1. Long-term alcohol use patterns and HIV disease severity in U. S
Long-term alcohol use patterns and HIV disease severity in U.S. veterans: A joint trajectory analysis
Brandon D.L. Marshall, PhD1
Janet P. Tate, ScD2,3,4
Kathleen A. McGinnis, DrPH, MS2
David A. Fiellin, MD3,4
Kendall J. Bryant, PhD5
Amy C. Justice, MD, MSc, PhD2,3,4
Department of Epidemiology, Brown University School of Public Health
VA Connecticut Healthcare System
Department of Internal Medicine, Yale University School of Medicine
Center for Interdisciplinary Research on AIDS, Yale University
National Institute on Alcohol Abuse and Alcoholism

2. Alcohol Use & HIV Disease Progression
Unhealthy alcohol use…
Adversely affects ART adherence and retention in care
Has direct effects on the immune system
Increases risk of mortality at lower levels of alcohol use among HIV-infected persons (Justice et al., 2016)

3. Study Context & Objective
Effect of long-term alcohol use patterns on HIV disease progression unclear
Objective: Characterize alcohol use trajectories and their relationship with HIV disease severity over time
Hypothesis: persistent unhealthy drinking patterns associated with more advanced HIV disease severity over time
Most studies measure alcohol use cross-sectionally or at only a few time points.
Classification of long-term alcohol use phenotypes could help to identify patients with alcohol use patterns that increase risk of long-term HIV disease morbidity and mortality.

4. Veterans Aging Cohort Study – Survey Sample
Participants enrolled at 8 US sites
Six waves of data collection, ~annually
Survey data linked to electronic medical records
Mortality from VA vital status file
3,631 HIV-infected participants enrolled between June 2002 and Sept 2010

5. Outcomes Alcohol use ascertained using AUDIT-C
Validated screening tool measuring quantity, frequency, and binge alcohol use
Scores range from 0 to 12
Values ≥4 considered unhealthy alcohol use in men

6. Outcomes VACS Index Score
Prognostic indicator of morbidity and mortality in HIV-infected persons
Score is created by summing points for indicators of HIV disease and organ system injury
Each 5-point increase indicates 20% increased risk of 5-year mortality

7. Trajectory Modeling
Sort each participant’s string of values into “clusters” to estimate distinct trajectories
Participants assigned to the trajectory with the highest probability of membership
Model selection based on:
Average membership probability
Fit statistics (i.e., BIC)
A priori clinical criteria
Probability greater than 0.7 indicate adequate internal reliability.
A priori clinical criteria includes trajectories that are at least one point different on the AUDIT-C, and 5-points different on the VACS index.

8. Multinomial Logistic Regression
Estimate odds of membership in each VACS index trajectory, conditional on AUDIT-C group and other confounding covariates
Applied inverse probability of censoring weights (IPCW) to mitigate biases from loss to follow-up
Three sets of sensitivity analyses conducted
conditional on AUDIT-C group membership and other covariates
Sensitivity analyses:
Restricted trajectory analyses to persons who completed >2 study assessments
Excluded persons who died during the study
Applied last value carry forward (LVCF) to participants who dropped out

9. VACS Tissue Repository & PEth
Blood collected from 1,499 HIV+ in
Tested for phosphatidylethanol (PEth)
Direct biomarker of past 21-day alcohol exposure
High specificity for alcohol abstinence
Examine mean concentration and proportion above limit of detectability (≥4 ng/ml)

10. Results
3,539 participants contributed 15,354 person- years of follow-up
The median age was 49 (IQR: 44-55)
98% men and 68% African American
At baseline:
42% had a viral load <400 copies/ml
Median AUDIT-C score was 1 (IQR: 0-4)
Median VACS index score was 29 (IQR: 17-46)

11. Alcohol Use Trajectories
Moderate Risk (24%)
Note: dashed lines represent predicted values and error bars represent 95% confidence intervals for each wave’s estimate; solid lines represent empirical averages

12. Validating Alcohol Trajectories Using PEth
Note: PEth concentration values ≥4 ng/ml were considered above the limit of detection
Note: AUDIT-C group trajectories and the proportion of participants with PEth above the limit of detection were highly correlated (Cramér’s V = 0.465, p < 0.001)

13. VACS Index Trajectories
Note: dashed lines represent predicted values and error bars represent 95% confidence intervals for each wave’s estimate; solid lines represent empirical averages

14. VACS Index Trajectory Group
Associations with VACS Index Trajectories
Baseline Characteristic
VACS Index Trajectory Group
p-value
Low
N = 68 (2%)
Moderate
N = 1629 (46%)
High
N = 1290 (36%)
Extreme
N = 552 (16%)
Age (median, IQR)
42 (38–44)
46 (41–51)
52 (47–56)
53 (48–58)
<0.001
CD4 count (median, IQR cells/mL)
719 (638–904)
450 (310–620)
309 (187–483)
170 (6 –331)
Virally suppressed (<400 copies/mL)
48 (71)
782 (48)
484 (38)
169 (30)
HCV positive
0 (0)
599 (37)
799 (62)
394 (71)
Race
White
26 (39)
447 (28)
271 (22)
83 (16)
African American
37 (55)
1042 (66)
909 (73)
407 (78)
Other
4 (6)
91 (6)
58 (5)
29 (6)
Current smoker
27 (40)
838 (52)
709 (55)
306 (56)
Injection drug use, ever
10 (15)
400 (25)
517 (41)
243 (52)
Died during study period
241 (15)
469 (36)
391 (71)

15. AUDIT-C Trajectory Group
Joint Trajectory Results
AUDIT-C Trajectory Group
Association between membership in VACS index score trajectory and AUDIT-C score trajectory is statistically significant (p < 0.001)

16. Adjusted Odds Ratio (95% CI)
Final Weighted Multinomial Logistic Regression
Characteristic
VACS Index Trajectory Group
Adjusted Odds Ratio (95% CI)
p-value
Low
Moderate
High
Extreme
AUDIT-C Group
REF
0.002
Abstainers
1.92 (1.07 – 3.44)
1.18 (0.96 – 1.47)
1.90 (1.40 – 2.57)
Lower Risk
1.07 (0.64 – 1.79)
1.14 (0.95 – 1.36)
1.35 (1.02 – 1.79)
Moderate Risk
Higher Risk
1.21 (0.89 – 1.63)
1.83 (1.21 – 2.78)
Results of all sensitivity analyses were similar.
Model adjusted for age, race, education, marital status, and history of injection drug use

17. Strengths & Limitations
Study restricted to veterans receiving care, predominately male sample
IPCW to mitigate bias from loss to follow-up
First study to validate long-term, self-reported alcohol use patterns with biomarker (PEth)

18. Take Away Points
Persistent unhealthy alcohol use associated with greater HIV disease severity over time
Targeted risk reduction and treatment needed
Trajectory methods to identify novel risk factors for long-term unhealthy alcohol use?
Poorer adherence to therapy
Alcohol-mediated alterations in immune function
Fewer drinks to get a “buzz”

19. Acknowledgements
Robert L. Cook, E. Jennifer Edelman, Julie R. Gaither, Christopher W. Kahler, & Don Operario
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
U24-AA (PI: D. Operario)
U10-AA13566, U01-AA020790, U24-AA (PI: A.C. Justice)
U01-AA020795, R01-DA (PI: D.A. Fiellin)
National Institute of Allergy and Infectious Diseases (NIAID)
P01-AA (PI: C.W. Kahler)
P30-AI (PI: C. Carpenter)
Brown University Henry Merrit Wriston Fellowship

20. Thank you! Brandon DL Marshall, PhD
Manning Assistant Professor of Epidemiology
Department of Epidemiology
Brown University School of Public Health

21. Adjusted Odds Ratio (95% CI)
Weighted Multinomial Logistic Regression
Characteristic
VACS Index Trajectory Group
Adjusted Odds Ratio (95% CI)
p-value
Low
Moderate
High
Extreme
AUDIT-C Group
REF
0.002
Abstainers
1.92 (1.07 – 3.44)
1.18 (0.96 – 1.47)
1.90 (1.40 – 2.57)
Lower Risk
1.07 (0.64 – 1.79)
1.14 (0.95 – 1.36)
1.35 (1.02 – 1.79)
Moderate Risk
Higher Risk
1.21 (0.89 – 1.63)
1.83 (1.21 – 2.78)
Age (per unit increase)*
0.94 (0.91 – 0.96)
1.12 (1.10 – 1.12)
1.13 (1.12 – 1.15)
<0.001
Race (ref: White)
African American
0.42 (0.26 – 0.66)
1.80 (1.52 – 2.14)
2.58 (1.98 – 3.38)
Other
0.41 (0.16 – 1.05)
1.44 (1.01 – 2.04)
2.41 (1.47 – 3.95)
>High school education
1.30 (0.80 – 2.13)
0.77 (0.66 – 0.90)
0.69 (0.56 – 0.84)
Marital status (ref: Married/Co-Hab.)
0.006
Divorced/separated/widowed
1.35 (0.71 – 2.58)
1.03 (0.85 – 1.24)
1.56 (1.18 – 2.07)
Never married
2.06 (1.16 – 3.64)
1.00 (0.82 – 1.21)
1.28 (0.96 – 1.73)
Injection drug use, ever
0.57 (0.31 – 1.08)
1.77 (1.52 – 2.07)
2.03 (1.64 – 2.52)

23. AUDIT-C Last Value Carry Foward
Slightly fewer participants in the high risk category