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Background: Polypharmacy (use of ≥ five medications) increases the risk of drug-drug interactions and can lead to negative health outcomes. This study aimed to review the medications of people living with HIV (PLWH) and HIV-negative controls in the POPPY study and evaluate the frequency of polypharmacy and potential drug-drug interactions (PDDIs)., Methods: PDDIs between non-antiretroviral (ARV) drugs were analysed using the Lexicomp ® database, and PDDIs between non-ARV and ARV drugs using the Liverpool drug interaction database. Between-group differences were assessed using χ 2 , Mann-Whitney U and Kruskal-Wallis tests., Results: This analysis included 698 PLWH ≥50 years, 374 PLWH <50 years and 304 HIV-negative controls ≥50 years. The prevalence of polypharmacy was 65.8% in older PLWH, 48.1% in younger PLWH and 13.2% in the HIV-negative group. When ARVs were excluded, 29.8% of older PLWH and 14.2% of younger PLWH had polypharmacy. The prevalence of ≥1 PDDI involving non-ARV drugs was 36.1%, 20.3% and 16.4%, respectively, in older PLWH, younger PLWH and HIV-negative controls. In PLWH the prevalence of ≥1 PDDI involving ARV and non-ARV drugs was 57.3% in older PLWH and 32.4% in younger PLWH., Conclusions: Polypharmacy and PDDIs involving non-ARV/ARV drugs and non-ARV/non-ARV drugs were common among older PLWH, highlighting the need for increased awareness and additional research on all types of PDDI.

Background: To analyse the effect of drug resistance mutations (DRM) on CD4 + T-cell (CD4) trends in HIV-positive people maintained on virologically failing antiretroviral therapy (ART)., Methods: Individuals from two large cohorts experiencing virological failure (VF) while maintained on ART with ≥1 CD4 count and ≥1 resistance test were included. CD4 slopes were estimated using linear mixed models. Principal component analysis (PCA) was used to assess the effect of clusters of mutations, defined using extracted component based scores from the PCA, on CD4 decline., Results: 5,357 individuals contributing 7,661 VF episodes were included: any DRM were detected in 88.8% of episodes. After adjustment, CD4 counts declined less steeply during episodes where DRM were detected compared to episodes with no DRM (difference =28 cells/mm 3 /year, 95% CI =18, 39; P<0.001). Among individuals with at least one DRM, we found evidence that any nucleoside/nucleotide reverse transcriptase inhibitor (NRTI) resistance, the reverse transcriptase (RT) mutations M184V, D67N and T215Y as well as the protease mutations V82A and I54V were associated with reduced CD4 declines. The detection of any non-nucleoside reverse transcriptase inhibitor resistance, the RT mutations V179D and L74V were associated with steeper CD4 declines. The presence of some mutation patterns similar to the clusters identified by the PCA also affected the CD4 decline., Conclusions: Detection of resistance and of certain DRM during VF of ART has a small but significant favourable effect on CD4 decline.

Background: Antiretroviral (ART) drugs have been associated with higher triglycerides (TG), higher total cholesterol (TC) and lower high-density lipoprotein cholesterol (HDL-C) levels. Associations between lipid levels with HIV viraemia and immunosuppression in the presence of ART remain unclear., Methods: Participants from the D:A:D study with at least one TG/TC/HDL-C measurement were included. Linear mixed effect models were used to determine the association of ART, viral load (VL), nadir and current CD4 + T-cell count and previous AIDS diagnosis with lipids., Results: Of 49,717 participants, 90%, 92% and 80% contributed at least one TG/TC/HDL-C measurement (median follow-up 6.8, 6.8 and 5.0 years, respectively). Predicted mean (95% CI) baseline levels for TG, TC and HDL-C (mmol/l), were 2.10 (2.05, 2.14), 4.94 (4.91, 4.98) and 1.08 (1.07, 1.10), respectively. Lopinavir was associated with the worst TG profile, (27.2% higher levels compared to atazanavir; 95% CI 25.2%, 29.2%), and darunavir had a similar profile as atazanavir. The nucleoside pair lamivudine/tenofovir was associated with the most favourable TG profile (-2.8%; -3.5%, -2.0%) compared with emtricitabine/tenofovir, whereas lamivudine/abacavir (+10.2%; +9.3%, +11.2%) and lamivudine/stavudine (+8.0%; +6.9%, +9.0%), were associated with the worst. Raltegravir was associated with lower TG (-5.2%; -6.4%, -3.9%), and nevirapine had a more favourable HDL-C profile (+11.3%; +10.8%, +11.7%) than efavirenz (+5.3%; 5.0%, 5.7%), compared to atazanavir. Higher VLs were associated with lower TG/TC/HDL-C, whereas higher CD4 + T-cell counts were associated with higher TG/TC/HDL-C., Conclusions: TG, TC and HDL-C levels, which generally improved over time, are dependent on ART, viraemia and, to a lesser extent, immunosuppression.

Accurate estimates of HIV prevalence in Europe are hampered by incomplete reporting of new HIV diagnoses. Defining the epidemiology of late presentation is even more challenging. In Europe, the most common definitions of late presentation are based on CD4(+) T-cell counts, but there is little consistency among definitions. Thus, estimates of the incidence of late presentation vary widely between studies and across Europe, making comparative analysis difficult. Late presentation has been observed to be common in all demographic groups, but certain factors indicate greater risk for late presentation, including intravenous drug use, older age, foreign birth and non-White ethnicity. Standardizing the definition of late presentation will facilitate understanding, clinical research and, ultimately, effective treatment of late-presenting patients.

Background: Data on a link between HCV or HBV infection and the development of cardiovascular disease among HIV-negative and HIV-positive individuals are conflicting. We sought to investigate the association between HBV or HCV infection and myocardial infarction in HIV-infected individuals., Methods: The prospective observational database of the D:A:D collaboration of 11 cohorts of HIV-infected individuals, including 212 clinics in Europe, the United States and Australia was used. Multivariate Poisson regression was used to assess the effect of HCV or HBV infection on the development of myocardial infarction after adjustment for potential confounders, including cardiovascular risk factors, diabetes mellitus and exposure to antiretroviral therapy., Results: Of 33,347 individuals, 517 developed a myocardial infarction over 157,912 person-years, with an event rate of 3.3 events/1,000 person-years (95% confidence interval [CI] 3.0-3.6). Event rates (95% CIs) per 1,000 person-years in those who were HCV-seronegative and HCV-seropositive were 3.3 (3.0-3.7) and 2.7 (2.2-3.3), respectively, and for those who were HBV-seronegative, had inactive infection or had active infection were 3.2 (2.8-3.5), 4.2 (3.1-5.2) and 2.8 (1.8-3.9), respectively. After adjustment, there was no association between HCV seropositivity (rate ratio 0.86 [95% CI 0.62-1.19]), inactive HBV infection (rate ratio 1.07 [95% CI 0.79-1.43]) or active HBV infection (rate ratio 0.78 [95% CI 0.52-1.15]) and the development of myocardial infarction., Conclusions: We found no association between HBV or HCV coinfection and the development of myocardial infarction among HIV-infected individuals.

Background: In recent years, several new drugs from the protease inhibitor (PI) class designed to treat HIV infection have become available and the use of ritonavir-boosting has increased in popularity. These changes might be expected to affect the prevalence and patterns of protease resistance in the population of patients who experience treatment failure., Methods: The UK HIV Drug Resistance Database aims to capture the results of all genotypic resistance tests conducted nationally. Tests on antiretroviral therapy-experienced patients were identified through linkage with the UK Collaborative HIV Cohort Study, from which detailed clinical information on these patients, including a full antiretroviral therapy history, was obtained., Results: Analyses were on the basis of 8,553 genotypic resistance tests carried out between 1998 and 2005, during which time the overall prevalence of protease resistance halved from 35% to 16%. Substantial declines were observed regardless of whether the patient had been exposed to unboosted PIs and/or boosted PIs. The frequency of protease resistance among patients who had received boosted PIs fell sharply until 2002 with a weaker trend thereafter, falling to 12% in 2005. Individual mutations L33F, M461/L, V82A/F/T/S/L and 184V became relatively more frequent over the period of study., Conclusions: The decline in protease resistance was partly due to increasing use of ritonavir-boosting. Nonetheless, the prevalence of resistance was higher than suggested by clinical trials, indicating that prolonged exposure to a boosted PI could ultimately select for major protease mutations.

Background: The aim of this study was to examine factors influencing plasma concentration of efavirenz and nevirapine., Methods: Data from the Liverpool Therapeutic Drug Monitoring (TDM) registry were linked with the UK Collaborative HIV Cohort (CHIC) Study. For each patient, the first measurement of efavirenz (600 or 800 mg/day) or nevirapine (400 mg/day) plasma concentration was included. Linear regression was used to evaluate the association of dose, gender, age, weight, ethnicity and concomitant antiretroviral drugs or rifampicin with log-transformed drug concentration, adjusted for time since last intake., Results: Data from 339 patients on efavirenz (34% black, 17% rifampicin) and 179 on nevirapine (27% black, 6% rifampicin) were included. Multivariable models revealed the following predictors for efavirenz concentration: black ethnicity (59% higher; P<0.001), weight (10% lower per additional 10 kg; P=0.002), 800 mg/day (52% higher; P=0.027), rifampicin (35% lower; P=0.039), and zidovudine (25% lower; P=0.010). Notably, without adjustment for other factors, patients on rifampicin had 48% higher efavirenz concentration, as these patients were mostly black and on 800 mg/day. For nevirapine the predictors were black ethnicity (39% higher; P=0.002), rifampicin (40% lower; P=0.002), protease inhibitor (28% higher; P=0.008) and tenofovir (22% higher; P=0.024)., Conclusions: We observed clear associations between ethnicity and concentrations of nevirapine and efavirenz. Our analyses confirm that concomitant rifampicin substantially decreases concentration of both efavirenz and nevirapine; however, for efavirenz this effect was more than counterbalanced by the effect of ethnicity and increased efavirenz dose. There was also an additional impact of weight, which should be considered when determining optimal dosage. Other associations from our analysis (between tenofovir or protease inhibitor and nevirapine, and zidovudine and efavirenz), require confirmation in formal pharmacokinetic studies.