1. Predictor factors associated with liver fibrosis and steatosis by transient elastography in HIV mono-infected patients under long-term combined antiretroviral therapy
Hugo Perazzo, Sandra W Cardoso, Carolyn Yanavich, João Carlos Soares, Juliana Fittipaldi, Michelle Morata, Claudia Cardoso, Paula Simplicio, Cristiane de Almeida, Valdilea G Veloso, Beatriz Grinsztejn
National Institute of Infectious Diseases Evandro Chagas (INI)
Oswaldo Cruz Foundation (FIOCRUZ)
Rio de Janeiro - Brazil
Abstract MOAB0305
HIV and Liver: Co-Infection and Complications
July 24th, 2017

2. Disclosures
The authors have nothing to disclosure

3. Background General population HIV – scare dataÇç l
HIV – scare data
Chronic inflammation and immune activation ?
Hepatotoxicity associated with c-ART ?

4. Aims
To evaluate factors associated with liver fibrosis and steatosis in HIV mono-infected patients under long-term combined-antiretroviral therapy (c-ART)

5. Methods Cohort of HIV patients at INI-FIOCRUZ Study design
~4,000 patients have been followed from 1990 (c-ART regimens, CD4 count, viral load, co-infections, AIDS-related events)
Study design
Cross-sectional study (PROSPEC-HIV; NCT )
Inclusion criteria
HIV infection
Exclusion criteria
Viral hepatitis co-infection
c-ART naïve

6. Methods Performed at the same day (fasting status)
Clinical evaluation: anthropometric measures, alcohol intake (AUDIT score), co-morbidities and co-medication use, history of HIV infection and c-ART treatment (current and previous)
Blood tests
Transient elastography by FibroScan ®
Parameter
Assessment
Cut-offs
LSM
Fibrosis
≥ 8.0 kPa †
CAP
Steatosis
≥ 250 dB/m §
Reliability criteria
10 valid measures
IQR/LSM < 30% / IQR/CAP < 30%
Success rate ≥ 60%
† Koehler et al Hepatology 2016
§ De Ledinghen et al J Hepatol 2014

7. Methods
Metabolic features / Metabolic syndrome: according to the International Diabetes Federation
Backbone ART:
AZT = use of AZT, ddI, ddC, D4T or ddI-EC
TDF = use of TDF, ABC, Emtricitabine or TAF
Core Drugs ART:
NNRTI = use of EFV, NVP, ETV, CAP or TMC
PI = use of any protease inhibithor
II = use of any integrase inhibithor
Cummulative ART: years of use and most used class of drug for Backbone and Core Drug

8. Methods Outcomes Multivariate Logistic regression
Liver fibrosis (LSM ≥ 8.0 kPa) in reliable LSM
Liver steatosis (CAP ≥ 250 dB/m ) in reliable CAP measures
Multivariate Logistic regression
Univariate analysis: p ≤ into multivariate model
Multivariate analysis adjusted for age, gender and confounding factors
Significance level: p < 0.05 two-tailed tests
STATA software (2017; StataCorp LP, TX, USA)

9. Flow-chart of the study

10. Characteristics of patients - I
All (n=395)
Female gender
236 (60%)
Age, years
45 [35-52]
Black/Mixed skin color
210 (53%)
Education level > 8 years of study
202 (51%)
AUDIT score ≥ 8
90 (23%)
Former or current smoking
184 (47%)
Metabolic features
BMI, Kg/m²
25.7 [ ]
Central obesity (WC > 94 cm in men and > 88 cm in women)
266 (68%)
Type-2 diabetes
37 (10%)
Dyslipidemia
234 (61%)
Hypertension
118 (30%)
Metabolic syndrome
117 (32%)
Biochemistry
ALT, IU/L
30 [23-42]
AST, IU/L
26 [20-34]
GGT, IU/L
46 [34-76]
Alkaline Phosphatase, IU/L
88 [69-107]
Total bilirubin, mg/dL
0.43 [ ]
Albumin, mg/dL
3.9 [ ]
Fasting glucose, mg/dL
93 [87-100]
Triglycerides, mg/dL
127 [87-178]
Total cholesterol, mg/dL
185 [ ]
LDL-cholesterol, mg/dL
112 [88-138]
HDL-cholesterol, mg/dL
42 [35-54]
Data expressed as n (%) or median [IQR]

11. Characteristics of patients - II
All (n=395)
HIV infection history
Duration of HIV infection, years
10 [6-16]
CD4 count (cells/mm3)
667 [ ]
HIV viral load > 40 copies/mm3
80 (20%)
Nadir CD4 < 100 cells/mm3)
104 (26%)
c-ART history
Duration of c-ART, years
7 [4-14]
Current treatment
Backbone drug classes
TDF
309 (78%)
AZT
86 (22%)
Core Drugs classes
NNRTI
175 (44%)
PI or II
220 (56%)
Most used drugs during HIV infection
225 (57%)
170 (43%)
197 (50%)
198 (50%)
Cummulative time of use of Backbone drugs, years
3 [1-6]
2 [0-9]
Cummulative time of use of Core Drugs, years
2 [1-6] PI
2 [0-7] II
0 [0-1]
Data expressed as n (%) or median [IQR]

12. Results Transient elastography by FibroScan (reliable exams)
Liver stiffness measurement
(n=367)
Fibrosis
LSM, kPa
5.3 [ ]
IQR, kPa
0.7 [ ]
IQR/LSM, %
13.3 [ ]
Sucess rate, %
100 [91-100]
LSM > 8.0 kPa
33 (9%)
Controlled Attenuation Parameter
(n=344)
Steatosis
CAP, dB/m
230 [ ]
IQR, dB/m
30 [23-39]
IQR/CAP, %
13.5 [ ]
CAP > 250 dB/m
121 (35%)
Data expressed as median [IQR]

13. Factors associated with fibrosis
Univariate Analysis
Multivariate Analysis
OR [95%CI]
p value
Social and demographics characteristics
Female gender
1.10 [ ]
0.805
1.04 [ ]
0.927
Age (per 10 years)
1.78 [ ]
< 0.001
1.80 [ ]
0.001
White skin color
1.44 [ ]
0.323
Education < 8 years of study
1.73 [ ]
0.143
AUDIT score ≥ 8
0.57 [ ]
0.258
Former or current smoking
1.21 [ ]
0.598
HIV infection history
Duration of HIV infection (per 10 years)
1.30 [ ]
0.306
CD4 count < 200 cells/mm3
3.69 [ ]
0.032
7.80 [ ]
0.002
HIV viral load > 40 copies/mm3
0.98 [ ]
0.957
Nadir CD4 < 100 cells/mm3
1.42 [ ]
0.338
c-ART history
Duration of c-ART (per 10 years)
1.55 [ ]
0.120
Current treatment
AZT Backbone drug class (vs TDF)
1.19 [ ]
0.691
PI or II Core Drugs class (vs NNRTI)
1.73 [ ]
0.154
Most used drugs during HIV infection
1.49 [ ]
0.275
1.44 [ ]
0.322
Metabolic features
Central obesity
1.21 [ ]
0.632
Type-2 diabetes
3.78 [ ]
0.006
2.67 [ ]
0.061
Dyslipidemia
1.03 [ ]
0.937
Hypertension
2.19 [ ]
0.038
1.30 [ ]
0.535
Biochemistry
ALT ≥ 1.5 ULN
3.40 [ ]
0.296
GGT ≥ 1.5 ULN
1.90 [ ]
0.161
Alkaline Phosphatases ≥ 1.5 ULN
1.29 [ ]
0.813

14. Factors associated with steatosis
Univariate Analysis
Multivariate Analysis
Model with
metabolic features
Metabolic syndrome
OR [95%CI]
p value
Social and demographics characteristics
Male gender
1.88 [ ]
0.006
6.06 [ ]
< 0.001
1.94 [ ]
0.015
Age (per 10 years)
1.48 [ ]
<0.001
0.99 [ ]
0.983
1.13 [ ]
0.318
White skin color
1.85 [ ]
0.007
1.45 [ ]
0.204
1.64 [ ]
0.067
Education < 8 years of study
0.77 [ ]
0.239
AUDIT score ≥ 8
0.86 [ ]
0.563
Former or current smoking
1.05 [ ]
0.818
HIV infection history
Duration of HIV infection (per 10 years)
1.76 [ ]
0.001
1.47 [ ]
0.408
1.34 [ ]
0.503
CD4 count < 200 cells/mm3
0.54 [ ]
0.355
HIV viral load > 40 copies/mm3
0.53 [ ]
0.034
0.58 [ ]
0.145
0.59 [ ]
0.133
Nadir CD4 < 100 cells/mm3
1.11 [ ]
0.647
c-ART history
Duration of c-ART (per 10 years)
1.72 [ ]
0.003
0.98 [ ]
0.966
1.17 [ ]
0.758
Current treatment
AZT Backbone drug class (vs TDF)
1.55 [ ]
0.102
PI or II Core Drugs class (vs NNRTI)
0.93 [ ]
0.737
Most used drugs during HIV infection
2.03 [ ]
0.002
1.62 [ ]
0.135
1.29 [ ]
0.410
0.91 [ ]
0.685
Metabolic features
Central obesity
4.27 [ ]
10.74 [ ]  - -
Type-2 diabetes
9.56 [ ]
9.74 [ ]
Dyslipidemia
5.34 [ ]
2.61 [ ]
0.004
Hypertension
1.96 [ ]
0.67 [ ]
0.253
Presence of metabolic syndrome
4.82 [ ]
4.28 [ ]
Biochemistry
ALT ≥ 1.5 ULN
1.84 [ ]
0.545
GGT ≥ 1.5 ULN
1.43 [ ]
0.264
Alkaline Phosphatases ≥ 1.5 ULN
0.91 [ ]
0.900

15. Correlation and collinearity
Variance Inflation Factor (VIF)
quantify the severity of multicollinearity
VIF < 1 = not correlated.
VIF = = moderately correlated
VIF > 5 = highly correlated
Multivariate Model for steatosis
Variable
VIF
Duration of c-ART
7.05
Duration of HIV infection
5.27
Duration of AZT Backbone
2.67
Age
1.58
Central obesity
1.55
Gender
1.46
Dyslipidemia
1.30
Hypertension
1.22
Type-2 diabetes
1.10
White skin color
1.08
HIV viral load
1.03

16. Sensitivity analysis Factors associated with steatosis
Multivariate Analysis
Model A
Model B
Model C
Duration of HIV infection
Duration on c-ART
Cumulative use of AZT BB
OR [95%CI]
p value
Social and demographics characteristics
Male gender
6.18 [ ]
< 0.001
6.36 [ ]
5.82 [ ]
Age (per 10 years)
1.01 [ ]
0.929
1.02 [ ]
0.920
1.07 [ ]
0.610
White skin color
1.45 [ ]
0.200
0.201
1.47 [ ]
0.186
HIV infection history
Duration of HIV infection (per 10 years)
1.64 [ ]
0.029
HIV viral load > 40 copies/mm3
0.58 [ ]
0.141
0.60 [ ]
0.165
c-ART history
Duration of c-ART (per 10 years)
1.68 [ ]
0.036
AZT BB as the most used ART (vs TDF)
1.90 [ ]
0.028
Metabolic features
Central obesity
10.35 [ ]
10.72 [ ]
10.75 [ ]
Type-2 diabetes
9.44 [ ]
9.30 [ ]
9.42 [ ]
Dyslipidemia
2.70 [ ]
0.003
2.74 [ ]
2.60 [ ]
0.004
Hypertension
0.66 [ ]
0.229
0.68 [ ]
0.266
0.69 [ ]
0.280
Variance Inflation Factor (VIF)
Absence of severe multicollinearity in Model A, B and C
Variables Model A
VIF
Age
1.55
Central obesity
Gender
1.45
Dyslipidemia
1.29
Duration of HIV infection
1.26
Hypertension
1.21
Type-2 diabetes
1.09
White skin color
1.08
HIV viral load
1.03
Variables Model B
VIF
Age
1.57
Central obesity
1.54
Gender
1.45
Dyslipidemia
1.29
Duration on c-ART
1.24
Hypertension
1.21
Type-2 diabetes
1.09
White skin color
1.08
HIV viral load
1.03
Variables Model C
VIF
Central obesity
1.54
Gender
1.44
Age
1.41
Dyslipidemia
1.30
Hypertension
1.21
Type-2 diabetes
1.09
AZT BB most used drug class
1.08
White skin color
HIV viral load
1.03

17. Conclusions In mono-infected HIV patients :
Low CD4 count was independently associated with presence of liver fibrosis by transient elastography
Metabolic features (central obesity, type-2 diabetes and dyslipidemia) and metabolic syndrome were independently associated with presence of liver steatosis by CAP
Higher duration of c-ART, especially by AZT as Backbone, was associated with steatosis independently of metabolic factors

18. Thank you for your attention
Acknowledgement
Participants of the PROSPEC-HIV study
Colleagues from LAPCLIN-AIDS at INI-FIOCRUZ
Agencies that have been supporting the PROSPEC study
Thank you for your attention