Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Viremia copy-years: A measure of cumulative HIV burden among patients initiating antiretroviral therapy predicts long-term clinical outcomes Michael Mugavero 1, Sonia Napravnik 2, Stephen Cole 2, Joseph Eron 2, Bryan Lau 3, Heidi Crane 4, James Willig 1, Mari Kitahata 4, Michael Saag 1, and CFAR Network of Integrated Clinical Systems (CNICS) 1 University of Alabama at Birmingham, 2 University of North Carolina at Chapel Hill, 3 Johns Hopkins University, and 4 University of Washington
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Background Single plasma HIV viral load (VL) on combination antiretroviral therapy (cART) predicts clinical outcomes (Egger M et al. Lancet 2002;360:119-29, Chene G et al. Lancet 2003;362:679-86, Lanoy E et al. AIDS 2009;23: ) But a single VL value cannot capture effects of intermittent viral replication over time Therefore, we developed viremia copy-years (VCY) to capture longitudinal cumulative VL burden
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI087360
Viremia Copy-Years Estimate of cumulative HIV burden over time Example: 10,000 copy-years 1,000 c/mL per day for 10 years 10,000 c/mL per day for 1 year VCY approximated as time-weighted sum using trapezoidal rule: Cole SR et al. Am J Epidemiology 2010;171:
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Aims Evaluate patient factors associated with VCY following modern cART initiation Estimate the prognostic value of VCY following modern cART initiation
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Methods Cohort: CNICS 8-site US clinical cohort Kitahata et al., Int J Epi : Eligibility Criteria ART-naïve initiating therapy Initiated with modern cART PI/r or NNRTI-based regimen At least 12 months f/u from cART start Principal exposure: Viremia Copy-Years (VCY)
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Methods Relationships between patient factors and VCY Multivariable linear regression of log 10 VCY with robust variances Relationship between log 10 VCY and all- cause mortality Cox proportional hazards models
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Results: Study Population Characteristic (N=1906)N (%) or Median (IQR) Female381 (20%) Black724 (38%) Ritonavir-boosted PI591 (31%) Pre-cART CD4 cell count, cells/mm (55, 282) Pre-cART log 10 VL, copies/mL4.9 (4.4, 5.4) Follow-up, years3.5 (2.0, 5.4) VL measures contributed (n=24,105)11 (6, 17) VCY, log 10 copy-years/mL2.76 (2.21, 3.89) VCY, copy-years/mL575 (162, 7762)
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Results: Relationship between patient factors and VCY from modern cART initiation Patient Factorslog 10 VCY a 95% CIP value CD4 at cART-initiation (per 100 cell increase) , -0.03<0.01 Women , 0.63<0.01 Ritonavir-boosted PI b , 0.50<0.01 a Multivariable linear regression model controlling for CD4 at cART initiation, sex, initial cART, duration of treatment and site. b Measured at cART-initiation, comparison group are patients initiating an NNRTI- based regimen, intention to treat approach * Higher pre-cART VL was associated with greater VCY in bivariable but not multivariable models
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Results: Relationship between VCY and all- cause mortality from modern cART initiation a Multivariable Cox proportional hazards model controlling for pre-cART VL, peak VL, time-updated VL, time-updated CD4, age, sex, initial cART (cART switches / discontinuations were not included), HIV acquisition mode, and site Hazard Ratio a 95% CIP value VCY, log 10 copy-years/mL , Pre-cART VL, log 10 copies/mL , Peak VL on cART, log 10 copies/mL , Time-updated VL, log 10 copies/mL , Time-updated CD4 (per 100 cell increase) , 0.85<0.01
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Conclusions VCY, an estimate of cumulative HIV burden, was associated with several patient characteristics following cART-initiation Independent of cross-sectional VL and CD4 cell count Among patients initiating modern cART regimens VCY had demonstrable prognostic value for all-cause mortality Independent of cross-sectional and time-updated VL and CD4 measures, and other patient factors
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Conclusions Future studies of VCY will include: Evaluating the effect of VCY on clinical outcomes among specific groups of patients, including those with low- level or intermittent viremia Estimating the relationship between VCY and AIDS- and non-AIDS events Assessing relationships between VCY and markers of inflammation and immune activation
Supported by: NIAID/NHLBI R24 AI067039, NIAID R21 AI Acknowledgements Co-authors CNICS patients CNICS site PIs & co-investigators Stephen Van Rompaey Donna Porter CNICS site staff