6:398–406403
Several mechanisms have been proposed to explain the
potential adverse effect of low relative skeletal muscle mass
on breast cancer prognosis [3–5, 17]. First, chemotherapy
dosing protocols use body-surface area to estimate the
amount of metabolic target tissue [39–41]. Given the het-
erogeneity in distribution of lean soft tissue and fat tissues
across the BMI distribution, the use of body-surface area
may result in an overestimation or an underestimation of
actual metabolic target tissues . Potential mismatches in
chemotherapy dosing may help explain the association of
sarcopenia with increased risk of chemotherapeutic toxicity
and treatment failure [3, 17]. Second, sarcopenia is associ-
ated with functional impairment and muscle weakness [19,
22, 42], which may influence important lifestyle habits such
as poor dietary nutrient intake, decreased physical activity,
weight gain, and tobacco or alcohol use, which are recog-
nizable risk factors for adverse prognosis of breast
cancer.[16, 35, 43–45] Finally, muscle tissue has multiple
important functions, such as glucose homeostasis and insu-
lin sensitivity, respiratory integrity, and cardiac output ;
therefore, a significant reduction of muscle mass may fur-
ther increase the risk of adverse outcomes in patients with
Research on the effect of depleted skeletal muscle mass
on morbidity and mortality has been limited both by the lack
of an operational definition, as well as by the challenge of
reliably quantifying lean mass in large population studies
. Baumgartner was the first to use a dichotomous meth-
od based on two standard deviations below the sex-specific
mean of height-adjusted appendicular lean mass in young
healthy adults, as measured by DXA [5, 8, 48, 49]. Other
approaches have used similar types of cut-points using other
measurement tools (e.g., bioelectrical impedance and com-
puted tomography) or used residuals from linear regression
models of lean mass given fat mass and height, or fat-mass
cut points associated with adverse outcomes in vulnerable
populations (e.g., lung cancer patients) [3, 4, 17]. Newman
et al.  demonstrated variation in prevalence of sarcope-
nia and impact for prognostic outcomes were dependent on
both the quantitative method used and definition of sarco-
penia. Thus, a standard approach for both measuring and
defining sarcopenia is necessary to accurately describe the
extent and impact of sarcopenia. A recent collaborative
physical functioning measured as a gait speed <1 m/s−1plus
reduced muscle mass, using an T score of muscle mass
(corrected for either height, body weight or fat mass)
two SD or less be used . Further methodological work is
needed in this area.
The strengths of our study include a well-characterized
cohort with a larger sample size (N0471) compared to prior
studies examining sarcopenia and cancer outcomes. We used
well-annotated tumor-, treatment-, and traditional prognostic-
related data and have approximately 11 years of well-
documented outcomes based on medical record reviews and
annual SEER registry updates. We used DXA scan to assess
body composition [42, 50–52]. DXA has a good reported
reproducibility, with coefficients of variation (CV%) for total
body fat mass of 1–2 %, for total body fat-free and total body
lean tissueof 1–2 %,for arm leansofttissueof 3–4 %,and for
leg lean soft tissue of 1–2 % [26, 50].
Limitations included the observational design and there-
fore causality cannot be inferred. We adjusted our models
for clinical and lifestyle-related factors, alcohol intake,
physical activity, and smoking status. Residual confound-
ing, however, may still exist. Sarcopenia may be a surrogate
variable for the true causal exposures, such as BMI or
physical activity, through alternative mechanisms [16, 23].
Furthermore, there is evidence that the sarcopenia–mortality
association is more apparent in women with excessive adi-
posity (BMI ≥30 kg/m2) [3–5]; however, we had no obese
women based on BMI with sarcopenia in our cohort. Our
observations for sarcopenia did not change when adjusted
for total body fat percentage or hours of physical activity,
and no significant interactions were observed. Lastly, a
limited number of deaths were documented in our cohort
as breast-cancer-specific deaths, limiting the statistical pow-
er to examine breast-cancer-specific mortality by sarcopenic
status. Given extensive published evidence of the positive
association between sarcopenia and mortality, our finding
for all-cause mortality is unlikely to be due to chance.
Data from this cohort of breast cancer survivors suggest
that sarcopenia may be an independent predictor of mortal-
ity, regardless of adiposity. Further research is needed to
validate our findings and examine the potential use of body
composition assessment for dosing chemotherapeutics
agents. These observations are particularly important given
the relatively high prevalence of sarcopenia in this cohort of
breastcancersurvivorsandthe naturally occurringage-related
loss of muscle mass, potentially accelerated by cancer, its
treatment, and hormone manipulation [53–55]. Research into
the development of effective interventions to maintain and/or
increase skeletal muscle mass may also improve prognosis in
breast cancer survivors.
Todd Gibson for their continued assistance and support, as well as the
HEAL participants for their ongoing dedication to this study. This
study was supported through National Cancer Institute contracts
NO1-CN-75036-20, NO1-CN-05228, NO1-PC-67010, U54-
CA116847, and training grant R25-CA094880. A portion of this work
was conducted through the Clinical Research Center at the University
of Washington and support by the National Institutes of Health
grant MO1-RR-0037 and University of New Mexico grant, NCRR
The authors would like to thank Anita Ambs and
Disclosure of potential conflicts of interest
interest were disclosed.
No potential conflicts of
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