Similar but different: Integrated phylogenetic analysis of Austrian and Swiss HIV-1 sequences reveal differences in transmission patterns of the local HIV-1 epidemics.

OBJECTIVES Phylogenetic analyses of two or more countries allow to detect differences in transmission dynamics of local HIV-1 epidemics beyond differences in demographic characteristics. METHODS A maximum-likelihood phylogenetic tree was built using pol-sequences of the Swiss HIV Cohort Study (SHCS) and the Austrian HIV Cohort Study (AHIVCOS), with international background sequences. Three types of phylogenetic cherries (clusters of size 2) were analyzed further: 1) Domestic cherries, 2) International cherries and 3) SHCS/AHIVCOS-cherries. Transmission group and ethnicities observed within the cherries were compared to the respective distribution expected from a random distribution of patients on the phylogeny. RESULTS The demographic characteristics of the AHIVCOS (included patients: 3'141) and the SHCS (included patients: 12'902) are very similar. In the AHIVCOS, 36.5% of the patients were in domestic cherries, 8.3% in international cherries, and 7.0% in SHCS/AHIVCOS cherries. Similarly, in the SHCS, 43.0% of the patients were in domestic cherries, 8.2% in international cherries, and 1.7% in SHCS/AHIVCOS cherries. While international cherries in the SHCS were dominated by heterosexuals (HET) with MSM being underrepresented, the opposite was the case for the AHIVCOS. In both cohorts, cherries with one patient belonging to the transmission group intravenous drug user (IDU) and the other one non-IDU were underrepresented. CONCLUSION In both cohorts, international HIV transmission plays a major role in the local epidemics, mostly driven by MSM in the AHIVOS, and by HET in the SHCS, highlighting the importance of international collaborations to understand global HIV transmission links on the way to eliminate HIV

A Lower CD4 Count Predicts Most Causes of Death except Cardiovascular Deaths. The Austrian HIV Cohort Study

(1) Objective: To investigate changes in mortality rates and predictors of all-cause mortality as well as specific causes of death over time among HIV-positive individuals in the combination antiretroviral therapy (cART) era. (2) Methods: We analyzed all-cause as well as cause-specific mortality among the Austrian HIV Cohort Study between 1997 and 2014. Observation time was divided into five periods: Period 1: 1997-2000; period 2: 2001-2004; period 3: 2005-2008; period 4: 2009-2011; and period 5: 2012-2014. Mortality rates are presented as deaths per 100 person-years (d/100py). Potential risk factors associated with all-cause mortality and specific causes of death were identified by using multivariable Cox proportional hazard models. Models were adjusted for time-updated CD4, age and cART, HIV transmission category, population size of residence area and country of birth. To assess potential nonlinear associations, we fitted all CD4 counts per patient using restricted cubic splines with truncation at 1000 cells/mm$^{3}$. Vital status of patients was cross-checked with death registry data. (3) Results: Of 6848 patients (59,704 person-years of observation), 1192 died: 380 (31.9%) from AIDS-related diseases. All-cause mortality rates decreased continuously from 3.49 d/100py in period 1 to 1.40 d/100py in period 5. Death due to AIDS-related diseases, liver-related diseases and non-AIDS infections declined, whereas cardiovascular diseases as cause of death remained stable (0.27 d/100py in period 1, 0.10 d/100py in period 2, 0.16 d/100py in period 3, 0.09 d/100py in period 4 and 0.14 d/100py in period 5) and deaths due to non-AIDS-defining malignancies increased. Compared to latest CD4 counts of 500 cells/mm$^{3}$, lower CD4 counts conferred a higher risk of deaths due to AIDS-related diseases, liver-related diseases, non-AIDS infections and non-AIDS-defining malignancies, whereas no significant association was observed for cardiovascular mortality. Results were similar in sensitivity analyses where observation time was divided into two periods: 1997-2004 and 2005-2014. (4) Conclusions: Since the introduction of cART, risk of death decreased and causes of death changed. We do not find evidence that HIV-positive individuals with a low CD4 count are more likely to die from cardiovascular diseases

Factors associated with low-level viraemia and virological failure: results from the Austrian HIV Cohort Study

BACKGROUND: In human immunodeficiency virus treatment adequate virological suppression is warranted, nevertheless for some patients it remains a challenge. We investigated factors associated with low-level viraemia (LLV) and virological failure (VF) under combined antiretroviral therapy (cART). MATERIALS AND METHODS: We analysed patients receiving standard regimens between 1st July 2012 and 1st July 2013 with at least one viral load (VL) measurement below the quantification limit (BLQ) in their treatment history. After a minimum of 6 months of unmodified cART, the next single VL measurement within 6 months was analysed. VF was defined as HIV RNA levels ≥200 copies/mL and all other quantifiable measurements were classified as LLV. Factors associated with LLV and VF compared to BLQ were identified by logistic regression models. RESULTS: Of 2276 participants, 1972 (86.6%) were BLQ, 222 (9.8%) showed LLV and 82 (3.6%) had VF. A higher risk for LLV and VF was shown in patients with cART interruptions and in patients with boosted PI therapy. The risk for LLV and VF was lower in patients from centres using the Abbott compared to the Roche assay to measure VL. A higher risk for LLV but not for VF was found in patients with a higher VL before cART [for >99.999 copies/mL: aOR (95% CI): 4.19 (2.07-8.49); for 10.000-99.999 copies/mL: aOR (95% CI): 2.52 (1.23-5.19)] and shorter cART duration [for <9 months: aOR (95% CI): 2.59 (1.38-4.86)]. A higher risk for VF but not for LLV was found in younger patients [for <30 years: aOR (95% CI): 2.76 (1.03-7.35); for 30-50 years: aOR (95% CI): 2.70 (1.26-5.79)], people originating from high prevalence countries [aOR (95% CI): 2.20 (1.09-4.42)] and in male injecting drug users [aOR (95% CI): 2.72 (1.38-5.34)]. CONCLUSIONS: For both VF and LLV, factors associated with adherence play a prominent role. Furthermore, performance characteristics of the diagnostic assay used for VL quantification should also be taken into consideration