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HepC Newsletter
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Dema-@aol.com
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Jul 02, 2009 08:47 PDT
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NATAP http://natap.org/
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Hepatitis C Virus Infection and the Risk of Coronary Disease
"HCV‐infected persons are younger and have lower lipid levels and a lower
prevalence of hypertension. Despite a favorable risk profile, HCV infection
is associated with a higher risk of CAD after adjustment for traditional
risk factors."
"To summarize, the increased risk of CAD in HCV‐infected persons may be
related to a differential level of cytokines, which are markers of
inflammation, thrombosis, and endothelial dysfunction [33–35, 37]; behavioral and
social risk profile [42–44]; malnutrition and/or inflammation pathway
activation [36]; or liver injury. More likely, a combination of these factors acts
in concert to negate the protective effect of a favorable risk profile and
increases the overall risk of CAD.
In conclusion, in a comparison of HCV‐infected subjects with HCV‐
uninfected control subjects, HCV infection is associated with a higher risk of CAD,
even after adjustment for traditional risk factors. The reason(s) and
mechanism(s) of this association need further study."
Clinical Infectious Diseases July 15 2009;49:225–232
Adeel A. Butt,1,2,3 Wang Xiaoqiang,2,3 Matthew Budoff,5 David Leaf,6,7
Lewis H. Kuller,4 and Amy C. Justice8,9
1University of Pittsburgh School of Medicine, 2Center for Health Equity
Research and Promotion, 3VA Pittsburgh Healthcare System, and 4Department of
Epidemiology, University of Pittsburgh Graduate School of Public Health,
Pittsburgh, Pennsylvania; 5Los Angeles Biomedical Research Institute at Harbor
‐UCLA Medical Center, 6VA Greater Los Angeles Healthcare System, and
7David Geffen School of Medicine at UCLA, Los Angeles, California; and 8VA
Connecticut Healthcare System, West Haven, and 9Yale University School of
Medicine and Public Health, New Haven, Connecticut
Background. The association between hepatitis C virus (HCV) infection and
coronary artery disease (CAD) is controversial. We conducted this study to
determine and quantify this association.
Methods. We used an established, national, observational cohort of all HCV‐
infected veterans receiving care at all Veterans Affairs facilities, the
Electronically Retrieved Cohort of HCV Infected Veterans, to identify HCV‐
infected subjects and HCV‐uninfected control subjects. We used the Cox
proportional‐hazards model to determine the risk of CAD among HCV‐infected
subjects and control subjects.
Results. We identified 82,083 HCV‐infected and 89,582 HCV‐uninfected
subjects. HCV‐infected subjects were less likely to have hypertension,
hyperlipidemia, and diabetes but were more likely to abuse alcohol and drugs and to
have renal failure and anemia. HCV‐infected subjects had lower mean (±
standard deviation) total plasma cholesterol (175 ± 40.8 mg/dL vs. 198 ± 41.0
mg/dL), low‐density lipoprotein cholesterol (102 ± 36.8 mg/dL vs. 119 ±
38.2 mg/dL), and triglyceride (144 ± 119 mg/dL vs. 179 ± 151 mg/dL) levels,
compared with HCV‐uninfected subjects (p<.001 for all comparisons). In
multivariable analysis, HCV infection was associated with a higher risk of CAD
(hazard ratio, 1.25; 95% confidence interval, 1.20–1.30). Traditional risk
factors (age, hypertension, chronic obstructive pulmonary disease, diabetes,
and hyperlipidemia) were associated with a higher risk of CAD in both
groups, whereas minority race and female sex were associated with a lower risk
of CAD.
Conclusions. HCV‐infected persons are younger and have lower lipid levels
and a lower prevalence of hypertension. Despite a favorable risk profile,
HCV infection is associated with a higher risk of CAD after adjustment for
traditional risk factors.
Several infectious etiologies for coronary artery disease (CAD) have been
proposed in recent years on the basis of epidemiological associations, but
there is no consensus regarding a causative role [1–3]. The association
between hepatitis C virus (HCV) infection and CAD is less clear. A small
number of reported studies have shown conflicting results; some have reported no
association between HCV infection and CAD [4–7], whereas others have
reported an increased risk [8] or an increase in measures of subclinical
atherosclerosis (e.g., carotid intima‐media thickness) [9–11]. Many of the
studies showing no association between HCV infection and CAD used a case‐control
design in which subjects with known CAD were compared with control subjects
without CAD and the prevalence of HCV infection was compared between the 2
groups without adjustment for all CAD risk factors.
Persons with HCV infection are at an increased risk of developing hepatic
steatosis, which shares many clinical features with the metabolic syndrome
[12, 13]. Hepatic steatosis has also been associated with elevated levels
of markers of inflammation and endothelial dysfunction [14]. These factors
suggest a biologically plausible mechanism of increased risk of CAD in at
least a subset of HCV‐infected persons. We set out to determine the
association between HCV infection and CAD in a large, national, electronically
retrieved cohort of HCV‐infected veterans (ERCHIVES). Such large observational
studies with carefully identified controls are better suited to identify any
true association between HCV infection and cardiovascular disease.
Discussion
To our knowledge, this is the largest study to determine the role of HCV
infection in the risk of CAD. We found that HCV‐infected subjects were at a
significantly higher risk of developing CAD, compared with HCV‐uninfected
subjects, even after adjustment for traditional risk factors for
cardiovascular disease. The reason for the increased risk is unclear, especially
because several cardiovascular risk factors were less prevalent in the HCV‐
infected subjects. For example, HCV‐infected subjects were younger; had lower
total cholesterol, LDL‐C, and triglyceride levels; and had a lower prevalence
of hypertension. Because the risk of CAD was higher after adjustment for
the traditional risk factors, HCV infection itself or other unknown factors
are at least partly responsible for the increased risk.
Recent studies support the role of inflammation in the pathogenesis of CAD
[29–32]. According to these studies, a complex balance between
proinflammatory and anti‐inflammatory cytokines dictates the initiation, propagation,
and rupture of atherosclerotic lesions. Some studies have shown that the
levels of inflammatory markers (e.g., high sensitivity C‐reactive protein,
interleukin 6, and tumor necrosis factor α) are higher in HCV‐infected
subjects, compared with HCV‐uninfected control subjects [33–35]. Since
inflammation and thrombosis are critical pathways in the genesis of CAD and since
HCV infection is also associated with alterations in inflammatory markers,
this might be the common pathway that increases CAD risk. Markers of
thrombosis and inflammation have also been associated with more‐severe CAD, and
the malnutrition inflammation scores are elevated in HCV‐infected persons
with CAD, compared with those without CAD [36, 37]. Most studies have shown an
increased prevalence of diabetes among HCV‐infected persons, which is a
major cardiovascular risk factor. Although we did not find an increased
prevalence of diabetes among the HCV‐infected persons in the current study, we
did not adjust for body mass index in the 2 groups. In our previous work, we
found that HCV‐infected persons have a lower body mass index, compared
with HCV‐uninfected persons (authors' unpublished data), which could at least
partly explain this finding. Another possibility is that HCV‐infected
persons are seen less frequently for care and are less likely to receive a
diagnosis of diabetes. In fact, nonadherence to follow‐up visits was the most
common reason that HCV‐infected people were not prescribed treatment for HCV
infection in one study [38]. Although diabetes was not more prevalent among
the HCV‐infected group in our study, when present, it was associated with a
significantly higher risk of CAD in both groups.
The proportion of subjects with evidence of liver injury was higher among
the HCV‐infected persons. This finding is intuitive and confirms multiple
previous studies. Liver injury was associated with an increased risk of CAD,
but this risk was contributed to by the HCV‐uninfected subjects and was
not significant for the HCV‐infected subjects. Furthermore, the lack of
association between HCV infection and CAD in the subset of persons with liver
injury (in the absence of a diagnosis of alcohol abuse or dependence)
suggests a role for liver injury in determining the risk of CAD.
Our finding of lower lipid levels in the HCV‐infected persons is
consistent with previous studies [39–41]. Postulated mechanisms for lower lipid
levels in HCV‐infected persons include binding of HCV particles to various
lipid fractions, impaired hepatocyte assembly of very‐low‐density lipoprotein
because of inhibition of microsomal transfer protein, and entry of HCV into
hepatocytes through the LDL‐C receptors [39]. Although the lipid levels
were lower in the HCV‐infected subjects, the risk of CAD associated with
hyperlipidemia was similar in the HCV‐infected and ‐uninfected subjects.
Other traditional risk factors (e.g., age, male sex, hypertension, COPD [a
surrogate for heavy smoking], and diabetes) were associated with a higher
risk of CAD in both HCV‐infected and ‐uninfected groups, as shown in other
studies. Unanticipated was the association of black race with a lower risk
of CAD. Numerous studies indicate that minority race is associated with a
higher risk of cardiovascular risk factors (e.g., hypertension and
diabetes), but this did not translate into a higher risk of CAD in our study.
Whether the lower risk of CAD found in our study is related to access‐to‐care
issues or other factors needs further study. The finding of a positive
association between drug abuse or dependence and CAD in the HCV‐infected persons
is an interesting finding. Cocaine use has been well established as a risk
factor for acute myocardial infarction in persons with and without
preexisting coronary disease [42]. Although coronary vasospasm has been implicated
as the most likely mechanism, arrhythmias and increased atherosclerosis
due to adventitial mast cells have also been proposed to effect such risk
[43, 44]. Whether our observation is associated with such behavioral risk
factors is unclear at this time.
There are many strengths to our study. We studied a large national
population, rather than a geographically limited sample. The VA health care system
is a unique population that offers significant advantages for large
studies of outcomes. Foremost is the availability of data at centralized centers,
from which appropriate clinical, laboratory, pharmacy, and outcome
parameters can be retrieved. The VA is the largest single provider of
comprehensive health care to HCV‐infected persons in the United States. Its extensive
electronic medical information–gathering system is linked nationally and
provides unparalleled opportunity for longitudinal follow‐up of patients. The
patients at the VA medical centers are cared for regardless of their
ability to pay. Patients may relocate multiple times and will still be cared for
by the same system, with health care providers having access to patient
information from other sites.
A limitation of our study is the use of ICD‐9 codes for the diagnosis of
CAD. Although it would be ideal to use adjudicated clinical measures for the
diagnosis of CAD, it would not be possible in such a large national study.
ICD‐9 codes have been used in other large national studies for
cardiovascular outcomes. Another limitation is the lack of inclusion of body mass
index and family history of CAD, which are important risk factors for CAD.
Although we do not believe that family history of CAD may be different in HCV‐
infected and ‐uninfected persons, the former are more likely to have a lower
body mass index. If true, the higher risk found in our study is actually
an underestimation of the true risk. We used the diagnosis of COPD as a
surrogate for heavy smoking status, because it is likely to pick up only a
subset of smokers with the most severe consequences of smoking. It may be argued
that persons who receive a diagnosis of an acute coronary event may not
have presented to a VA facility for care and instead may have been taken to
the nearest emergency facility. If true, this is likely to affect both HCV‐
infected and ‐uninfected persons equally.
To summarize, the increased risk of CAD in HCV‐infected persons may be
related to a differential level of cytokines, which are markers of
inflammation, thrombosis, and endothelial dysfunction [33–35, 37]; behavioral and
social risk profile [42–44]; malnutrition and/or inflammation pathway
activation [36]; or liver injury. More likely, a combination of these factors acts
in concert to negate the protective effect of a favorable risk profile and
increases the overall risk of CAD.
In conclusion, in a comparison of HCV‐infected subjects with HCV‐
uninfected control subjects, HCV infection is associated with a higher risk of CAD,
even after adjustment for traditional risk factors. The reason(s) and
mechanism(s) of this association need further study.
Results
Our final analysis set consisted of 171,665 subjects (82,083 HCV‐infected
and 89,582 HCV‐uninfected subjects) (figure 2). HCV‐infected subjects were
less likely to have hypertension, hyperlipidemia, and diabetes but were
more likely to abuse alcohol or drugs and to have renal failure and anemia,
compared with HCV‐uninfected control subjects (table 1). Mean plasma levels
of total cholesterol, LDL‐C, and triglycerides were significantly lower in
the HCV‐infected subjects, compared with HCV‐uninfected subjects.
In univariable analysis, factors associated with a higher risk of CAD in
the whole group were increasing age, hypertension, COPD, diabetes,
hyperlipidemia, renal failure, and anemia. Female sex and Hispanic race were
associated with a lower risk of CAD. When we analyzed HCV‐infected and ‐
uninfected subjects separately, the same factors were associated with risk of CAD,
except that black race was associated with a higher risk in the HCV‐infected
group, and drug abuse or dependence was associated with a lower risk of
CAD in the HCV‐uninfected group. The magnitude of effect for hypertension,
COPD, and renal failure was slightly greater in the HCV‐infected group than
in the HCV‐uninfected group (table 2).
In multivariable Cox regression analysis of the whole group, HCV infection
was associated with a higher risk of CAD (hazard ratio, 1.27; 95%
confidence interval [CI], 1.22–1.31). As in the univariable model, traditional risk
factors (increasing age, hypertension, COPD, diabetes, hyperlipidemia, and
renal failure) were associated with a higher risk of CAD, whereas minority
race and female sex were associated with a lower risk of CAD. When we
analyzed HCV‐infected and ‐uninfected subjects separately, the same factors
were associated with the risk of CAD. Drug abuse or dependence was associated
with a higher risk of CAD in the HCV‐infected group but not in the HCV‐
uninfected group (table 3). In Kaplan‐Meier analysis, HCV‐infected subjects
had a higher risk of CAD after adjustment for traditional risk factors (age,
race, sex, hypertension, diabetes, hyperlipidemia, and COPD) (figure 3).
We determined the number of inpatient and outpatient visits to any VA
facility for subjects with and without a diagnosis of incident CAD, and we
compared the number of visits in the years before and the years after the CAD
diagnosis to determine whether there may be a bias in seeking care at a VA
facility versus a non‐VA facility. For this analysis, we excluded visits to
outpatient mental health facilities, group therapy, and substance abuse
clinics, as well as laboratory visits and visits related to hemodialysis. The
median number of visits before CAD diagnosis among subjects who later
developed CAD was 7, compared with 5 visits among subjects who never developed
CAD. In years after the CAD diagnosis, the median number of visits was 13.5
among those with CAD and 7 among those without CAD, which suggests that a
high proportion of veterans seek care from VA facilities after a diagnosis
of coronary events.
To determine the role of liver injury in the risk of CAD among HCV‐
infected and ‐uninfected subjects, we computed the risk of liver injury in the
hazards of CAD in the Cox proportional‐hazards model. The overall hazard ratio
was 1.09 (95% CI, 1.05–1.14); for HCV‐infected and ‐uninfected groups,
the hazard ratios were 1.05 (95% CI, 0.80–1.06) and 1.15 (95% CI, 1.09–
1.22), respectively. We conducted further analyses limited to those subjects who
had evidence of liver injury in the absence of a diagnosis of alcohol
abuse or dependence. In multivariable Cox proportional‐hazards analysis, HCV
infection was not associated with a higher risk of CAD (hazard ratio, 0.99;
95% CI, 0.93–1.06). All other associations (age, sex, hypertension, COPD,
diabetes, dyslipidemia, renal failure, and anemia) remained significant as in
the previous models.
Methods
The creation of ERCHIVES has been described elsewhere [15–18]. The current
study used an updated cohort of subjects identified from 2001 through
2006. In brief, we assembled a national cohort of HCV‐infected veterans from
the VA National Patient Care Database, the VA Pharmacy Benefits Management
database, and the Decisions Support System database in VA fiscal years 2001–
2006 (1 October 2001 through 30 September 2006; the original cohort included
subjects identified in 1998–2003) (figure 1). Demographic and clinical
data were extracted from the National Patient Care Database. The utility and
accuracy of the VA administrative data and VA Pharmacy Benefits Management
data have been previously reported by our group and others [17, 19–24]. The
National Patient Care Database contains hospitalization records, including
discharge diagnoses from 1970 onward. The discharge diagnoses are coded
according to the International Classification of Diseases, 9th Revision (ICD‐
9) For 1997 onward, the National Patient Care Database also contains
outpatient visit records, including diagnoses and clinic visits. The validity of
ICD‐9 codes has been tested previously for a range of comorbid conditions,
and the sensitivity, specificity, and agreement (κ values) have been found
to correlate well with chart abstractions [20, 23, 25, 26].
The laboratory values were retrieved from the Decisions Support System
database, which contains selected laboratory data collected from 2000 onward
during routine clinical care of veterans. The laboratory data included
measurements of HCV antibody, total cholesterol, low‐density lipoprotein
cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), triglyceride,
hemoglobin, alanine and aspartate aminotransferase, serum albumin,
bilirubin, international normalization ratio, and glucose levels. To validate the
Decisions Support System data, we compared data collected in the Decisions
Support System and the Immunology Case Registry for 22,647 human
immunodeficiency virus (HIV)–infected veterans with an inpatient or outpatient visit
in fiscal year 2002 for 9 laboratory tests. For 6 of the 9 laboratory tests,
the Decisions Support System provided laboratory values for more
individuals. Overlapping results were nearly perfectly correlated [27].
For our study, HCV infection was defined by the presence of HCV antibody
or a positive result of qualitative or quantitative testing for HCV RNA. CAD
was defined by the presence of at least 1 inpatient or 2 outpatient ICD‐9
codes for myocardial infarction or congestive heart failure or any code for
coronary artery bypass grafting or percutaneous transluminal coronary
angioplasty. Dyslipidemia was defined by the presence of any of the following:
(1) total cholesterol level >200 mg/dL on 2 separate occasions, (2) total
cholesterol level >200 mg/dL on 1 occasion and LDL‐C level >130 mg/dL on 1
occasion, and (3) prescription of cholesterol‐lowering medication for >30
days. Subjects were considered to have diabetes if they met any of the
following criteria: (1) glucose level 200 mg/dL on 2 separate occasions; (2) ICD‐
9 codes (2 outpatient or 1 inpatient) and treatment with an oral
hypoglycemic or insulin for 30 days; (3) ICD‐9 codes (2 outpatient or 1 inpatient)
and glucose level 126 mg/dL on 2 separate occasions; and (4) glucose level
200 mg/dL on 1 occasion and treatment with an oral hypoglycemic or insulin
for 30 days. We compared our definition with the presence of at least 1
inpatient or at least 2 outpatient codes for diabetes. Our definition had a
sensitivity of 86.6%, specificity of 97.5%, and agreement of 95.5%, with a κ
value of 0.85, suggesting a very high degree of correlation. Renal failure was
defined by an estimated glomerular filtration rate <30 mL/min/1.73 m2, as
calculated by the simplified modification of diet in renal disease (i.e.,
MDRD) equation. Liver injury was defined by alanine or aspartate
aminotransferase levels above the upper limit of normal. Because the diagnostic codes
for smoking have been found to be inaccurate (A. Justice, personal
communication), we used the diagnosis of chronic obstructive pulmonary disease
(COPD) as a surrogate for heavy smoking. The number of pack years of smoking
has been demonstrated to correlate with a diagnosis of COPD in HIV‐infected
and ‐uninfected persons among veterans [28].
Case patients were all HCV‐infected subjects initially identified in the
ERCHIVES on the basis of a positive result of an HCV antibody test or a
positive result of an HCV RNA test performed during routine clinical care.
Control subjects were matched by age (in 5‐year increments), sex, race, and
year of entry into care in the VA health care system. We retained subjects
with complete clinical and laboratory data and excluded subjects who were
coinfected with HIV. We also excluded subjects who had a diagnosis of CAD at
baseline. We analyzed all subjects with complete data, as well as HCV‐
infected subjects and their corresponding individually matched HCV‐uninfected
control subjects with complete data for our analysis (figure 1).
Baseline characteristics were compared using the χ2 test or the t test as
appropriate. Predictors of incident CAD were determined in univariable and
multivariable Cox regression analyses. Unadjusted and adjusted Kaplan‐Meier
plots were drawn to plot the hazards of developing CAD over time. We used
Stata, version 8.2 (Stata Corp), for statistical analyses.
To determine whether the exclusion of any subjects may have led to a bias
in our analysis, we compared the subjects who were excluded with those who
were retained in the final analysis. We also compared the characteristics
of subjects who were excluded because of a prevalent diagnosis of CAD at
entry into the cohort. Finally, we determined the number of inpatient and
outpatient visits for HCV‐infected and ‐uninfected subjects, as well as for
those with and without CAD, to indirectly analyze any diagnosis bias due to
care outside the VA health care system.
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