*Correlations are shown as absolute values. Starred biomarkers demonstrated NEGATIVE correlations with the indicated biomarker of inflammation. Specifically, eGFR, hemoglobin, and CD4 count were all negatively correlated with all three biomarkers of inflammation.
# 796
Biomarkers of Inflammation, Coagulation and Monocyte Activation Are
Strongly Associated with the VACS Index among Veterans on cART
Amy Justice*1,2, Matthew Freiberg3, Russell Tracy4, Janet Tate1,2, Matthew Goetz5, Adeel Butt3, Maria Rodriguez-Barradas6, Cynthia Gibert7, Kris Ann Oursler8, Kendall
Bryant9, for the Veterans Aging Cohort Study (VACS) 1Yale University, New Haven, CT, US~ 2VA Connecticut Healthcare System, West Haven, CT, US~ 3University of Pittsburgh, Pittsburgh, PA, US~ 4University of Vermont, Burlington, VT,
US~ 5VA Los Angeles Healthcare System, Los Angeles, CA, US~ 6Baylor College of Medicine, Houston, TX, US and Michael E. DeBakey VA Medical Center, Houston, TX, US~ 7VA Medical Center, Washington, DC, US and George Washington Univ., Washington, DC,
US~ 8Univ. of Maryland-Baltimore, Baltimore, MD, US and Baltimore VA Medical Center, Baltimore, MD, US~ and 9National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, US
BACKGROUND
Everywhere ART available:
Most patients achieve viral suppression
Incident AIDS events are rare and variably associated with mortality
Life expectancy is extended
HIV Associated Non AIDS (HANA) Conditions determine disease burden
We need a clinically accessible and reasonably standardized approach to
tracking disease progression that:
Integrates CD4 count, HIV-1 RNA, and age
Includes measures of hematologic, liver, and renal disease
BACKGROUND
RESULTS
continued
METHODS
Scoring For Indices*
Component
Value
includes HIV infected Veterans and an age/race/site matched control group
of uninfected Veterans in care.
Age
Tissue Samples: In 2005-2006 we collected and banked blood and DNA
specimens on consenting subjects enrolled in VACS 8. 1532 HIV infected
participants consented to provide blood specimens. Blood specimens were
collected using serum separator and EDTA blood collection tubes. After
collection, blood specimens were shipped to a central repository.
CD4 Count
<50
50-64
>65
>500
350-499
200-349
100-199
50-99
<50
<500
500 to 5 log
>5 log
>14
12-13.9
10-11.9
<10
<1.45
1.45-3.24
>3.25
The Veterans Aging Cohort Study (VACS): VACS has been well described and
Clinical Laboratory Tests and Calculating the VACS Index: The VACS
Index is composed of routinely collected laboratory tests of organ system
functioning and age (Table 1). Since our initial publication, we have refined
the VACS Index by omitting variables that are increasingly uncommon
(AIDS defining Illnesses), variably associated with mortality (AIDS defining
Illnesses), or inconsistently measured across cohorts (AIDS defining
illnesses, diagnoses of substance abuse, hepatitis B co infection). The
Index is based on age and laboratory tests recommended in current HIV
care guidelines. Hepatitis C is considered present after a single sero
positive test until a subsequent test demonstrates viral clearance.
Markers of Inflammation: We selected soluble interleukin-6 (IL-6; systemic
inflammation), fibrin fragment D-dimer (procoagulant activity), and soluble
CD14 (sCD14; lipopolysaccharide-mediated monocyte activation) as
sentinel markers of inflammation because prior work suggests that these
represent important mechanisms for accelerated aging, end organ damage,
and mortality among those aging with HIV infection. Biochemical analyses
were performed at the Laboratory for Clinical Biochemistry Research at the
University of Vermont under the supervision of Dr. Russell Tracy.
(years)
(mm3)
HIV-1 RNA (copies/ml)
Hemoglobin
(g/dL)
FIB 4 =
(age*ALT/platelets
*sqrt(ALT)
eGFR =
186.3*creatinine-1.154
*age-0.203
Hepatitis C
Sero Status
>60
45-59.9
30-49.9
<30
Negative
Positive
VACS
Index
Restricted
Index
0
12
27
0
6
6
10
28
29
0
7
14
0
10
22
38
0
6
25
0
23
44
0
10
10
19
40
46
0
11
25
0
6
8
26
0
5
*Points for each component are summed.
Prognostic
Model
Sample Characteristics
We have developed the Veterans Aging Cohort Study Risk Index (VACS Index) and demonstrated that it accurately predicts
mortality among people initiating ART and those on ART for extended periods (see poster # 793). Here we explore whether
these markers are associated with the Index and whether addition of these markers improves prediction of mortality.
Total
Gender Male
Race
White
Black
Other
Age
<50
50 to 64
> 65
CD4
>500
350 to 499
300 to 349
100 to 299
50 to 99
< 50
VL
< 500
500 to < 5log
> 5log
Hgb
>14
12 to 13.9
10 to 11.9
< 10
Fib 4
< 1.45
1.45 to 3.25
>3.25
eGFR >60
45 to 59.9
30 to 49.9
< 30
Hep C Yes
N
1304
1265
251
892
114
489
740
73
434
297
279
155
69
68
915
317
70
664
483
139
16
714
460
128
1200
56
17
29
585
Discrimination* for 5 Year Mortality
(%)
(97.2)
(19.3)
(68.5)
(8.8)
(37.6)
(56.8)
(5.6)
(33.3)
(22.8)
(21.4)
(11.9)
(5.3)
(5.2)
(70.3)
(24.3)
(5.4)
(51.0)
(37.1)
(10.7)
(1.2)
(54.8)
(35.3)
(9.8)
(92.2)
(4.3)
(1.3)
(2.2)
(44.9)
Statistical Analyses: We compared the associations of the VACS Index, the Restricted Index and each of their components with IL-6, D-dimer, and sCD14. Because these markers
of inflammation are not normally distributed, we used spearman rank correlation to measure association. In nested Cox models we estimated the unadjusted and the adjusted
association of each marker of inflammation with mortality. Since we had complete data on 99.8% (1302/1304) of sampled subjects, we did not impute values. We then conducted
nested Cox regression models to determine whether IL-6, D-dimer, or sCD14 added independent prognostic information to the VACS Index by improving the discrimination of the
Index for all cause mortality.
Biomarker
VACS
Index
Restricted
Index
Alone
n/a
0.80
0.75
+IL-6
0.74
0.81
0.80
+D-dimer
0.73
0.82
0.80
+sCD14
0.72
0.81
0.80
+all three
0.76
0.82
0.80
*Discrimination measured using c statistics.
1.8
1.6
1.4
Restricted Index Score
1.2
D-dimer
Background: Composed of age and routine clinical data, the Veterans
Aging Cohort Study (VACS) Index is more predictive of mortality among
those with HIV infection than an index restricted to CD4 count, HIV-1
RNA, and age. We ask whether biomarkers of inflammation (IL-6),
coagulation (D-dimer), and lipopolysaccharide-mediated
monocyteactivation (sCD14) improve the prognostic discrimination of the
VACS index.
Methods: 1311 HIV infected subjects on cART from the VACS 8 Site
Study had samples drawn and analyzed for IL-6, d-dimer, and sCD14.
Using clinical tests performed closest to the date of sample collection, an
HIV Restricted Index, composed of age, CD4 count, and HIV-1 RNA was
compared to the VACS Index which also includes hemoglobin, AST, ALT,
platelet count, HCV antibody, and creatinine. We tested association using
Spearman correlation and predictive discrimination using C statistics
calculated from proportional hazards models.
Results: Among the 1311 patients on cART with samples, 77 died. The
VACS Index was correlated with each biomarker (0.36-0.42) and these
correlations were higher than for the HIV Restricted Index (0.24-0.29). In
multivariate analyses, the VACS Index (C statistic 0.80) was more
discriminating of mortality than any biomarker alone (C statistic 0.720.74), all three biomarkers together (C statistic 0.76) or the HIV Restricted
Index (C statistic 0.75) (p for all comparisons<0.001). Addition of these
biomarkers to the indices improved prediction for both indices but
discrimination remained superior for the VACS Index compared to the
Restricted Index (0.82 vs. 0.80. p<0.001). Results were similar when
stratified by level of viral suppression and HCV serostatus.
Conclusions: Biomarkers of inflammation, coagulation, and
lipopolysaccharide-mediated monocyte activation were highly correlated
with the VACS Index biomarkers
Correlation with Biomarkers
SUMMARY
The VACS Index is more strongly correlated with
biomarkers of inflammation, coagulation and
monocyte activation than an index restricted to CD4
count, HIV-1 RNA, and age. The VACS Index is also
more predictive of mortality than any of these
markers (alone or in combination) or than the
Restricted Index. Addition of D-dimer to the VACS
Index improves discrimination of mortality as much
as addition of all three.
CONCLUSION: The VACS Index is more
associated with markers of chronic inflammation and
mortality than the Restricted Index, but can be
improved by the addition of D dimer, a test that is
routinely available in clinical settings.
R² = 0.7748
1.0
0.8
0.6
0.4
0.2
0.0
0
20
40
60
80
100
1.8
1.6
1.4
VACS Risk Index score
1.2
D-dimer
ABSTRACT
R² = 0.961
1.0
0.8
0.6
0.4
0.2
0.0
0
20
40
60
80
100
SUPPORTING REFERENCES:
D'Arminio MA, et al. The changing incidence of AIDS events in patients receiving HAART. Arch Intern Med 2005;165(4):416-423.
Mocroft A, et al. Variable impact on mortality of AIDS-defining events diagnosed during cART. Clin Infect Dis 2009;48(8):1138-1151.
Justice AC, et al. Towards a combined prognostic index for survival in HIV infection. HIV Med 2009.
Sandler N, et al. Plasma Levels of Soluble CD14 Predict Mortality in HIV Infection. 17th CROI Abstract # 304. 2-16-0010.
Kuller LH, et al. Inflammatory and coagulation biomarkers and mortality in patients with HIV infection. PLoS Med 2008;5(10):e203.
Justice AC, et al. Veterans Aging Cohort Study (VACS). Med Care 2006;44(8 Suppl 2):S13-S24.
Aberg JA , et al. Primary care guidelines for the management of persons infected with HIV... Clin Infect Dis 2009;49(5):651-681.
Vallet-Pichard A, et al. FIB-4... Hepatology 2007;46(1):32-36.
Ravasi G, et al. Comparison of glomerular filtration rate estimates vs. 24-h creatinine clearance in HIV…. HIV Med 2009;10(4):219-228.
ACKNOWLEDGEMENT: supported by NIH: NIAAA (2U10AA13566) and NHLBI (3R01HL095136-03)