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Poorer adherence to medication is normal in adolescence and is one of a range of risk-taking behaviours common during a developmental stage that encompasses enormous cognitive, physical, sexual, social and emotional change. For adolescents living with human immunodeficiency virus (HIV) infection, poor adherence to antiretroviral therapy (ART) confers two significant challenges: poor health, but also the specific additional burden of onward transmission to partners. Late adolescence (15–19 years) is the only age group where HIV-associated mortality is rising, driven by poor adherence to ART and lack of access to second-line therapy, particularly amongst surviving perinatally infected young people. A previous lack of well-powered randomised multimodal behavioural ART adherence interventions specifically targeting adolescents is now being addressed and ongoing studies registered to ClinicalTrials.gov are described in the context of previous data. Accepting that despite enhanced support, some adolescents will continue to struggle with adherence, we must address how best to use existing ART agents to reduce mortality and allow adolescents the time to mature into adult life. Single-tablet regimens with a high genetic barrier to resistance based on integrase inhibitors and boosted protease inhibitors exist, but global access, in resource limited settings of young people living with HIV reside, is limited. Pragmatically, such regimens tolerate the intermittent adherence so characteristic of adolescence, preserving immune function, without the rapid evolution of resistance. The potential role of long-acting injectable ART, specifically cabotegravir and rilpivirine, is discussed and future strategies including ultra-long-acting drug-delivery systems and broadly neutralising monoclonal antibodies explored.

OBJECTIVES The aim of the study was to analyse the prevalence of integrase resistance mutations in integrase strand transfer inhibitor (INSTI)-experienced HIV-1-infected patients and its predictors. METHODS We selected HIV-1 integrase sequences from the Antiviral Response Cohort Analysis (ARCA) database, derived from INSTI-experienced patients between 2008 and 2017. Differences in the prevalence of resistance to raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG) were assessed by χ2 test and predictors of resistance were analysed by logistic regression. RESULTS We included 462 genotypes from INSTI-exposed individuals: 356 'INSTI-failing' patients and 106 'previously INSTI-exposed' patients (obtained a median of 42 weeks after INSTI discontinuation [interquartile range (IQR) 17-110 weeks]). Overall, at least low-level resistance (LLR) to any INSTI (Stanford 8.5 algorithm) was detected in 198 (42.9%) cases. The most frequent INSTI resistance mutation was N155H, followed by Q148H/K/R, G140A/C/S, E138A/K/T and Y143C/H/R. Y143R and E138A were more prevalent in viral subtype B versus non-B [5.2 versus 1.5%, respectively (P = 0.04), and 3.1 versus 0%, respectively (P = 0.02)]. Overall, the Q148H/K/R plus G140A/C/S and/or E138A/K/T pattern, defining an intermediate level of resistance to DTG, was detected in 70 (15%) cases. Independent predictors of at least LLR to any INSTI were current use versus past use of INSTIs, a lower genotypic sensitivity score (GSS) for contemporary antiretroviral drugs used, and having an integrase sequence obtained in calendar year 2016 as compared to 2008-2009. CONCLUSIONS The results support integrase resistance testing in INSTI-experienced patients. Emergence of INSTI resistance is facilitated by the reduced genetic barrier of the regimen as a consequence of resistance to companion drugs. However, INSTI resistance may become undetectable by standard population sequencing upon INSTI discontinuation.

Publisher's version (útgefin grein), Objectives There are currently few data on the long‐term risk of cancer and death in individuals taking raltegravir (RAL). The aim of this analysis was to evaluate whether there is evidence for an association. Methods The EuroSIDA cohort was divided into three groups: those starting RAL‐based combination antiretroviral therapy (cART) on or after 21 December 2007 (RAL); a historical cohort (HIST) of individuals adding a new antiretroviral (ARV) drug (not RAL) to their cART between 1 January 2005 and 20 December 2007, and a concurrent cohort (CONC) of individuals adding a new ARV drug (not RAL) to their cART on or after 21 December 2007. Baseline characteristics were compared using logistic regression. The incidences of newly diagnosed malignancies and death were compared using Poisson regression. Results The RAL cohort included 1470 individuals [with 4058 person‐years of follow‐up (PYFU)] compared with 3787 (4472 PYFU) and 4467 (10 691 PYFU) in the HIST and CONC cohorts, respectively. The prevalence of non‐AIDS‐related malignancies prior to baseline tended to be higher in the RAL cohort vs. the HIST cohort [adjusted odds ratio (aOR) 1.31; 95% confidence interval (CI) 0.95–1.80] and vs. the CONC cohort (aOR 1.89; 95% CI 1.37–2.61). In intention‐to‐treat (ITT) analysis (events: RAL, 50; HIST, 45; CONC, 127), the incidence of all new malignancies was 1.11 (95% CI 0.84–1.46) per 100 PYFU in the RAL cohort vs. 1.20 (95% CI 0.90–1.61) and 0.83 (95% CI 0.70–0.99) in the HIST and CONC cohorts, respectively. After adjustment, there was no evidence for a difference in the risk of malignancies [adjusted rate ratio (RR) 0.73; 95% CI 0.47–1.14 for RALvs. HIST; RR 0.95; 95% CI 0.65–1.39 for RALvs. CONC] or mortality (adjusted RR 0.87; 95% CI 0.53–1.43 for RALvs. HIST; RR 1.14; 95% CI 0.76–1.72 for RALvs. CONC). Conclusions We found no evidence for an oncogenic risk or poorer survival associated with using RAL compared with control groups., EuroSIDA was supported by the European Union's Seventh Framework Programme for research, technological development and demonstration under EuroCoord grant agreement no. 260694. Current support includes unrestricted grants from Bristol‐Myers Squibb, Gilead, GlaxoSmithKline LLC, Janssen R&D, Merck and Co. Inc. and Pfizer Inc. The participation of centres from Switzerland was supported by The Swiss National Science Foundation (Grant 108787). The study is also supported by a grant (grant number DNRF126) from the Danish National Research Foundation.

Paola Bagella,1 Giuseppe VL De Socio,2 Elena Ricci,3 Barbara Menzaghi,4 Canio Martinelli,5 Nicola Squillace,6 Paolo Maggi,7 Giancarlo Orofino,8 Leonardo Calza,9 Laura Carenzi,3 Benedetto Maurizio Celesia,10 Giovanni Penco,11 Antonio Di Biagio,12 Laura Valsecchi,3 Francesca Vichi,13 Valeria Colombo,14 Giustino Parruti,15 Chiara Dentone,16 Katia Falasca,17 Paolo Bonfanti,18 Giordano Madeddu1 On behalf of the C.I.S.A.I. Study Group, Italy 1Unit of Infectious Diseases, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy; 2Infectious Diseases Unit, Department of Medicine, Azienda Ospedaliero-Universitaria di Perugia, Santa Maria Hospital, Perugia, Italy; 3Department of Infectious Diseases, ASST Fatebenefratelli Sacco, Milan, Italy; 4Unit of Infectious Diseases, ASST della Valle Olona, Busto Arsizio, Italy; 5Unit of Infectious and Tropical Diseases, Careggi Hospital Florence, Florence, Italy; 6Infectious Diseases Unit, San Gerardo Hospital, University of Milano-Bicocca, Monza, Italy; 7Infectious Diseases Clinic, University of Bari, Policlinico Consorziale, Bari, Italy; 8Amedeo di Savoia Hospital Unit of Infectious Diseases, Torino, Italy; 9University of Bologna, Department of Infectious Diseases, S. Orsola Malpighi Hospital, Bologna, Italy; 10Unit of Infectious Diseases, Garibaldi Hospital, Catania, Italy; 11Infectious Diseases Unit, Galliera Hospital, Genoa, Italy; 12Unit of Infectious Diseases, IRCCS San Martino Hospital – IST, Genoa, Italy; 13Infectious Diseases Unit, Santa Maria Annunziata Hospital, Florence, Italy; 14Infectious Diseases Unit, University of Milan, DIBIC Luigi Sacco, Milan, Italy; 15Unit of Infectious Diseases, Pescara Hospital, Pescara, Italy; 16Unit of Infectious Diseases, Sanremo Hospital, Sanremo, Italy; 17Infectious Diseases Unit, University of Chieti, Chieti, Italy; 18Unit of Infectious Diseases, A. Manzoni Hospital, Lecco, Italy Abstract: Rilpivirine is associated with a good efficacy and safety profile. However, data from real-life settings are scarce. Methods: We investigated the durability, safety and efficacy of Rilpivirine-based antiretroviral therapy in a prospective, observational, multicenter study. Results: We enrolled 499 HIV-infected patients, 360 (72.1%) males, mean age 43.4 ± 10.5years, mean CD4 600 ± 327 cell/μL, mean HIV-RNA 3.80 ± 1.15 log10 cp/mL. After a median follow up of 16 months, 81 (16.2%) interruptions were reported, 36 (7.2%) of which for adverse events (16 of grade ≥3), most commonly neurological and gastrointestinal. We observed virological failures in only 8 (1.6%) patients. Naive patients showed a significant reduction in eGFR at week 24, 48 and 72 and in total cholesterol (TC)/HDL ratio at week 48 (p=0.007). In patients switching from PI we found a significant decrease at week 24 and 48 in TC and triglycerides at week 24, 48 and 72. eGFR showed a significant decrease at week 48 and 72. TC/HDL ratio showed a statistically significant decrease at week 24 (p=0.0008) and 72 (p=0.04). A significant increase at week 24 and 48 in AST and ALT values was observed. Patients switching from TDF/FTC/EFV showed a reduction in HDL, total cholesterol and triglycerides at week 24 and 48 and in eGFR at all follow up times. TC/HDL ratio showed a significant decrease at week 48 (p=0.01). CDC stage C and antiretroviral-experience (especially Protease Inhibitors) were associated with RPV discontinuation. Conclusion: In conclusion, our data confirm Rilpivirine efficacy, safety and tolerability with improvement in lipid profile. Although hepatic and renal events rarely caused discontinuation, liver and kidney parameters should be monitored. Keywords: HIV-1, combination antiretroviral therapy, NNRTI, cohort study, naive, experienced patients

We compared 2 rules-based genotype interpretation systems and real or virtual phenotype through a retrospective analysis of a prospective trial. Genotypes were determined with VircoGEN II (VIRCO) and were interpreted with either RetroGram 1.4 or TRUGENE HIV-1 (guidelines 3.0) or original virtual phenotype (Virtual Phenotype; VIRCO), as available in the year 2000. Among 188 human immunodeficiency virus (HIV) type 1 isolates, overall concordance (kappa agreement) was observed for the 2 rules-based systems, whereas striking discordances were noted between them and real and virtual phenotype interpretations for stavudine, didanosine, zalcitabine, abacavir, and amprenavir (kappa