Observational cohort study of rilpivirine (RPV) utilization in Europe

INTRODUCTION: Data on safety and effectiveness of RPV from the real-world setting as well as comparisons with other NNRTIs such as efavirenz (EFV) remain scarce. METHODS: Participants of EuroSIDA were included if they had started a RPV- or an EFV-containing regimen over November 2011-December 2017. Statistical testing was conducted using non-parametric Mann-Whitney U test and Chi-square test. A logistic regression model was used to compare participants' characteristics by treatment group. Kaplan-Meier analysis was used to estimate the cumulative risk of virological failure (VF, two consecutive values > 50 copies/mL). RESULTS: 1,355 PLWH who started a RPV-based regimen (11% ART-naïve), as well as 333 initiating an EFV-containing regimen were included. Participants who started RPV differed from those starting EFV for demographics (age, geographical region) and immune-virological profiles (CD4 count, HIV RNA). The cumulative risk of VF for the RPV-based group was 4.5% (95% CI 3.3-5.7%) by 2 years from starting treatment (71 total VF events). Five out of 15 (33%) with resistance data available in the RPV group showed resistance-associated mutations vs. 3/13 (23%) among those in the EFV group. Discontinuations due to intolerance/toxicity were reported for 73 (15%) of RPV- vs. 45 (30%) of EFV-treated participants (p = 0.0001). The main difference was for toxicity of central nervous system (CNS, 3% vs. 22%, p  50 copies/mL and resistance in participants treated with RPV were similar to those reported by other studies. RPV safety profile was favourable with less frequent discontinuation due to toxicity than EFV (especially for CNS)

The effect of a treatment switch to integrase Strand transfer inhibitor–based regimens on weight gain and other metabolic syndrome-related conditions

Abstract Objective This study aimed to assess weight gain associated with treatment switching to INSTI-based regimens in people living with HIV (PLWH) and to determine whether it is accompanied by worsening features of hypertension, dyslipidemia, or hyperglycemia. Methods In this two-center retrospective observational study, we assessed weight gain and metabolic features in PLWH who switched to an INSTI-based regimen (study group) as compared to patients who remained on a non-INSTI regimen (control group) over a 24-month follow-up period. Results One-hundred seventy-four PLWH were included in the study group, and 175 were included in the control group. The study group gained 2.51 kg ± 0.31 (mean ± standard deviation) over the 2 years of follow-up, while the control group gained 1.1 ± 0.31 kg over the same time course (p < 0.001). INSTI treatment, Caucasian origin, and lower BMI were risk factors associated with excessive weight gain during the 2 years of follow-up. Among metabolic parameters, only glucose levels increased after initiating INSTI-based regimens, although limited to males of African origin (p = 0.009). Conclusions We observed a mild weight gain after switching to INSTI-based regimens, with no major impact on metabolic parameters over 2 years of follow-up. Longer follow-up might be needed to observe the adverse metabolic effects of INSTI-based regimens. The impact on weight gain should be discussed with every patient before the treatment switch to ensure a balanced diet and physical activity to prevent excessive weight gain that might hamper compliance with ART

Epidemiology and Transmitted HIV-1 Drug Resistance among Treatment-Na&iuml;ve Individuals in Israel, 2010&ndash;2018

Despite the low prevalence of HIV-1 in Israel, continuous waves of immigration may have impacted the local epidemic. We characterized all people diagnosed with HIV-1 in Israel in 2010&ndash;2018. The demographics and clinical data of all individuals (n = 3639) newly diagnosed with HIV-1 were retrieved. Subtypes, transmitted drug-resistance mutations (TDRM), and phylogenetic relations, were determined in &gt;50% of them. In 39.1%, HIV-1 transmission was through heterosexual contact; 34.3% were men who have sex with men (MSM); and 10.4% were people who inject drugs. Many (&gt;65%) were immigrants. Israeli-born individuals were mostly (78.3%) MSM, whereas only 9% of those born in Sub-Saharan Africa (SSA), Eastern Europe and Central Asia (EEU/CA), were MSM. The proportion of individuals from SSA decreased through the years 2010&ndash;2018 (21.1% in 2010&ndash;2012; 16.8% in 2016&ndash;2018) whereas those from EEU/CA increased significantly (21% in 2010&ndash;2012; 27.8% in 2016&ndash;2018, p &lt; 0.001). TDRM were identified in 12.1%; 3.7, 3.3 and 6.6% had protease inhibitors (PI), nucleotide reverse transcriptase inhibitors (NRTI), and non-nucleoside reverse transcriptase inhibitors (NNRTI) TDRM, respectively, with the overall proportion remaining stable in the studied years. None had integrase TDRM. Subtype B was present in 43.9%, subtype A in 25.2% (A6 in 22.8 and A1 in 2.4%) and subtype C in 17.1% of individuals. Most MSM had subtype B. Subtype C carriers formed small clusters (with one unexpected MSM cluster), A1 formed a cluster mainly of locally-born patients with NNRTI mutations, and A6 formed a looser cluster of individuals mainly from EEU. Israelis, &lt;50 years old, carrying A1, had the highest risk for having TDRM. In conclusion, an increase in immigrants from EEU/CA and a decrease in those from SSA characterized the HIV-1 epidemic in 2010&ndash;2018. Baseline resistance testing should still be recommended to identify TDRM, and improve surveillance and care

Transmission patterns of HIV-subtypes A/AE versus B: inferring risk-behavior trends and treatment-efficacy limitations from viral genotypic data obtained prior to and during antiretroviral therapy.

BACKGROUND: HIV subtypes A and CRF01_AE (A/AE) became prevalent in Israel, first through immigration of infected people, mostly intravenous-drug users (IVDU), from Former Soviet-Union (FSU) countries and then also by local spreading. We retrospectively studied virus-transmission patterns of these subtypes in comparison to the longer-established subtype B, evaluating in particular risk-group related differences. We also examined to what extent distinct drug-resistance patterns in subtypes A/AE versus B reflected differences in patient behavior and drug-treatment history. METHODS: Reverse-transcriptase (RT) and protease sequences were retrospectively analyzed along with clinical and epidemiological data. MEGA, ClusalX, and Beast programs were used in a phylogenetic analysis to identify transmission networks. RESULTS: 318 drug-naive individuals with A/AE or patients failing combination antiretroviral therapy (cART) were identified. 61% were IVDU. Compared to infected homosexuals, IVDU transmitted HIV infrequently and, typically, only to a single partner. 6.8% of drug-naive patients had drug resistance. Treatment-failing, regimen-stratified subtype-A/AE- and B-patients differed from each other significantly in the frequencies of the major resistance-conferring mutations T215FY, K219QE and several secondary mutations. Notably, failing boosted protease-inhibitors (PI) treatment was not significantly associated with protease or RT mutations in either subtype. CONCLUSIONS: While sizable transmission networks occur in infected homosexuals, continued HIV transmission among IVDU in Israel is largely sporadic and the rate is relatively modest, as is that of drug-resistance transmission. Deviation of drug-naive A/AE sequences from subtype-B consensus sequence, documented here, may subtly affect drug-resistance pathways. Conspicuous differences in overall drug-resistance that are manifest before regimen stratification can be largely explained in terms of treatment history, by the different efficacy/adherence limitations of older versus newer regimens. The phenomenon of treatment failure in boosted-PI-including regimens in the apparent absence of drug-resistance to any of the drugs, and its relation to adherence, require further investigation

Comparable long-term efficacy of Lopinavir/Ritonavir and similar drug-resistance profiles in different HIV-1 subtypes.

BACKGROUND: Analysis of potentially different impact of Lopinavir/Ritonavir (LPV/r) on non-B subtypes is confounded by dissimilarities in the conditions existing in different countries. We retrospectively compared its impact on populations infected with subtypes B and C in Israel, where patients infected with different subtypes receive the same treatment. METHODS: Clinical and demographic data were reported by physicians. Resistance was tested after treatment failure. Statistical analyses were conducted using SPSS. RESULTS: 607 LPV/r treated patients (365 male) were included. 139 had HIV subtype B, 391 C, and 77 other subtypes. At study end 429 (71%) were receiving LPV/r. No significant differences in PI treatment history and in median viral-load (VL) at treatment initiation and termination existed between subtypes. MSM discontinued LPV/r more often than others even when the virologic outcome was good (p = 0.001). VL was below detection level in 81% of patients for whom LPV/r was first PI and in 67% when it was second (P = 0.001). Median VL decrease from baseline was 1.9±0.1 logs and was not significantly associated with subtype. Median CD4 increase was: 162 and 92cells/µl, respectively, for patients receiving LPV/r as first and second PI (P = 0.001), and 175 and 98, respectively, for subtypes B and C (P<0.001). Only 52 (22%) of 237 patients genotyped while under LPV/r were fully resistant to the drug; 12(5%) were partially resistant. In48%, population sequencing did not reveal resistance to any drug notwithstanding the virologic failure. No difference was found in the rates of resistance development between B and C (p = 0.16). CONCLUSIONS: Treatment with LPV/r appeared efficient and tolerable in both subtypes, B and C, but CD4 recovery was significantly better in virologically suppressed subtype-B patients. In both subtypes, LPV/r was more beneficial when given as first PI. Mostly, reasons other than resistance development caused discontinuation of treatment

Mutations found in patients failing regiments containing LPV/r or NNRTIs.

<p>Mutations found in patients failing regiments containing LPV/r or NNRTIs.</p><p>The Table classifies patients failing on LPV/r or NNRTI containing regimens according to the number of mutations conferring resistance to the different drug classes. “+” indicates presence of mutations, but for some patients the actual mutations are listed. “–” indicates “no mutations” or also “no previous PI-containing regimens”.</p><p>EFV – efavirenz; IDV – indinavir; LPV/r – lopinovir/ritonavir; NFV – nelfinavir; NNRTIs – Non-nucleosides reverse transcriptase inhibitors; NRTIs – Nucleosides reverse transcriptase inhibitors; NVP – nevirapine; SQV – saquinavir; PIs – protease inhibitors.</p

Co-infection with hepatitis and demographic data on patients stratified according to their hepatitis status.

<p>176 of the 318 A/AE-HIV carriers (55.3%) were co-infected with hepatitis: 148 had HCV, 11 HBV and 17 had both. 130 were not infected with hepatitis and for 12 there was no information.</p>a<p>For 8 IVDU, 2 MSM and 2 Others the status of hepatitis infection was unknown.</p>b<p>Other birth sites were in Africa, America, Asia, Europe, or unknown.</p><p>IVDU – Intravenous drug users; MSM – men who have sex with men; TG – Transmission group.</p

Resistance Mutations in the reverse transcriptase of drug-naive and drug-treated individuals.

<p>250 samples from 234 drug-naive patients and 115 samples from 78 treated A/AE patients were genotyped. 31 patients were sampled both prior to treatment and after treatment failure. RT mutations found in all A/AE naive patients were compared to those found in A/AE drug-treated ones and to samples from 254 drug naive and 60 drug treated B individuals diagnosed since 2001. The first available sample from each drug-naive individual was used for analysis. For mutation-frequency analysis of drug-treated patients each mutation was counted once. Only mutations showing statistically significant differences between drug-naive and drug-treated patients and/or between A/AE and B frequencies are included.</p><p>Major NRTI related mutations included TAMs: M41L, D67N, K70R, L210W, T216Y/F and K219Q/E, as well as A62V, K65R, L74V/I, L77F, F116Y, Q151M and M184V/I. Major NNRTI mutations included A98G, L100I, K101E/P, K103N/S, V106A/M, V108I, Y181C, Y188C/H/I, G190A/S, P225H and K238T.</p><p>NNRTIs – Non-nucleosides reverse transcriptase inhibitors; NS – Not significant; NRTIs – Nucleosides reverse transcriptase inhibitors;</p>a<p>Subtyping was performed using the Stanford Database Rapid Subtyping Tool <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-Rhee1" target="_blank">[23]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-Rhee2" target="_blank">[24]</a>. According to that classification 192 patients had virus containing protease of subtype A and RT most similar to CRF01_AE; for 70 both the protease and the RT were CRF01_AE; 52 were of subtype A; and four had protease classified as CRF01_AE and RT classified as A. Other subtyping tools such as Geno2Pheno (<a href="http://www.geno2pheno.org/" target="_blank">http://www.geno2pheno.org/</a>) or the Rega Subtyping Tool (<a href="http://jose.med.kuleuven.be/subtypetool/html/" target="_blank">http://jose.med.kuleuven.be/subtypetool/html/</a>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-deOliveira1" target="_blank">[57]</a> vary to some extent in the classification of variants.</p

Resistance Mutations in the Protease of drug-naive and drug-treated individuals.

<p>250 samples from 234 drug-naive patients and 115 samples from 78 treated A/AE patients were genotyped. 31 patients were sampled both prior to treatment and after treatment failure. PI mutations found in all A/AE naive patients were compared to those found in A/AE drug-treated ones and to samples from 254 drug naive and 60 drug treated B individuals diagnosed since 2001. The first available sample from each drug-naive individual was used for analysis. For mutation-frequency analysis of drug-treated patients each mutation was counted once. Only mutations showing statistically significant differences between drug-naive and drug-treated patients and/or between A/AE and B frequencies are included.</p><p>Mutations in the Protease: The PI mutations L23I, L24I, D30N, V32I, M46I/L, I47A, G48V, I50L/V, I54V, V82A/S, I84V/A/C, N88S/T and L90M were considered major mutations. Secondary PI mutations included L10V/I/F/M, K20R, L33F, M36I, F53L, A71V/I and G73S/T/C/A.</p><p>N – NRTIs; NN – NNRTIs; NNRTIs – Non-nucleosides reverse transcriptase inhibitors; NS – Not significant; NRTIs – Nucleosides reverse transcriptase inhibitors; PI – Protease inhibitors;</p>a<p>Subtyping was performed using the Stanford Database Rapid Subtyping Tool <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-Rhee1" target="_blank">[23]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-Rhee2" target="_blank">[24]</a>. According to that classification 192 patients had virus containing protease of subtype A and RT most similar to CRF01_AE; for 70 both the protease and the RT were CRF01_AE; 52 were of subtype A; and four had protease classified as CRF01_AE and RT classified as A. Other subtyping tools such as Geno2Pheno (<a href="http://www.geno2pheno.org/" target="_blank">http://www.geno2pheno.org/</a>) or the Rega Subtyping Tool (<a href="http://jose.med.kuleuven.be/subtypetool/html/" target="_blank">http://jose.med.kuleuven.be/subtypetool/html/</a>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057789#pone.0057789-deOliveira1" target="_blank">[57]</a> vary to some extent in the classification of variants.</p