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Objectives Recent studies have shown that pre‐exposure prophylaxis (PrEP) can substantially reduce the chance of acquiring HIV infection. However, PrEP efficacy has been found to be compromised in macaque studies if the challenge virus is antiretroviral therapy (ART)‐resistant. Our objective was to evaluate the likelihood that a UK man who has sex with men (MSM) would be exposed to PrEP‐resistant HIV in a homosexual encounter with an HIV‐infectious partner. Methods Data from the UK Collaborative HIV Cohort (UK CHIC) study were linked to the UK HIV Drug Resistance Database for HIV‐1‐positive MSM patients seen between 2005 and 2008. Patients were categorized as undiagnosed; diagnosed but ART‐naïve; ART‐experienced and on treatment; and ART‐experienced and on a treatment interruption. Considering current PrEP regimens, resistance to (a) tenofovir (TDF) alone, (b) TDF and emtricitabine (FTC), and (c) TDF or FTC was estimated. Patients without resistance tests had PrEP resistance imputed using bootstrapping and logistic regression models. Results The population‐level prevalence of PrEP resistance in HIV‐infectious individuals in 2008 was estimated to be 1.6, 0.9 and 4.1% for PrEP resistance definitions a, b and c, respectively. Prevalence in ART‐experienced patients was highest, with negligible circulating resistance amongst ART‐naïve individuals. The levels of resistance declined over the period of study. Conclusions Our analysis indicates low levels of resistance to proposed PrEP drugs. The estimated PrEP resistance prevalence in UK HIV‐infected MSM is towards the lower range of values used in simulation studies which have suggested that circulating PrEP drug resistance will have a negligible impact on PrEP efficacy at the population level.

BACKGROUND: Recruitment to randomised clinical trials can be challenging and slow recruitment has serious consequences. This study aimed to summarise and reflect on the challenges in enrolling young children to a multidrug-resistant TB (MDR-TB) prevention trial in South Africa.METHODS: Recruitment to the Tuberculosis Child Multidrug-resistant Preventive Therapy Trial (TB-CHAMP) was tracked using an electronic recruiting platform, which was used to generate a recruiting flow diagram. Structured personnel questionnaires, meeting minutes and workshop notes were thematically analysed to elucidate barriers and solutions.RESULT: Of 3,682 (85.3%) adult rifampicin (RIF) resistant index cases with pre-screening outcomes, 1597 (43.4%) reported having no children under 5 years in the household and 562 (15.3%) were RIF-monoresistant. More than nine index cases were pre-screened for each child enrolled. Numerous barriers to recruitment were identified. Thorough recruitment planning, customised tracking data systems, a dedicated recruiting team with strong leadership, adequate resources to recruit across large geographic areas, and excellent relationships with routine TB services emerged as key factors to ensure successful recruitment.CONCLUSION: Recruitment of children into MDR-TB prevention trials can be difficult. Several MDR-TB prevention trials are underway, and lessons learnt from TB-CHAMP will be relevant to these and other TB prevention studies.

Introduction and objectivesThe current standard treatment for pulmonary tuberculosis (TB) has been in use for several decades and the major risks associated with each of the four drugs (HRZE) are well recognised. However, large prospective trials with regular review and documentation of adverse events while taking HRZE are lacking.We used the incidence of grade 3 and 4 adverse events (AEs) and serious adverse events (SAEs) in patients taking HRZE in the REMoxTB trial to investigate the overall tolerability of the regimen.MethodsGrade 3 or 4 AEs and SAEs (of any grade) for patients taking standard TB therapy were analysed. Events were labelled as occurring in the intensive phase, continuation phase or in follow-up (up to 18 months after enrolment). ANOVA and chi-square testing was used to test for significant differences in the incidence of events across the treatment phases. Logistic regression was used to investigate associations between baseline characteristics and on-treatment SAEs and withdrawal from treatment, death or relapse/treatment failure.Results201 (31.5%) of 639 patients taking standard therapy experienced grade 3/4 AEs or SAEs during treatment. AEs, SAEs, and withdrawals from treatment occurred most frequently in the intensive phase (see Table). Of 116 SAEs reported 84 (72.4%) improved or resolved and were most commonly respiratory (16.4%), gastrointestinal (6.9%), and infection (5.2%) related. There were 10 deaths in follow-up due to suicide, trauma, TB relapse, and acute illness. Logistic regression detected a significant association between on-treatment SAEs and withdrawal (p < 0.001) or death (p < 0.001), but not relapse/treatment failure (p = 0.611). HIV-positive status (OR 4.25, p = 0.016) and lower baseline weight (OR 1.46, p = 0.023) were associated with the reporting of on-treatment SAEs.DiscussionAEs and SAEs were predominantly reported in the intensive phase, probably due to a combination of TB and effects of medication. However most deaths occurred in follow-up and were unrelated, emphasising the impact that social circumstances have on TB patients. The lack of significant association between SAEs during treatment and relapse/treatment failure provides reassurance that a complicated treatment period can end with successful treatment of TB. The association between SAEs on treatment and lower weights at baseline and HIV infection reinforces the need to monitor these patients closely.Abstract P119 Table 1Intensive Phase(Month 0–2)n = 639Continuation Phase(Month 3–6)n = 596Follow Up Phase(Month 7–18)n = 569P valueNo of Grade 3 AEs Reported 663119***No. Grade 4 AEs Reported 1963***System Organ Class of Reported Grade 3 & 4 AEs Musculoskeletal 14700.102Metabolism & Nutrition 11060.006General Disorders 7310.838No of Grade 3 or 4 AEs per Patient 0 578574554<0.0011 491892 924≥3 322No of Patients with ≥1 SAE(Considered Related) 32(21)18(6)20(2)0.168Mean No of SAEs per Patient 1.781.391.600.092No of Withdrawals 38261<0.001No of Deaths 51100.014