H I V / A I D S M A J O R A R T I C L E
Does an Index Composed of Clinical Data Reflect
Effects of Inflammation, Coagulation, and
Monocyte Activation on Mortality Among Those
Aging With HIV?
Amy C. Justice,1,2Matthew S. Freiberg,4,5Russ Tracy,6Lew Kuller,5Janet P. Tate,1,2Matthew Bidwell Goetz,7,8
David A. Fiellin,3Gary J. Vanasse,9Adeel A. Butt,4Maria C. Rodriguez-Barradas,10,11Cynthia Gibert,12,13
Kris Ann Oursler,14,15Steven G. Deeks,16Kendall Bryant,17and the VACS Project Team
1Veterans Affairs Connecticut Healthcare System, West Haven;2Section of General Internal Medicine, and3Department of Medicine, Yale University,
New Haven, Connecticut;4University of Pittsburgh School of Medicine, and5University of Pittsburgh Graduate School of Public Health, Pennsylvania;
6University of Vermont College of Medicine, Burlington;7Veteran Affairs Greater Los Angeles Health Care System,8David Geffen School of Medicine,
University of California, Los Angeles;9Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts;
10Michael E. DeBakey Veteran Affairs Medical Center, and11Infectious Disease Section, Baylor College of Medicine, Houston, Texas;12Washington
DC Veteran Affairs Medical Center, and13George Washington University School of Medicine, Washington, DC;14Baltimore Veteran Affairs Health
Care System, and15University of Maryland School of Medicine, Baltimore;16Department of Medicine, University of California, San Francisco; and
17National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland
(Restricted Index), hemoglobin, FIB-4 Index, hepatitis C virus (HCV), and estimated glomerular filtration rate
improve prediction of mortality. Weighted and combined, these 7 routine clinical variables constitute the Veterans
Aging Cohort Study (VACS) Index. Because nonroutine biomarkers of inflammation (interleukin 6 [IL-6]),
coagulation (D-dimer), and monocyte activation (sCD14) also predict mortality, we test the association of these
indices and biomarkers with each other and with mortality.
Methods. Samples from 1302 HIV-infected veterans on antiretroviral therapy were analyzed. Indices were
calculated closest to date of collection. We calculated Spearman correlations stratified by HIV-1 RNA and HCV
status and measured association with mortality using C statistics and net reclassification improvement (NRI).
Results.Of 1302 subjects, 915 had HIV-1 RNA ,500 copies/mL and 154 died. The VACS Index was more
correlated with IL-6, D-dimer, and sCD14 than the Restricted Index (P , .001). It was also more predictive of
mortality (C statistic, 0.76; 95% confidence interval [CI], .72–.80) than any biomarker (C statistic, 0.66–0.70) or the
Restricted Index (C statistic, 0.71; 95% CI, .67–.75). Compared to the Restricted Index alone, NRI resulted from
incremental addition of VACS Index components (10%), D-dimer (7%), and sCD14 (4%), but not from IL-6 (0%).
Conclusions. Among HIV-infected individuals, independent of CD4, HIV-1 RNA, and age, hemoglobin and
markers of liver and renal injury are associated with inflammation. Addition of D-dimer and sCD14, but not IL-6,
improves the predictive accuracy of the VACS Index for mortality.
When added to age, CD4 count and human immunodeficiency virus type 1 (HIV-1) RNA alone
Index because chronic human immunodeficiency virus
(HIV) infection, aging, comorbidity, and treatment
toxicity likely cause organ system injury beyond that
reflected by CD4 cell count or HIV-1 RNA levels .
The VACS Index incorporates age and 8 routinely
monitored clinical tests: CD4 count; HIV-1 RNA, he-
moglobin, aspartate aminotransferase, alanine amino-
transferase, platelet, and creatinine levels; and hepatitis
C virus (HCV) serostatus. The VACS Index predicts all-
cause mortality more accurately than an does index
restricted to age, CD4 count, and HIV-1 RNA among
people living with HIV infection in North America
Received 15 August 2011; accepted 5 December 2011; electronically published
15 February 2012.
Correspondence: Amy Justice, MD, PhD, VA CT Healthcare System-11ACSLG,
Bldg 35a,Rm2-212,950 Campbell Ave, West Haven, CT 06516 (email@example.com).
Clinical Infectious Diseases
Published by Oxford University Press on behalf of the Infectious Diseases Society of
d CID 2012:54 (1 April)
and Europe [2–5]. However, the VACS Index has been
limited to routinely available clinical data.
Among those with HIV infection, a strong association has
been documented between biomarkers of chronic inflam-
mation and morbidity and mortality [6, 7]. The biomarkers
most consistently associated with patient outcomes include
soluble interleukin 6 (IL-6; a marker of systemic inflam-
mation), fibrin fragment D-dimer (D-dimer; a marker of
procoagulant activity), and soluble CD14 (sCD14; a marker of
lipopolysaccharide-mediated monocyte activation) . All
3 of these markers are elevated in untreated and, to a lesser
degree, treated patients with HIV infection compared with
uninfected controls [7, 8]. The mechanism for this persistent
inflammation is unknown, but is likely to include T-cell
dysfunction, a loss of immunoregulatory responses, excess
burden of viral coinfections, and microbial translocation.
We and others have postulated that chronic inflammation
may contribute to development of end-organ dysfunction,
which in turn can contribute to premature morbidity and
mortality—as it does among the uninfected, aging population
[6, 7, 9, 10].
The VACS Index was developed to capture the combined
and likely interacting effects of HIV disease, comorbid dis-
ease, substance use, and treatment toxicity on outcome in
HIV-infected subjects. Given that a complex association also
likely exists between overall health and inflammation, we
investigated the associations among 3 well-characterized
biomarkers (IL-6, D-dimer, and sCD14), the VACS Index,
and mortality in a large cohort of combination antiretroviral
therapy (ART)–treated, HIV-infected veterans [6, 7].
Veterans Aging Cohort Study
VACS has been well described [11, 12]. It includes HIV-infected
veterans and an age/race/site–matched control group of un-
infected veterans in care. Our long-term goal is to understand
the role of comorbid (ie, not AIDS-defining) medical and psy-
chiatric disease, including alcohol and other substance use and
abuse, in determining clinical outcomes in HIV infection. These
analyses are based on data from the prospectively enrolled and
consented 8-site study .
In 2005–2006, we collected and banked blood and DNA
specimens from consenting subjects. Blood samples were
provided by 1532 HIV-infected participants; of these, 1302
were on ART, defined as $3 antiretroviral agents for at least
1 year. Blood specimens were collected using serum separator
and ethylenediaminetetraacetic acid blood collection tubes.
After collection, blood specimens were shipped to a central
repository, the Massachusetts Veterans Epidemiology Research
and Information Center in Boston, Massachusetts.
All biomarkers were analyzed under the supervision of
Dr Russell Tracy, director of Clinical Biochemistry Research
at the University of Vermont [6, 7]. IL-6 was measured using
a chemiluminescent immunoassay (QuantiGlo IL-6 immu-
noassay; R&D Systems, Minneapolis, Minnesota). This as-
say’s detectable range was 0.4–10 000 pg/mL. We have found
that this assay’s sensitivity, which falls between the standard
and the high-sensitivity enzyme-linked immunosorbent (ELISA)
RNA) and Veterans Aging Cohort Study Index, Derived in 4932
Male Veterans After 1 Year of Antretroviral Therapy
Point Values for Restricted Index (Age, CD4, and HIV-1
500–1 3 105
$1 3 105
FIB-4 was calculated as (years of age 3 AST)/(platelets in 109/L 3 square root
ofALT); eGFRwascalculatedas186.33 (serumcreatinine21.154)3 (age20.203)3
(0.742 for women) 3 (1.21 if black); HCV infection was defined as diagnosis
with a positive antibody test or detectable virus.
Abbreviations: ALT, alanine aminotransferase; ART, antiretroviral therapy;
AST, aspartate aminotransferase; eGFR, estimated glomerular filtration rate;
FIB, fibrosis index; HCV, hepatitis C virus; HIV, human immunodeficiency
virus; VACS, Veterans Aging Cohort Study.
d CID 2012:54 (1 April)
Characteristics of 1302 HIV-Infected Veterans With at Least 180 Days of Combination Antiretroviral Therapy, by Level of
,1.6 1.6–,2.4 2.4–,3.9
Male1265 97.296.498.1 96.897.7 .50
White 24919.1 21.7220.127.116.11.26
Black900 69.167.0 72.666.3 71.5
Other 118.104.22.168 10.3 10.6
Unknown42 22.214.171.124 3.21.9
,50 495 38.0 46.3 38.233.3 28.9
741 56.950.657.3 59.664.3
,.0001350–499289 22.221.0 22.3 25.220.9
300–349270 20.717.219.1 26.2 22.8
100–299160 12.3 7.014.312.119.0
70 126.96.36.199 6.48.0
725.5 188.8.131.52 11.4
HIV-1 RNA (copies/mL)
918 70.578.1 70.168.8 60.1
,.0001306 23.519.423.626.6 27.0
786.0 2.56.4 4.612.9
,.0001 12–13.9483 37.136.335.7 37.939.2
14010.8 3.8 7.3 12.125.1
15 1.20.00.0 0.74.9
,1.45721 55.4 67.556.4 48.641.1
1289.83.4 7.013.8 19.8
$601203 92.4 97.193.392.2 83.7
,.0001 45–59.951 3.9 184.108.40.206.8
171.3 0.51.0 2.81.5
312.40.2 1.6 1.48.0
HCV 597 45.935.045.9 53.555.9
VACS Index score, mean (SD)22.8 (15.5) 29.2 (17.2)35.0 (20.3) 47.4 (24.9)
Deaths per 100 PY1.3 2.03.27.3
d CID 2012:54 (1 April)
Table 2 continued.
,0.18 0.18–,0.34 0.34–,0.64
Total372 413284 233
White22.6 21.818.39.9 .004
Other 9.18.5 8.5 7.7
Unknown 4.6 3.12.1 2.6
,5047.3 36.133.8 31.8
1.6 6.8 5.37.3
43.5 36.628.2 20.6
,.0001 350–49924.5 22.522.218.0
100–299 8.39.715.5 19.3
2.4 4.1 8.19.9
HIV-1 RNA (copies/mL)
2.2 3.98.5 12.9
,.0001 12–13.930.934.4 43.743.8
2.7 9.2 14.1 22.3
,1.45 67.256.247.5 44.6
$60 96.594.489.4 85.8 .0003
45–59.9 2.2 2.45.6 7.3 .0013
0.5 1.24.2 5.2
VACS Index score, mean (SD) 22.1 (15.6) 29.7 (17.9)37.3 (22.1) 45.3 (24.1)
Deaths per 100 PY 1.52.5 2.9 7.0
d CID 2012:54 (1 April)
assays for IL-6 from R&D Systems, is most appropriate for
studies of HIV-positive individuals. Calibration was by the
manufacturer, traceable to the National Institute for Biological
Standards and Control 89/548 (IU/mL). Neither soluble IL-6
receptor nor soluble gp130 demonstrates significant in-
terference in this assay.Four levels of controls wererun withthe
VACS samples, with the interassay coefficient of variation (CV)
ranging from 7.7% to 12.3%.
Table 2 continued.
,2010 2010–,2310 2310–,2710
Male 96.897.6 97.5 99.0.60
Black69.4 67.371.1 67.3
Other 8.26.1 11.611.5
Unknown3.6 2.4 1.72.9
,5040.8 32.728.133.7 .03
54.961.8 63.6 58.7.0013
4.3 5.5 8.3 7.7
300–34921.7 20.014.0 21.2
100–299 9.815.8 21.518.3
4.2 7.39.1 8.7
4.1 7.9 9.110.6
HIV-1 RNA (copies/mL)
72.3 69.159.5 70.2
56.9 45.5 28.9 33.7
,.000112–13.9 35.7 39.443.837.5
0.4 1.2 3.3 4.8
,1.45 59.8 46.140.549.0
$60 96.7 90.383.5 68.3
0.4 0.6 4.16.7
0.4 4.2 4.114.4
HCV 42.456.4 47.1 57.7.0005
VACS Index score, mean (SD)27.5 (18.3)37.8 (21.6)44.4 (23.2)47.3 (25.8)
Deaths per 100 PY 2.0 220.127.116.11
Abbreviations: eGFR, estimated glomerular filtration rate; FIB, fibrosis index; HCV, hepatitis C virus; HIV, human immunodeficiency virus; IL, interleukin; PY, person-
years; sCD14, soluble CD14; SD, standard deviation; VACS, Veterans Aging Cohort Study.
av2or test for trend Mantel–Haenszel.
d CID 2012:54 (1 April)
D-dimer, a terminal product of plasmin acting on a fibrin,
increases during the activation states of coagulation and was
measured by the STAR automated coagulation analyzer
(Diagnostica Stago) using an immuno-turbidometric assay
(Liatest D-DI; Diagnostica Stago, Parsippany, New Jersey).
The agents used in this assay are latex particles coated with
2 different mouse antihuman monoclonal antibodies specific
to D-dimer. There is no significant cross-reactivity with native
fibrinogen. The detectable range is 0.01–20 ug/mL. We used
4 controls, with interassay CVs ranging from 2.8% to 14.8%.
CD14 is the cell-surface receptor for lipopolysaccharide (en-
dotoxin)on monocytes.The soluble form(sCD14) occurseither
through proteolysis or loss of the glycophosphatidylinositol
anchor via phospholipase activity, and increased sCD14 in-
dicates the presence in blood of gram-negative bacteria. The lab
measured sCD14 with an ELISA (Quantikine sCD14 immuno-
assay, R&D Systems), with a detectable range of 40–3200 ng/ml,
using a standard 200-fold sample dilution and 4 controls,
with interassay CVs ranging from 7.2% to 8.1%.
VACS and Restricted Indices
Since initial publication , we have refined the VACS Index
by omitting AIDS-defining illnesses, diagnoses of substance
use, and hepatitis B infection. AIDS events are uncommon
among those on ART  and are variably associated with
mortality . Diagnoses of substance abuse and hepatitis B
infection are inconsistently measured across cohorts. As
a result, the VACS Index is now based on age and 8 routine
clinical tests. The Restricted Index is limited to CD4 count,
HIV-1 RNA, and age (Table 1). Laboratory values used were
closest to the date of the blood banking. Hepatitis C was
considered present after a single seropositive test until
a subsequent test demonstrated viral clearance. The accuracy
of this revised index for mortality among HIV-infected in-
dividuals on ART has been externally validated .
We compared the associations of the VACS and Restricted
indices and each component with IL-6, D-dimer, and sCD14.
Because these biomarkers are not normally distributed, we
used Spearman rank correlation to measure association. To
evaluate whether correlations among VACS Index compo-
nents and biomarkers of inflammation varied by level of
HIV-1 RNA suppression or HCV infection, we also conducted
analyses stratified by HIV-1 RNA ,500 and $500 copies/mL
and HCV status. In nested Cox models, we estimated un-
adjusted and adjusted associations with mortality and calcu-
lated Harrell’s C statistic. Because C statistics are insensitive
to improvements in discrimination, we calculated net re-
classification improvement (NRI) to determine whether ad-
dition of VACS Index components to the Restricted Index
or addition of inflammatory biomarkers to the VACS Index
improved discrimination [15, 16]. We used a parametric
model (c) to predict mortality for these calculations. Data
was complete on 99.8% (1302 of 1304) of sampled subjects,
so no imputation was done.
Participants were predominantly male (97%), black (69%),
and aged 50–64 years (57%). Although samples were collected
from 2005 to 2007, most were collected in 2006 (57%). We
observed 154 deaths. At the time of sample collection (Table 2),
one-third of subjects had CD4 counts .500 cells/mm3(34%),
and most had HIV-1 RNA levels ,500 copies/mL (71%).
Twelve percent had hemoglobin levels ,12 g/dL. Ten percent
had a fibrosis index 4 (FIB-4) consistent with fibrosis (.3.25),
and 8% had some compromise in renal function (estimated
glomerular filtration rate [eGFR] , 60). Nearly half (46%) of
the participants were coinfected with HCV.
Measures of IL-6, D-dimer, and sCD14 were similar to prior
reported values among patients with HIV infection [6, 8].
Overall, the median was 2.1 pg/mL (interquartile range [IQR],
D-dimer, and 1728 ng/mL (IQR, 1462–2115 ng/mL) for sCD14.
Among those with HIV-1 RNA,500 copies/mL, the median
was 1.9 pg/mL (IQR, 1.3–2.1 pg/mL) for IL-6, 0.23 ug/mL
(IQR, 0.15–0.39 ug/mL) for D-dimer, and 1692 ng/mL (IQR,
1435–2075 ng/mL) for sCD14.
Association of VACS and Restricted Indices With Biomarkers
All components of the VACS Index were associated with
IL-6, D-dimer, and sCD14 (P , .005) (Table 2; Figures 1 and
2). VACS Index score was correlated with IL-6, D-dimer, and
sCD14 (P , .0001) (Figure 1A–C), and these were of similar
magnitude as correlation among biomarkers IL-6 and
D-dimer, 0.45; IL-6 and sCD14, 0.41; D-dimer and sCD14,
0.24) (Figure 1D–F).
When stratified by HIV-1 RNA suppression and by
HCV infection, the VACS Index remained more strongly
correlated with each biomarker than the Restricted Index
in all subgroups. Overall, correlations for all VACS Index
components with IL-6 were strongest among those with
HIV-1 RNA.500 copies/mL who were coinfected with
HCV (Figure 2A–D). Differences across groups were less
pronounced for D-dimer and sCD14. Correlations among
non-HIV markers of organ injury and biomarkers of in-
flammation were of similar magnitude with correlations of
CD4 count and these biomarkers in every subgroup. He-
moglobin demonstrated the strongest correlations among
those with HIV-1 RNA.500 copies/mL, regardless of HCV
status (Figure 2C–D). FIB-4 was relatively consistent in
d CID 2012:54 (1 April)
its correlations across groups with the exception of IL-6,
which appeared more correlated with FIB-4 among those
with HCV infection. Age demonstrated stronger correlations
with inflammatory biomarkers among those with HIV-1
RNA,500 copies/mL who were HCV uninfected (Figure 2A).
Associations With All-Cause Mortality
All 3 biomarkers were associated with mortality in unadjusted
analyses (P , .0001) (Table 2). However, inflammatory bio-
markers alone or in combination did not discriminate morta-
lity as well as the VACS Index (C statistic, 0.76; 95% confidence
interval [CI], .72–.80). D-dimer and sCD14, but not IL-6, re-
mained independently associated with mortality after adjust-
ment for the VACS Index (P , .05). The VACS Index was more
discriminating of mortality than the Restricted Index (C statistic,
0.71; 95% CI .67–.75). The NRI of adding VACS Index com-
ponents to the Restricted Index was 10% (Figure 3). Adding
D-dimer to the VACS Index resulted in an NRI of 7%, and
further addition of sCD14 improved classification modestly
(NRI, 4%). Adding IL-6 resulted in no improvement (NRI, 0%).
Among veterans with HIV infection on ART, an index that
includes generic measures of organ system injury (VACS Index)
is correlated with IL-6, D-dimer, and sCD14, whether or not
subjects have achieved viral suppression or are coinfected with
HCV. Although the mechanism for this association cannot be
determined using our study design, the associations observed
are consistent with the hypothesis that chronic inflammation
contributes to end-organ dysfunction and/or that several
chronic diseases common among those with HIV infection may
be proinflammatory. Although all 3 biomarkers are associated
withmortality,theirassociations arenot as strongasthose ofthe
VACS Index. When added to the VACS Index, IL-6 was not
independently associated with mortality, whereas D-dimer and
sCD14 remained significant and improved risk reclassification.
This suggests that effects of IL-6 on mortality are reflected
by the VACS Index, whereas those of D-dimer and sCD14 are
at least partially independent. Importantly, the VACS Index
is more associated with biomarkers of chronic inflammation
and with all-cause mortality than the Restricted Index; this es-
tablishes the independent association of hemoglobin, liver in-
jury, and renal injury with inflammation and with mortality
after adjustment for CD4 count, HIV-1 RNA level, and age.
The VACS provides a well-characterized and validated
sample for these analyses. VACS data have been compared
with .30 other cohorts in North America and Europe, and
associations in VACS were found to be similar to those
observed in other cohorts [17, 18].
Although they offer insight for understudied populations,
our data may not generalize to all affected populations.
When comparing VACS subjects with Centers for Disease
Control and Prevention (CDC) HIV data , VACS sub-
jects are more likely to be people of color (77% vs 64% black
or Hispanic), older (62% vs 25% aged $50 years), and male
(97% vs 75%). In both CDC and VACS data, 48% of men
report having sex with men. VACS may not represent women
or younger subjects, but it does offer insight regarding these
biomarkers among the growing proportion of individuals
aging with HIV infection, including men who have sex with
men, those with HCV coinfection, and people of color. More-
over, we used a cutoff of HIV-1 RNA , 500 copies/mL when
a lower threshold is reported in current assays. Among the 918
Cohort Study (VACS) Index Scores. Spearman correlation coefficients were
as follows: A, Interleukin (IL)–6 and VACS Index (r 5 0.42); B, D-dimer and
VACS Index (r 5 0.39); C, Soluble CD14(sCD14) and VACS Index (r 5 0.35);
D, D-dimer and IL-6 (r 5 0.41); E, sCD14 and IL-6 (r 5 0.45); and F, D-dimer
and sCD14 (r 5 0.24). Abbreviations: IL, interleukin; sCD14, soluble CD14;
VACS, Veterans Aging Cohort Study.
Scatterplots of biomarkers of inflammation and Veterans Aging
d CID 2012:54 (1 April)
77% had HIV-1 RNA #75 copies/mL, and 31% had HIV-1
RNA #50 copies/mL. The correlations among VACS Index
and inflammatory biomarkers were similar when we restricted
analysis to HIV-1 RNA #50 copies/mL. We doubt that lower
levels of detection would substantially alter our findings.
Our findings suggest that the chronic inflammation and
organ system injury observed among HIV-infected in-
dividuals on ART are strongly related to each other. Given
the associations demonstrated in our analyses and in prior
work, this pathophysiologic process may result from syner-
gistic effects of HIV, aging, substance use, multimorbidity,
of combination antiretroviral therapy among those with HIV-1 RNA ,500 copies/mL, hepatitis C virus (HCV) uninfected (n 5 505) (A); HIV-1 RNA
,500 copies/mL, HCV infected (n 5 413) (B); HIV-1 RNA .500 copies/mL, HCV uninfected (n 5 200) (C); and HIV-1 RNA .500 copies/mL, HCV
infected (n 5 184) (D). Abbreviations: eGFR, estimated glomerular filtration rate; FIB, fibrosis index; IL, interleukin; Rest. Index, Restricted Index;
VACS, Veterans Aging Cohort Study.
Spearman correlation coefficients of biomarkers in 1302 human immunodeficiency virus (HIV)–infected veterans with at least 180 days
d CID 2012:54 (1 April)
and medication toxicity [1, 20]. Prior literature has demon-
strated an association between markers of inflammation and
age , and recently, investigators have demonstrated that
markers of inflammation are associated with CD4 count, with
HIV-1 RNA, and with mortality among those with HIV in-
fection [6, 7]. We extend these observations by demonstra-
ting that an index with additional indicators for organ system
injury is more strongly correlated with these biomarkers and
with mortality. Of note, the combination of 8 variables into
a single index decreases measurement error inherent in any sin-
gle biomarker. Further, clinical tests such as those included in
the VACS Index (and D-dimer) must comply with Clinical Lab-
oratory Improvement Amendments regulatory standards and
are less variable than basic science assays such as IL-6 or sCD14.
Because D-dimer and sCD14 reflect systemic inflammatory
processes, they may provide additional insights beyond the
VACS Index. For example, both D-dimer and sCD14 are likely
involved in the development of vascular disease, pulmonary
disease, osteoporosis, and central and peripheral nerve injury
not currently included in the VACS Index. They may also
reflect earlier signs of injury to the liver, kidney, and bone
marrow than are reflected by FIB-4, eGFR, or hemoglobin.
Because D-dimer is inexpensive and clinically available,
adding it to the VACS Index might be a reasonable first step.
Once D-dimer was included, the addition of sCD14 offered
only modest improvement in the VACS Index.
The prevalence of anemia among HIV-infected individuals,
its correlation with these biomarkers, and its independent
association with mortality  underscores its importance
among those aging with HIV infection. Little is known about
the underlying mechanisms of anemia among those aging
with HIV infection. For many patients, anemia improves on
ART . Anemia that persists or develops after treatment
may indicate poor adherence, emerging HIV resistance, or
additional causes of chronic inflammation. The contributing
roles of continued alcohol use, chronic HCV infection, other
chronic viral infections, progressive liver disease, and renal
disease in anemia should all be explored.
Liver disease is a leading cause of death among those aging
with HIV infection. Prior work has demonstrated that HCV
(B) for adding VACS Index components to the Restricted Index, adding D-dimer to the VACS Index, and further addition of soluble CD14. Abbreviations:
NRI, net reclassification improvement; sCD14, soluble CD14; VACS, Veterans Aging Cohort Study.
Net reclassification improvement shown in detail for adding D-dimer to the Veterans Aging Cohort Study (VACS) Index (A) and final result only
d CID 2012:54 (1 April)
infection progresses more rapidly to liver failure and death
among those with HIV infection [24–27], but few have explored
liver injury among those with HIV infection not coinfected with
HCV. Further, although there is growing evidence that FIB-4 is
an excellent indicator of liver fibrosis among those with HIV
and/or HCVinfection[28, 29], its associationwith inflammation
and all-cause mortality has not been previously reported.
Of organ systems included in the VACS Index, renal
disease demonstrated the weakest associations with IL-6,
D-dimer, and sCD14. This may reflect a true difference in
association or limitations of eGFR as an indicator of renal
disease. Although single-site studies suggest that among
those with eGFRs ,90 mL/minute/1.73 m the performance
of eGFR is close to a 24-hour urine creatinine clearance
[30, 31], it may not be as relevant as proteinuria or other less
routinely assessed measures.
We believe that the VACS Index (with or without the ad-
dition of D-dimer) will prove more clinically useful than any
single biomarker. Although our unadjusted hazard ratio for
the highest quartile vs the lowest of of IL-6, D-dimer, and
sCD14 on mortality were close to those reported among other
populations with HIV infection [6, 7], the VACS Index was
more strongly predictive of all-cause mortality than any bio-
marker and is readily quantified using standardized and
widely available clinical tests. D-dimer and sCD14 improved
classification when added to the VACS Index, but not as much
as the addition of the VACS Index components improved the
To date, we have demonstrated that the VACS Index is
highly predictive of all-cause mortality and strongly associated
with biomarkers of inflammation. We have yet to prove that
changes in the VACS Index due to intervention correspond to
changes in risk of mortality. Nothing short of a randomized
trial can definitely establish the utility of the VACS Index as
a surrogate outcome. Nevertheless, we have made 3 observa-
tions that support this assumption. First, we showed biologic
plausibility in this analysis in that the VACS Index is more
correlated with biomarkers of inflammation (IL-6), microbial
translocation (D-dimer), and hypercoagulability (sCD14)
than the Restricted Index . Second, in prior work we have
shown that hemoglobin, FIB-4, and eGFR, as well as CD4
count and HIV-1 RNA, change substantially in response to
ART initiation  and that the VACS Index is more res-
ponsive to ART initiation (and to differences in ART adher-
ence) than the Restricted Index . Finally, also in prior
work, we have demonstrated that the prognostic discrimina-
tion of the VACS Index is consistent when applied at any
point over the first 5 years of ART . Taken together, these
findings suggest that the VACS Index may provide a superior
means of tracking disease burden over time among HIV-
infected individuals on ART.
The VACS Index provides a stronger indication of in-
flammation (ie, stronger correlation with IL-6, D-dimer, and
sCD14) and overall mortality than an index restricted to CD4
count, HIV-1 RNA, and age. The superior prognostic in-
formation available in the VACS Index can be realized without
additional cost because required laboratory tests are already
routinely monitored in clinical care. Whether the additional
information offered by incorporating D-dimer (or sCD14) into
the VACS Index justifies the added cost and complexity remains
to be determined. Use of the VACS Index may help clinicians
better gauge response to treatment so that modest improvement
in a single test (eg, CD4 count) is not overshadowed by a decline
in overall score.
in the Veterans Aging Cohort Study and the study coordinators and
staff at each of our sites and at the West Haven Coordinating Center.
Without the commitment and care of these individuals, this research
would not be possible. We would also like to acknowledge the sub-
stantial in-kind support we receive from the Veterans Affairs Healthcare
Financial support.This work was supported by the National Institutes
of Health: National Institute on Alcohol Abuse and Alcoholism (U10-
AA13566), National Heart, Lung, and Blood Institute (R01-HL095136;
R01-HL090342; RCI-HL100347), and National Institute on Aging (R01-
AG029154; K23 AG024896). J. P. T. was supported by the Training
Program in Environmental Epidemiology (T32 ES07069).
Potential conflicts of interest.All authors: No reported conflicts.
All authors have submitted the ICMJE Form for Disclosure of Potential
Conflicts of Interest. Conflicts that the editors consider relevant to the
content of the manuscript have been disclosed.
We acknowledge the veterans who participate
1. Justice AC. HIV and aging: time for a new paradigm. Curr HIV/AIDS
Rep 2010; 7:69–76.
2. Justice AC, McGinnis KA, Skanderson M, et al. Towards a combined
prognostic index for survival in HIV infection: the role of ‘‘non-HIV’’
biomarkers. HIV Med 2009; 11:143–51.
3. Brown ST, Kyriakides K, kirkwood K, et al. The VACS risk index
responds to treatment interventions and is highly correlated with and
predictive of mortality events in the OPTIMA study. Int AIDS Conf
4. Akgun KM, Pisani MA, Fried TR, et al. Risk factors for medical
intensive care unit admission in HIV infected veterans. Am Throacic
5. Tate JP, Justice AC, Hughes MD, et al. Performance of the re-
fined VACS risk index during the first 12 months of antiretroviral
therapy among US and European subjects. In: Program and ab-
stracts of the 15th International Workshop on HIV Observational
Databases (Prague, Czech Republic). Bordeaux, France: IWHOD,
6. Kuller LH, Tracy R, Belloso W, et al. Inflammatory and coagulation
biomarkers and mortality in patients with HIV infection. PLoS Med
7. Sandler NG, Wand H, Roque A, et al. Plasma levels of soluble CD14
independently predict mortality in HIV infection. J Infect Dis 2011;
d CID 2012:54 (1 April)
8. Neuhaus J, Jacobs DR Jr, Baker JV, et al. Markers of inflammation, Download full-text
coagulation, and renal function are elevated in adults with HIV in-
fection. J Infect Dis 2010; 201:1788–95.
9. Deeks SG, Phillips AN. HIV infection, antiretroviral treatment, ageing,
and non-AIDS related morbidity. BMJ 2009; 338:a3172.
10. Brenchley JM, Price DA, Schacker TW, et al. Microbial translocation is
a cause of systemic immune activation in chronic HIV infection. Nat
Med 2006; 12:1365–71.
11. Justice AC, Dombrowski E, Conigliaro J, et al. Veterans Aging
Cohort Study (VACS): overview and description. Med Care 2006;
44(8 Suppl 2):S13–24.
12. Fultz SL, Skanderson M, Mole LA, et al. Development and verification
of a ‘‘virtual’’ cohort using the national VA health information system.
Med Care 2006; 44(8 Suppl 2):S25–30.
13. D’Arminio MA, Sabin CA, Phillips A, et al. The changing incidence of
AIDS events in patients receiving highly active antiretroviral therapy.
Arch Intern Med 2005; 165:416–23.
14. Mocroft A, Sterne JA, Egger M, et al. Variable impact on mortality of
AIDS-defining events diagnosed during combination antiretroviral
therapy: not all AIDS-defining conditions are created equal. Clin Infect
Dis 2009; 48:1138–51.
15. Cook NR, Ridker PM. Advances in measuring the effect of individual
predictors of cardiovascular risk: the role of reclassification measures.
Ann Intern Med 2009; 150:795–802.
16. Cook NR. Use and misuse of the receiver operating characteristic curve
in risk prediction. Circulation 2007; 115:928–35.
17. Kitahata MM, Gange SJ, Abraham AG, et al. Effect of early versus
deferred antiretroviral therapy for HIV on survival. N Engl J Med 2009;
18. Sterne JA, May M, Costagliola D, et al. Timing of initiation of anti-
retroviral therapy in AIDS-free HIV-1–infected patients: a collaborative
analysis of 18 HIV cohort studies. Lancet 2009; 373:1352–63.
19. Centers for Disease Control and Prevention. HIV/AIDS surveillance
reports 2007. Department of Health and Human Services, 2009.
Available at: http://www.cdc.gov/hiv/topics/surveillance/resources/
reports/index.htm. Accessed 10 June 2011.
20. Justice AC. Prioritizing primary care in HIV: comorbidity, toxicity, and
demography. Top HIV Med 2006; 14:159–63.
21. Bruunsgaard H, Pedersen BK. Age-related inflammatory cytokines and
disease. Immunol Allergy Clin North Am 2003; 23:15–39.
22. Harris RJ, Sterne JA, Abgrall S, et al. Prognostic importance of
anaemia in HIV type-1-infected patients starting antiretroviral
therapy: collaborative analysis of prospective cohort studies. Antivir
Ther 2008; 13:959–67.
23. Moore RD, Forney D. Anemia in HIV-infected patients receiving
highly active antiretroviral therapy. J Acquir Immune Defic Synd 2002;
24. Al-Mohri H, Murphy T, Lu Y, Lalonde RG, Klein MB. Evaluating liver
fibrosis progression and the impact of antiretroviral therapy in HIV
and hepatitis C coinfection using a noninvasive marker. J Acquir
Immune Defic Syndr 2007; 44:463–9.
25. McGinnis KA, Fultz SL, Skanderson M, Conigliaro J, Bryant K,
Justice AC. Hepatocellular carcinoma and non-Hodgkin’s lym-
phoma: the roles of HIV, hepatitis C infection, and alcohol abuse.
J Clin Oncol 2006; 24:5005–9.
26. Piasecki BA, Lewis JD, Reddy KR, et al. Influence of alcohol use,
race, and viral coinfections on spontaneous HCV clearance in
a US veteran population. Hepatology 2004; 40:892–9.
27. Weber R, Sabin CA, Friis-Moller N, et al. Liver-related deaths in
persons infected with the human immunodeficiency virus: the
D:A:D study. Arch Intern Med 2006; 166:1632–41.
28. Sterling RK, Lissen E, Clumeck N, et al. Development of a simple
noninvasive index to predict significant fibrosis in patients with
HIV/HCV coinfection. Hepatology 2006; 43:1317–25.
29. Vallet-Pichard A, Mallet V, Nalpas B, et al. FIB-4: an inexpensive
and accurate marker of fibrosis in HCV infection. comparison with
liver biopsy and fibrotest. Hepatology 2007; 46:32–6.
30. Ravasi G, Lauriola M, Tinelli C, Brandolini M, Uglietti A, Maserati R.
Comparison of glomerular filtration rate estimates vs. 24-h creatinine
clearance in HIV-positive patients. HIV Med 2009; 10:219–28.
31. Barraclough K, Er L, Ng F, Harris M, Montaner J, Levin A.
A comparison of the predictive performance of different methods of
kidney function estimation in a well-characterized HIV-infected
population. Nephron Clin Pract 2009; 111:c39–48.
32. Justice AC, Freiberg MS, Tracy R, et al. Biomarkers of inflammation,
coagulation and monocyte activation are strongly associated with
the VACS index among veterans on cART. In: Program and abstracts
of the 18th Conference on Retroviruses and Opportunistic In-
fections, Boston, Massachusetts. Alexandria, VA: CROI, 2011.
33. Tate JP, Justice AC. for the VACS Project Team. Change in a prog-
nostic index for survival in HIV infection after one year on cART by
level of adherence. In: Program and abstracts of the 48th Annual
Meeting of the Infectious Diseases Society of America, Vancouver,
BC, Canada. Arlington, VA: IDSA, 2010.
34. Tate J, Justice AC, Hughes M, et al. An internationally validated
mortality risk index for HIV infected individuals on antiretroviral
therapy: performance by region, gender, risk group, and level of viral
d CID 2012:54 (1 April)