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

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)

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.

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

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

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 http://vacs.med.yale.edu

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.

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

VACS Tissue Repository & PEth Blood collected from 1,499 HIV+ in 2005-2006 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)

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)

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

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)

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

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)

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)

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

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)

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”

Acknowledgements Robert L. Cook, E. Jennifer Edelman, Julie R. Gaither, Christopher W. Kahler, & Don Operario National Institute on Alcohol Abuse and Alcoholism (NIAAA) U24-AA022000 (PI: D. Operario) U10-AA13566, U01-AA020790, U24-AA020794 (PI: A.C. Justice) U01-AA020795, R01-DA035616 (PI: D.A. Fiellin) National Institute of Allergy and Infectious Diseases (NIAID) P01-AA019072 (PI: C.W. Kahler) P30-AI042853 (PI: C. Carpenter) Brown University Henry Merrit Wriston Fellowship

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

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)

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