Aquestionnaire was used to collect socio-demographic and clinical data. The qualityof life scale proposed by the World Health Organization and a questionnaire tomeasure treatment adherence were used.  of the 314 interviewees, 190 (60.5%) were male, aged 43 years on average, 121(38.5%) had attended up to five years of schooling, 108 (34.4%) received up to twotimes the minimum wage, and 112 (35.7%) were on sick leave. In regard to clinicalvariables, individuals with an undetectable viral load scored higher in all thedomains concerning quality of life, with statistically significant differences inthree domains. Regarding treatment adherence, 235 (73.8%) presented poor adherenceand those who strictly adhered to treatment obtained better scores in quality oflife. The results show that quality of life is better among individuals adherentto ART. Supporting people to adhere to the antiretroviral treatment should be apersistent task of healthcare workers and other people participating in thetreatment, such as family members and friends. The number of AIDS-related deaths among adults and children decreased 29%since 2005. A decrease of 37% of AIDS-related deaths was observed in the last decade inLatin America. This decrease in deaths is certainly a result of therapeutic support,which in addition to prolonging survival, also improves quality of life.The impact of the antiretroviral therapy (ART) on people with HIV/AIDS contributed to adecrease in mortality or HIV/AIDS-related illnesses among infected people. The nu.Treatment adherence, psychological changes and clinical characteristics are factorsdirectly associated with the quality of life (QoL) of people living with HIV/AIDS.Consequently, there is a search not only for preventive and control methods, but alsofor strategies that facilitate and improve the quality of life of HIV/AIDS patients.Coping with HIV/AIDS means facing situations that can decrease or limit quality oflife.(-).Health conditions, housing, safety and social relationships are factors that affect thequality of life of people living with HIV/AIDS in different respects. Quality of life isone of the terms with the highest multifactor expression, which justifies its manydefinitions. In this study, we opted for the definition of quality of life (QoL)proposed by the World Health Organization (WHO): "individuals' perceptions of theirposition in life in the context of the culture and value systems in which they live andin relation to their goals, expectations, standards and concerns"-4.In this context, the quality of life of people living with HIV/AIDS and its relationshipwith ART became an object of study. Many studies assess the QoL of these people,however, those addressing the relationship of QoL and ART are rare. Hence, this study'sobjective was to assess the quality of life of people living with HIV/AIDS and itsassociation with clinical factors and adherence to antiretroviral therapy.This analytical, cross-sectional study was conducted in a referral hospital forinfectious diseases located in João Pessoa, Paraíba, Brazil.This study included a convenience sample composed of 314 people living with HIV/AIDS.The participants were selected using the feasibility criterion on days care was providedin the referral hospital. The selection criteria included: living with HIV/AIDS,receiving ART for at least three months, and residing in the state of Paraíba, sincemany of this hospital's patients are from other states. Data were collected over aperiod of four months (December 2012 to March 2013) by properly-trained researchassistants. The study was approved by the Institutional Review Board at the FederalUniversity of Paraíba (Protocol No. 0405/12) and all the participants signed free andinformed consent forms. was used to assess Quality of Life. This instrument was composed of 31items, divided into six domains: physical, psychological, social relationships,environments, level of independence, and religiosity.A semi-structured questionnaire was used to collect socio-demographic and clinicalinformation. The WHOQOL-HIV Bref was useigiosity.Cuestionario para la Evaluación de la Adhesión alTratamiento Antirretroviral en Personas con Infección por VIH y Sida) wasused to collect data related to adherence to ART. This instrument is composed of 20items divided into two dimensions: treatment adherence and factors influencing treatmentadherence. The minimum score is 17 and the maximum score is 89. In this study, theminimum score was 52 and the maximum was 88. In accordance with the analysis proposed byRemor, the following percentages (PC) were established for the questionnaireglobal score obtained by the sample: PC ≥ 85 indicates strict adherence (good); 50 ≤ PC< 85 indicates poor adherence (difficulty complying with the treatment); PC ≤ 49indicate no adherence. The scale's classification was used to compute the scores of eachitem of the WHOQOL HIV Bref. The internal consistency for the instrument domains wascomputed according to Cronbach's coefficient of reliability.The CEAT-VIH instrument  menand 124 (39.5%) women, aged 43 years old on average; ages ranged from 21 to 70 yearsold. Most participants (110/ 35.0%) were aged between 30 and 39 years old. In regard toeducation, 193 (61.4%) participants attended up to ten years of schooling, whileindividuals (121/ 38.5%) who attended from one to five years of schooling predominated.Most participants, 190 (60.5%), reported being Catholic; 190 (60.5%) individualsreported sick leave or retirement; and 226 (72%) individuals reported income of up totwo times the minimum wage .3. The viral load was undetectable for 248 (79%) participants;from 50 to 100,000 copies per ml were observed for 59 (18.8%) individuals, and seven(2.2%) individuals presented more than 100,000 copies per ml .Changes in the profile of people infected with HIV have drawn attention. The ratio ofcases between men and women decreased in all age groups. Even tof India and in . Early diagnosis is one of the aspects linked to a favorable prognosis forHIV/AIDS. Being aware of one's serological status early on enables appropriateinterventions and favors adherence to ART (11).Regarding clinical variables observed in this study, for time since diagnosis, thehighest number of individuals (124/39.5%) was among those who became aware of theirHIV-positive status less than five years ago. Most participants presented good clinicalparameters concerning viral load, i.e., undetectable and with a high number of CD4 Tcells. The individuals in this study with undetectable viral load scored higher in allthe QoL domains. Increased viral load aggravates the individual's clinical condition,worsening symptoms and increasing the likelihood of hospitalization, consequentlydecreasing QoL. Early , Santa Catarina, in São Paulo and in Porto Alegre.The results show that all the individuals scored well in the QoL domains according toclinical variables, especially in the psychological and spirituality domains, while thelowest scores were obtained in the level of independence and environment domains. Theenvironment domain presented the lowest score in comparison to the other QoL domains instudies conducted in Brazil: Rondônia, Santa Catarina, in Sãoão Paulo and in o Alegre.. The inverse was observed in this study. Spirituality was the domain withthe highest score. Religion, spirituality, and beliefs represent a search for meaning inlife, a search for responses to why and for what purpose individuals face stressful anddifficult situations, which are considered valid aspects for improved QoL.One study developed in India reports that the scores obtained in QoL domains were higherin regard to the environment domain and lower in the domain concerningspirituality. The inoved QoL.. An investigation conducted in Ribeirão Preto, SP, Brazil with individualsco-infected with tuberculosis and HIV/AIDS reports that the spirituality domains scoredhigher than the other domains.Spirituality provides support in times of distress, when there is social isolation anddistance from the family. Religion is an important aspect providing meaning and order tolife, suffering and distress, a result also found in another study,16. A domains..The total score obtained on the CEAT in this study was significantly correlated with thephysical, psychological, social relationships, and spirituality/religion domains. Lowscores obtained in the physical domain may be associated with clinical conditions, viralimmunosuppression or lack of ART..Non-adherence to therapy, particularly among people living with HIV/AIDS, is a problemof greater magnitude. The consequences of patients' lack of adherence affect not onlythe non-adherent individual but also lead to a series of problems that may reach thepopulation in general. Viral suppression, decreased contamination, minimization ofopportunistic infections, and reduced resistance to antiretroviral agents depend ontherapy adherence..Most of the studied sample present "poor adherence" and those classified as"non-adherent" obtained the lowest scores in all the QoL domains. The impact ofnon-adherence to ART on QoL was observed in this study. Given the changes in mortalityand morbidity, studies show the positive impact of adherence to ART on QoL.. One longitudinal study reports that adherence to ART is associated withimproved quality of life. Cross-sectional studies also identified associations between QoL andadherence to ART .It is known that adherence to ART improves clinical results, delays the progression ofthe disease, which in theory, should improve quality of life. One lo of life. Cross-.When assessing the quality of life of individuals with HIV/AIDS and its association withART, one needs to identify the individual's clinical characteristics and which phase ofthe infection the individual is experiencing: the asymptomatic, symptomatic or HIV/AIDSlast stage.. Adherence to antiretroviral treatment may cause side effects in the short run (nauseaand vomiting) and in the long run (lipodystrophy and dyslipidemia), impacting quality oflife. One study reports no significant difference in the domains of QoL in associationwith the use of antiretroviral agents, but found significant difference in the overallassessment of health with the presence of adverse effects of medications. (21).The relationship between adherence to ART and quality of life is reciprocal. The qualityof life of people living with HIV/AIDS may be influenced by adherence to ART. In thiscontext, it is imperative to understand antiretroviral therapy in order to maximize itsbenefits and minimize its adverse effects.Most of the participants in this study were asymptomatic with undetectable viral load(< 50 copies per ml). It can be inferred that these clinical characteristicsinfluence adherence to ART and, consequently, influence the QoL of individuals becausethe absence of symptoms combined with the presence of undesirable side effects, asreported by another study, are factors that hinder adherence to therapy.One limitation of this study is the cross-sectional methodological design. Despite thislimitation, the results indicate the need to assess the influence of ART on QoL in thisspecific population. The quality of life of the studied population according to the WHOQOL HIV Bref wasassociated with clinical variables and adherence to antiretroviral therapy. Regardingthe clinical variables, it is important to note that individuals with viral load below50 copies per ml obtained the highest scores in all the QoL domains. As for adherence toantiretroviral therapy, individuals classified as "non-adherent" obtained the lowestscores in all the QoL domains.Adherence to antiretroviral therapy is a positive factor in quality of life, especiallybecause it improves immunity, controls viral load and delays the progression of thedisease. Despite these benefits, many people living with HIV/AIDS have difficultyadhering to the therapy. Such difficulties are not only related to the clinicalrepercussions of the treatment but also due to difficulties accessing the service, andconsequently, accessing medications. In this sense, we suggest there is a need to monitor the ART adherence of people livingwith HIV/AIDS based on the understanding that adherence is a continuous process thatmainly involves the family and healthcare workers. In some situations, non-adherenceresults from the family and the healthcare workers themselves abandoning the patient.


Dolutegravir is a second generation integrase inhibitor with a proposed high genetic barrier to resistance. However, in clinical trials, decreased virological response was seen in a subset of patients with prior exposure to raltegravir and multiple integrase resistance mutations.We describe two cases of HIV subtype B-infected patients starting dolutegravir after previous failure on a raltegravir-containing regimen with extensive resistance. Genotypic analysis was performed using population sequencing and 454 ultradeep sequencing of integrase at time of raltegravir exposure.3) and the clinical condition improved substantially. In patient 2, similar worsening of the clinical condition was observed late 2012 during persistent failure on mega-cART. Five major PI, six minor PI, nine NRTI, seven NNRTI and one INI mutation plus DM-virus were detected. Ultra-deep sequencing showed selection of N155H, followed by Q95K and V151I variants and phenotypic raltegravir resistance was demonstrated. Dolutegravir was added to his failing regimen  at a VL of 39,000 cps/mL. Sustained virological suppression was reached within five months with considerable increase of CD4-count (41 to 175 mm3) and slight improvement of clinical condition.Both patients were diagnosed in early 1990s and received mono- and dual therapy, followed by several cART-regimens. Due to presence of extensive resistance, the genotypic susceptibility score of these regimens never reached a score >2 and never resulted in sustained virological suppression despite good adherence. Early 2012, the clinical condition of patient 1 worsened during persistent failure of a mega-cART regimen despite excellent drug levels. Six major PI, six minor PI, seven NRTI, six NNRTI and two INI mutations plus DM-virus were detected . Ultra-dWe present the first patients with extensive integrase resistance who were treated with dolutegravir in clinical practice and who achieved excellent virological and immunological success. These cases demonstrate the high genetic barrier of dolutegravir.


This study aimed to investigate treatment effect, drug resistance changes, and their influencing factors in Chinese AIDS patients after switching to second-line antiretroviral therapy, and thus provide important information for the scale-up of second-line antiretroviral treatment in China. In Weishi county of Henan province, where second-line antiretroviral therapy was introduced early in China, 195 AIDS patients were enrolled, of which 127 patients met the switching criterion and 68 patients volunteered to switch drugs without meeting the switching criterion. CD4 cell count, viral load and in-house PCR genotyping for drug resistance were measured for all 195 subjects before drug switch, as well as 6 and 12 months after drug switch. Extensive secondary mutations to the protease inhibitor were observed, which suggested that long-term drug resistance surveillance is necessary for patients switching to second-line antiretroviral therapy. Multidrug resistance and cross-resistance were extensive in Chinese patients that experienced first-line treatment failure. Patients need timely CD4 count, viral load, and drug resistance monitoring in order to switch to second-line therapy under conditions of relatively good immunity and low viral duplication levels. Highly active antiretroviral therapy (HAART) is currently the most effective therapy for the treatment of acquired immune deficiency syndrome (AIDS) China initiated a large-scale program for free antiretroviral treatment in 2003, with zidovudine (AZT)/stavudine (D4T) + didanosine (DDI) + nevirapine (NVP) as the main first-line therapy regimen. By October 2011, more than 130,000 patients with AIDS had received HAART. The increase in availability and access to free antiretroviral treatment had resulted in considerably prolonged survival time, improved quality of life and decreased mortality rate in AIDS patients Some foreign researchers reported that extensive drug-resistant mutations were observed before switching therapy regimens. Regarding treatment results after switching to second-line antiretroviral regimens, there is variance among reports from different regions and countries This study was approved by the Institutional Review Board of the First Affiliated Hospital of China Medical University . All participants ≥18 years of age, written informed consent was obtained from all subjects.Our research is an observational study; we did not determine or influence the course of treatment. We just collected the therapy information and blood samples of patients in the second-line antiretroviral therapy pilots in Henan province.One hundred and ninety-five AIDS patients living in Weishi county of Henan province were enrolled in August 2009 and February 2010, respectively. In accordance with Chinese National Free AIDS Antiretroviral Therapy Manual issued in 2009 The second-line antiretroviral regimen used was Lamivudine (3TC) + tenofovir (TDF) and lopinavir + ritonavir (LPV/r), as recommended by WHO Absolute CD4+, CD8+, and CD3+T lymphocytes were counted with the FACSCalibur flow cytometer .Viral loads were measured using COBAS AmpliPrep/COBAS TaqMan HIV-1 Test .HIV-1 viral RNA was extracted from 140 ul plasma with the QIAamp Viral RNA Mini Kit . Reverse transcription-polymerase chain reaction (RT-PCR) was carried out with the One-step RNA PCR Kit (AMV) within 4 hours, and 1300 bp of reverse transcriptase (RT) and protease (PR) genes of HIV-1 were amplified with nested PCR, including the whole PR and the first 300 amino acids of RT http://hivdb.stanford.edu) version 6.1.1. for analysis of HIV drug-resistant mutations and drug resistance. Statistical Package for Social Sciences (SPSS) version 15.0 was used for statistical analysis; data are shown as means ± standard deviation. Differences between groups were compared with chi-square tests and Fisher exact probability tests. Logistic regression analysis was used to identify the influencing factors of viral inhibition failure  12 months after switching to second-line treatment, and odds ratios (OR) and confidence intervals (CI) were used to express the relative strength of association. A P value <0.05 was considered statistically significant. Viral loads <400 copies/mL after treatment were considered to have virological inhibition. The average viral load was expressed with the logarithmic (log10) form.Sequencher 4.10.1, NTI advance 9 and ContigExpress were used for sequence editing, assembly and rectification. The resulting sequences were compared with the Stanford University HIV drug resistance database  were male and 56 patients (38.5%) were female. The average age was 45 (32–60) years. Among these 127 patients, 88 patients (69.3%) were drug resistant, 108 patients (85%) had CD4 cell counts <350 cells /mmopies/mL . Before 3, and all patients had viral loads <1,000 copies/mL  were male and 26 patients (38.2%) were female. The average age was 44 (33–59) years. Among these 68 patients, 7 patients (10.3%) were drug resistant, 42 patients (61.8%) had CD4 cell counts <350 cells /mmopies/mL . Before All patients were 95% or more adherent to therapy after switching to second-line therapy according to the questionnaire results. One hundred and fifty-six patients were followed up 6 months after switching to second-line therapy and one hundred and sixty-seven patients were followed up at 12 months.10) decreased from 4.6±0.8 before drug switches to 2.3±1.7; at 12 months, the percentage of patients with viral loads <400 copies/mL increased to 67.3%, and the viral load average VL (log10) decreased to 2.0±1.7  at 12 months with an increase of 76.6 cells/µl, showing a gradual increase trend. Percentage of patients with CD4 <350 cells/µl reduced to 70% (79/113) at 12 months. At 6 months, the percentage of patients with viral loads <400 copies/mL increased from 0% before drug switches to 60.8%, and the viral load average VL(log 2.0±1.7  (P<0.01)10) increased from 1.2±0.6 before drug switches to 1.6±1.4 at 6 months, and then decreased to 1.3±1.1 at 12 months  at 12 months with an increase of 68.4 cells/µl, showing insignificant difference compared to that before drug switches. The percentage of patients with viral loads <400 copies/mL decreased from 89.7% before drug switches to 83.1% at 6 months, and increased to 90.7% at 12 months (P>0.05); the viral load average VL (log2 months  (P>0.05)Of 127 patients, the rate of drug resistance was 69.3% (88/127) before second-line treatment, 23.5% (23/98) and 8.8% (10/113) after 6 and 12 months after drug switches, showing a significant decrease (P<0.001) compared to that before drug switches.Of 68 patients who volunteered to participate in second-line treatment, drug-resistant mutations existed in 7 patients before drug switches. At 6 months, 58 patients were followed-up and 4 patients were found to have drug resistance, of which 2 patients were new to carry drug resistance. At 12 months, 54 patients were followed-up and 1 new patient was found to have drug resistance. All drug resistance found were high drug resistance to nonnucleoside reverse transcriptase inhibitor (NNRTI). No significant difference was observed between drug resistance before and after second-line treatment (P>0.05).Before second-line treatment, rates of cross-resistance and multidrug resistance were high. The rates of drug resistance to NRTI and cross-resistance to AZT/D4 T/DDI were 54.3% (69/127) and 51.2% (65/127), respectively. Rates of drug resistance to NRTI significantly decreased to 17.3% (17/98) and 7.1% (8/113) at 6 and 12 months (P<0.001) after second-line drug switches; Rates of cross-resistance to AZT/D4 T/DDI significantly decreased to 16.3% (16/98) and 7.1% (8/113) at 6 and 12 months (P<0.001), respectively. Before drug switches, the rate of drug resistance to NNRTI was 69.3% (88/127), it decreased to 23.5% (23/98) and 11.5% (13/113) at 6 and 12 months after drug switches, respectively. The multidrug resistance rate to NRTI and NNRTI decreased from 54.3% (69/127) to 7.1% (8/113) after one year of second-line treatment .3TC and TDF, which were included in second-line therapy regimens, are NRTI. Rates of drug resistance to 3TC and TDF before drug switches were 30.7% (39/127) and 45.7% (58/127), respectively. After 6 and 12 months of second-line treatment, rates of drug resistance to 3TC decreased to 11.2% (11/98) and 2.7% (3/113) respectively, and rates of drug resistance to TDF decreased to 15.3% (15/98) and 6.2% (7/113) respectively . At 6 anAll patients were 95% or more adherent to therapy 6 and 12 months after second-line treatment initiation. At 12 months, viral loads in 32.7% (37/113) of patients were not inhibited under 400 copies/mL. Results of univariate analysis showed that HIV-1 RNA >100,000 copies/mL before drug switches correlated with ineffective inhibition of viral loads after regimen change, the OR values was 3.95  (P<0.05). The OR of CD4<100 cells/µl was 5.14 , however, the P value were insignificance statistical (P>0.05) . The OR In this study, 127 patients with first-line antiretroviral treatment failure switched to the second-line regimen after an average of 54.8 months of first-line treatment. Before second-line treatment, viral loads in all patients were higher than 1000 copies/mL. The patients had low immunity, 85% of which had a CD4 count lower than 350 cells/µl, and 69.3% harbored drug resistance. After switching to second-line regimen (3TC+TDF+LPV/r) for 12 months, 67.3% of patients had effective viral inhibition; the average of CD4 cell count had an increase of 76.6 cells/µl; the rate of CD4<350 cells/µl decreased to 70%; and the rate of drug resistance decreased to 8.8%. The significant improvement indicated that switching to second-line antiretroviral drugs led to good treatment effect.Chinese second-line antiretroviral therapy is the first treatment choice in Europe and America, which produced satisfactory results in antiretroviral-naïve patients with AIDS In our study, before switching to second-line antiretroviral therapy, drug resistance existed in 69.3% of patients who met drug switching criteria. Cross-resistance and multidrug resistance also existed severely. The rates of cross-resistance and multidrug resistance to NRTI and NNRTI were 69.3% and 54.3%, respectively. However, after one year of second-line treatment, the overall drug resistance rate decreased to 8.8%, and rates of cross-resistance and multidrug resistance also decreased to 11.5% and 7.1%. Our results showed that, although severe cross-resistance and multidrug resistance existed after first-line treatment failure, second-line therapy effectively decreased the rate of drug resistance, as well as the epidemic risk of drug-resistant bacterial strains. Analysis of cross-resistance to NRTI (3TC and TDF), the main drug in the second-line antiretroviral regimen, showed that before drug change, 28.3% of patients had cross-resistance to 3TC and TDF, along with viral loads >1000 copies/mL. After 12 months of second-line treatment, viral loads in 86.1% of patients were effectively inhibited. In these patients, although there was only LPV/r playing a role, satisfying effect were observed and the cross-resistance rate to the 3TC and TDF decreased to 1.8%. It was noticeable that in our study, although drug resistance to the protease inhibitor (PI) was not found, extensive PI secondary drug-resistant mutations were detected. In case PIs primary drug-resistant mutations occur, it will lead to high PI drug resistance. Considering that there were new patients found to have drug-resistant mutations at 6 and 12 months, drug resistance surveillance should be continued to observe the cross-resistance, multidrug resistance and PI drug-resistant mutations after long-term second-line treatment.Among patients meeting drug switching criteria, we performed a regression analysis of those patients whose virus loads were not inhibited under 400 copies/mL after drug change. The results showed that viral load higher than 100,000 copies/mL before drug change was a risk factor of virological inhibition failure. Similarly, a European study demonstrated that after switching to second-line antiretroviral regimen (including the protease inhibitor); levels of viral loads were more easily inhibited in patients with lower viral loads Multidrug resistance and cross-resistance existed severely in Chinese patients that experienced first-line treatment failure. These patients need to be monitored timely on viral loads and drug resistance and switch to second-line therapy under conditions of relatively low viral duplication levels. Satisfactory results were observed in patients treated with Chinese second-line antiretroviral therapy regimen (3TC+TDF+LPV/r) for 12 months, with no drug resistance to PI found. However, extensive secondary mutations to PI were observed, which suggested that the long-term drug resistance surveillance is necessary for patients switching to second-line antiretroviral therapy.


Monotherapy with protease-inhibitors (MPI) may be an alternative to cART for HIV treatment. We assessed the impact of this strategy on immune activation, bacterial translocation and inflammation.n=40) with patients on cART (n=20). Activation, senescence, exhaustion and differentiation stage in CD4+ and CD8+ T lymphocyte subsets, markers of monocyte activation, microbial translocation, inflammation, coagulation and low-level viremia were assessed.We performed a cross-sectional study comparing patients on successful MPI (p=0.031), soluble markers of monocyte activation , microbial translocation (lipopolysaccharide (LPS)-binding protein; LBP p=0.07), inflammation (IL-6 p=0.04) and low-level viremia (p=0.035). In a multivariate model, a higher level of CD14+ CD16−CD163+ cells and sCD14, and presence of very low-level viremia were independently associated with MPI. Monocyte activation was independently associated with markers of inflammation , microbial translocation  and low-level viremia (p=0.01).CD4+ or CD8+ T lymphocyte subset parameters were not significantly different between both groups. Conversely, as compared with triple cART, MPI patients showed a higher proportion of activated monocytes (CD14+ CD16−CD163+ cells, Patients on MPI showed a higher level of monocyte activation than patients on standard therapy. Microbial translocation and low-level viremia were associated with the high level of monocyte activation observed in patients on MPI. The long-term clinical consequences of these findings should be assessed. The introduction of HIV antiretroviral treatment has completely changed the spectrum of the illness that has become, in the past years, a chronic condition in developed countries. Prompt diagnosis has also permitted to treat patients earlier and the proportion of patients that are first diagnosed with a low number of CD4+ T lymphocytes or with an opportunistic infection has sharply decreased. With stable patients on treatment and living longer, the morbidity associated with medication and cost of treatment has notably increased. Strategies for simplifying treatment and lowering the cost have started to be implemented . MonotheSeveral clinical trials have assessed the virological effectiveness of simplification of a successful standard protease inhibitor containing regimen to a protease inhibitor monotherapy. The MONET and the MONOI studies compared ritonavir-boosted darunavir in monotherapy versus the standard triple therapy treatment. Both demonstrated non-inferiority in the per-protocol analysis ,3. In thOn the contrary, lower rates of virological suppression were seen in the MONARK study in naïve patients who started monotherapy with boosted lopinavir as compared with standard triple therapy containing regimen . FinallyOverall, monotherapy seems an effective strategy in patients previously suppressed with no prior virologic failure. However, more episodes of transient viremia elevation have been reported in the monotherapy groups included in the studies ,7, althoEfficacy in the above-cited clinical trials was determined by viral load (VL) suppression, but no other variables were taken into account. Concerns about the possibility of a higher immune activation in patients on monotherapy, or the possibility of lower penetration in the central nervous system were raised. Few studies were performed in an attempt to answer this question. A retrospective study of the samples in the MONET trial showed no differences in high-sensitive C-reactive protein (hs-CRP) or interleukin-6 (IL-6) between patients in monotherapy or triple therapy . SuppresWe hypothesized that patients on monotherapy could have a higher level of immune activation than patients on cART and, therefore, were at higher risk of suffering long-term clinical consequences (i.e. non-AIDS events). Here, we perform a study to compare the impact of successful monotherapy, either with boosted darunavir or boosted lopinavir, on immune activation, microbial translocation and other inflammatory markers.Forty patients on antiretroviral treatment who had successfully simplified to monotherapy either with ritonavir-boosted darunavir or ritonavir-boosted lopinavir (MPI group) were recruited between September 2011 and September 2012 in the outpatient HIV clinic in the Hospital Clinic, Barcelona. Patients had to fulfil the following inclusion criteria: age over 18 years, antiretroviral treatment with monotherapy for at least the previous 48 weeks and VL <37 copies/ml in the blood tests performed in the previous 48 weeks. Patients fulfilling the inclusion criteria and willing to participate signed informed consent and an extraction of 60 ml of blood was performed. Twenty patients on triple therapy with a PI-containing regimen (ritonavir-boosted darunavir or lopinavir) (cART group) were recruited as a comparison group. To participate in the study, written informed consent was obtained from all individuals, and the study protocol was evaluated and approved by the Hospital Ethical Committee.Plasma HIV-RNA was measured using Versant HIV-1 RNA v3.0 , which has a lower limit of detection and a lower limit of quantification of 37 copies/ml. Patients with a plasma VL that was detectable but below the limit of quantification (<37 copies/ml) were classified as patients with very low-level viremia (VLLV), and those patients with VL reported as not detected were classified as undetectable .All analyses were done in freshly isolated peripheral blood mononuclear cells (PBMCs). EDTA-anticoagulated blood was obtained by venipuncture; PBMCs were immediately isolated by density gradient centrifugation using Ficoll-Hypaque . We used a comprehensive approach of simultaneous measurement of different immunological parameters  in CD4+ Serum was initially frozen at a temperature of −80°C. Soluble markers of monocyte activation [soluble CD14 (sCD14) and soluble CD163 (sCD163)], markers of host response to lipopolysaccharide (LPS) , inflammation  and pro-coagulation (D-dimer) were assessed.Soluble CD14 was determined with Quantikine ELISA ; and soluble CD163 was determined by Macro163 ELISA  according to manufacturer's instructions. Human LBP and endotoxin-core antibodies were determined by ELISA . High-sensitive CRP was determined by an immune turbidimetric method . A result over 0.5 mg/dl was considered positive. IL-6 and TNF-alpha were determined by ELISA . Results over 5 and 10 pg/ml, respectively, were considered positive. D-dimer was used as a pro-coagulation marker. It was measured with a turbidimetric method  in a BCS automated coagulation system XP (Siemens Diagnostics). The sensitivity of the technique allows for the detection of levels as low as 10 ng/ml. The normal cut-off is 500 ng/ml.t-test or the non-parametric tests Mann–Whitney U-test. Correlations between quantitative parameters were explored using the Spearman's rho test. Logistic regression was used to analyze the factors independently associated with the type of therapy (MPI vs. cART). Multiple regression was used to analyze the factors independently associated with monocyte activation. All statistical analyses were performed using the SPSS software version 20 . All p-values were two-tailed, and were considered significant when lower than 0.05.Characteristics of the study population and the different immunological parameters, microbial translocation and inflammatory markers were recorded as median [interquartile range], and comparisons were made using 3 in both groups. No differences in plasma VL at the start of antiretroviral treatment were seen between groups. All patients had VL <37 copies in the last control performed before the inclusion in the study, but in the blood test performed the day of inclusion, four patients had detectable VL .No differences in age or gender were observed between the two groups . Patientp=0.033; CD14+ CD16− CD163+ cells 55.17% vs. 33.57%, p=0.031 No differences were observed in markers of T lymphocyte activation, senescence, exhaustion, co-receptor expression or differentiation stages between both groups see . Convers p=0.031 A; and CDp=0.004 (p=0.002 (p=0.07 (p=0.04). D-dimer levels were similar between both groups. Given that patients on monotherapy had a significantly longer time of known HIV infection and a lower CD4+ T lymphocyte count before starting cART and these variables could mean a bias to compare both groups, we repeated the analysis controlling both variables, excluding those patients on monotherapy with longer follow-up  and lower CD4+ T lymphocyte count previous to treatment . The differences in monocyte activation, microbial translocation and inflammatory markers between both groups were confirmed (data not shown).Levels of soluble markers of monocyte activation were higher in MPI vs. cART patients  (Table(p=0.002 . LBP lev (p=0.07 D]. Regarp=0.035).Finally, we analyzed the presence of VLLV, defined as viremia below limit of detection (37 copies) but qualitatively detectable. Fifteen out of 38 (39%) patients in the monotherapy group presented positive signal under the limit detection versus two out of 18 (11%) in the triple therapy one (p=0.023) and sCD14 (p=0.013), and presence of VLLV (p=0.027) were independently associated with MPI. We repeated the multivariate model controlling for CD4+ T lymphocyte at the start of the antiretroviral treatment, CD4+ T lymphocyte at inclusion, nadir CD4+ T lymphocyte and time of HIV infection. The results showed that CD14+ CD16− CD163+ cells and sCD14, but not VLLV, remained independently associated with MPI.A multivariate analysis was performed to assess the factors independently associated with the type of therapy (MPI vs. cART). Variables with statistically significant differences in univariate analysis were included in the model. A higher level of CD14+ CD16− CD163+ cells (p=0.039), sCD163 , hsPCR ; the levels of CD14+CD16+ cells were correlated with IL-6  and TNF-alpha ; and the levels of sCD14 with LBP , hsPCR  and TNF-alpha . Markers of monocyte activation were not correlated with CD4+ T cell at start of antiretroviral treatment or nadir CD4+ T lymphocyte.Patients with higher levels of monocyte activation showed the higher levels of microbial translocation and inflammatory markers. The levels of CD14+CD16+CD163+ cells were correlated with sCD14  and low-level viremia (p=0.01). In addition, in a multivariate model using as dependent variable sCD14, this soluble marker of monocyte activation was independently associated with the marker of microbial translocation LBP (p=0.028) and low-level viremia (p=0.05).In a multivariate analysis (using in the model as dependent variable either CD14+CD16+CD163+ cells or CD14+CD16+ cells), monocyte activation was independently associated with markers of inflammation  and inflammatory markers hs-PCR  and TNF-alpha .In addition to sCD14, the marker of microbial translocation LBP was directly correlated with sCD163  vs. 8574 (7820–9548), p=0.025]  vs. 7.65 (4.21–13.31), p=0.025] .The results of our study show a higher level of monocyte activation in patients on successful monotherapy with a boosted PI as compared with protease inhibitor standard regimen. The level of monocyte activation was associated with markers of host response to microbial translocation, inflammation and low-level viremia. These data might suggest that microbial translocation and VLLV drive the high level of monocyte activation observed in these patients on protease inhibitor monotherapy.The first objective of our study was to assess if the simplification to a successful monotherapy had an impact on activation of the immune system. Although no differences were observed in the percentage of CD4+ and CD8+ T lymphocytes subpopulations , patients on monotherapy with a boosted PI showed a higher level of monocyte activation as measured by the expression of CD16 and CD163 in CD14 cells, and the levels in plasma of soluble CD14 and CD163. Recent studies describe higher percentage of markers of monocyte activation in HIV viremic patients and, also in HIV-treated patients who, despite effective antiretroviral treatment, still express higher monocyte activation than age matched uninfected patients . The marThe second objective of the study was to investigate the factors associated with monocyte activation in this cohort. We found that patients with higher monocyte activation had a higher level of IL-6, LBP and low-level of viremia. These data might suggest that microbial translocation and VLLV drive the monocyte activation in patients on protease inhibitor monotherapy. We found that IL-6 was significantly higher in the monotherapy group. It has been reported that increases in concentrations of interleukin-6 are strongly associated with all-cause mortality . If the Early gut mucosal destruction in HIV infection results in microbial translocation and higher microbial products in the circulation that are supposed to be partially responsible of HIV-associated immune activation that persists despite the introduction of the antiretroviral treatment . A recenFinally, we observed that a higher number of patients included in the MPI group presented with VLLV. The importance of VLLV has been a recent issue of interest. Some studies have related VLLV to a higher risk of virologic failure, and have suggested that low-level viral replication is a cause of VLLV ,33. In oWe are aware that our study has other limitations. First of all, it is a transversal study and a low number of patients are included. Second, regarding baseline characteristics, the CD4+ T lymphocyte count at the start of treatment was lower in the MPI group, although no significant differences were observed in VL, nadir of CD4+ or CD4+ T lymphocyte count at the time of inclusion. In fact, it has been reported that clinically important CD4+ T lymphocyte count responses are likely to be better defined in terms of absolute postcART CD4+ T lymphocyte counts, rather than change from baseline . In addiIn summary, the higher monocyte activation observed in the monotherapy group raises concern about this strategy and the possible association with a higher mortality and long-term cardiovascular and neurocognitive deleterious effects. Larger clinical trials should be performed in order to confirm these results.


We sought to quantify agreement between Institute of Medicine (IOM) and Department of Health and Human Services (DHHS) retention indicators, which have not been compared in the same population, and assess clinical retention within the largest HIV cohort collaboration in the U.S.Observational study from 2008–2010, using clinical cohort data in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD).Retention definitions used HIV primary care visits. The IOM retention indicator was: ≥2 visits, ≥90 days apart, each calendar year. This was extended to a 2-year period; retention required meeting the definition in both years. The DHHS retention indicator was: ≥1 visit each semester over 2 years, each ≥60 days apart. Kappa statistics detected agreement between indicators and C statistics (areas under Receiver-Operating Characteristic curves) from logistic regression analyses summarized discrimination of the IOM indicator by the DHHS indicator.Among 36,769 patients in 2008–2009 and 34,017 in 2009–2010, there were higher percentages of participants retained in care under the IOM indicator than the DHHS indicator  (p<0.01), persisting across all demographic and clinical characteristics (p<0.01). There was high agreement between indicators overall , and C statistics revealed a very strong ability to predict retention according to the IOM indicator based on DHHS indicator status, even within characteristic strata.Although the IOM indicator consistently reported higher retention in care compared with the DHHS indicator, there was strong agreement between IOM and DHHS retention indicators in a cohort demographically similar to persons living with HIV/AIDS in the U.S. Persons with poorer retention represent subgroups of interest for retention improvement programs nationally, particularly in light of the White House Executive Order on the HIV Care Continuum. Retention in clinical care for HIV-infected patients is important for achieving and maintaining improved individual and public health outcomes The NA-ACCORD is the largest multi-site collaboration of interval and clinic-based cohort studies of HIV-infected adults (≥18 years old) receiving care in the U.S. and Canada Retention in clinical care was assessed in 2008–2009 and 2009–2010 using two different indicators defined as: 1) IOM-endorsed: the numerator was the number of adults with ≥2 HIV primary care visits within each calendar year, >90 days apart, and the denominator was adults with ≥1 visit during the year; 2) DHHS-endorsed: the numerator was the number of adults with an HIV primary care visit in each semester (January–June and July–December) of the 2-year period, each visit ≥60 days after the prior, and the denominator was adults with ≥1 visit during the first semester of the first year. The IOM-based definition was extended to a 2-year period (2008–2009 and 2009–2010) to allow direct comparison with the DHHS-based definition; patients were considered retained only if they met the numerator inclusion requirements in both years, and the denominator was restricted to adults with ≥1 visit in the first semester of the first year. Inpatient visits were excluded.We investigated whether clinical retention was associated with demographic characteristics, including age at first visit during the study period, race/ethnicity, HIV transmission risk group, sex, CD4+ lymphocyte (CD4) count, prescription of antiretroviral therapy (ART) during the study period, and suppression of plasma HIV-1 RNA. Race/ethnicity was categorized as non-Hispanic black, non-Hispanic white, Hispanic, and other/unknown. HIV transmission risk group was categorized as men who have sex with men (MSM), injection drug use (IDU), heterosexual contact, and other/unknown. Patients with both sexual and IDU transmission risk were categorized as IDU. CD4 count at baseline was categorized as <350 cells/µL, 350–499 cells/µL, or ≥500 cells/µL. ART was defined as a regimen of >3 antiretroviral agents from ≥2 classes or a triple nucleoside/nucleotide reverse transcriptase inhibitor (NRTI) regimen containing abacavir or tenofovir (consistent with contemporary guidelines) Chi-square tests were used to identify differences between the two indicators by demographic and clinical characteristics; kappa statistics were used to detect agreement between indicators. C statistics (areas under Receiver-Operating Characteristic curves) from logistic regression analysis were used to summarize “correct” classification of patients as retained or not by the DHHS indicator (using the IOM indicator as the reference standard); a sensitivity analysis using the DHHS indicator as the reference standard was also conducted During 2008–2009 and 2009–2010, there were significantly higher percentages of participants retained in care under the IOM indicator  than the DHHS indicator  (p<0.01). This difference persisted, with higher percentages retained by IOM than by DHHS indicator, across all demographic and clinical characteristics measured in both time periods p<0.01, .Across demographic characteristics, the percentage of patients who met clinical retention by the IOM and DHHS definitions varied from 62–87% and 54–84%, respectively in 2008–2009, and from 59–85% and 50–79%, respectively in 2009–2010. Regardless of definition or year, the lowest percentages retained in care were seen among persons aged ≤39 years, persons not prescribed ART≥6 months in each year, and persons with unsuppressed HIV-1 RNA . PersonsThere was very high agreement between indicators overall . Strong agreement in the IOM and DHHS indicators persisted across all demographic and clinical characteristics examined  was required to be classified as retained in care.The denominator requirements for the DHHS indicator may induce intra-individual missingness of retention outcomes across >24-month intervals. This is because a patient may be included in the denominator during the first 24-month window and subsequently excluded as the window “moves” forward, if they have no qualifying visit in the initial semester of the new 24-month interval. This was the case for 8.3% of individuals who were eligible to be included in the DHHS indicator denominator only in 2008–2009 (and not in 2009–2010), despite qualifying for the unaltered IOM indicator in both 12-month time periods.By contrast, the IOM numerator included individuals with any 2 visits (>90 days apart) during each calendar year (whether in different semesters or not). Although the IOM indicator is defined for a 12-month period, we employed a 24-month period by requiring the IOM indicator definition to be met in both calendar years of the 24-month period to allow for a more direct comparison with the 24-month period articulated in the DHHS indicator definition.The IOM indicator may be more desirable than the DHHS indicator when assessing clinical retention within individuals over longer periods of time. Both indicators revealed the same groups in need of targeted intervention to improve retention; namely the young, and those not prescribed ART. These characteristics allude to the challenge of engaging HIV-infected adults in care when they may not yet be feeling the effects of their HIV infection.The application of these indicators in different populations needs to be refined as clinical practice and guidelines for laboratory monitoring frequency change. Stable patients with suppressed HIV-1 RNA viral loads and high CD4+ cell counts may require fewer annual primary care visits and laboratory tests than patients with poorer health status; the utility of retention indicators to highlight gaps in the continuum of care related to negative individual- and population-level HIV outcomes should consequently be re-examined as guidelines are revised over time.Limitations to this analysis include possible difficulties in generalizing the results to populations of HIV-infected individuals newly linked to care. The study population was successfully engaged in care; about 93% were in care prior to 2008. It has been noted that nearly 33% of individuals newly linked to care are not retained in care in the United States Application of both the IOM and DHHS indicators yielded fairly similar results and showed strong agreement. These results should provide reassurance that utilizing the IOM indicator for annual or cross-sectional assessments at the clinic level should not produce widely disparate results compared with the DHHS approach


Tolerability and convenience are crucial aspects for the long-term success of combined antiretroviral therapy (cART). The aim of this study was to investigate the impact in routine clinical practice of switching to the single tablet regimen (STR) RPV/FTC/TDF in patients with intolerance to previous cART, in terms of patients’ well-being, assessed by several validated measures.Prospective, multicenter study. Adult HIV-infected patients with viral load under 1.000 copies/mL while receiving a stable ART for at least the last three months and switched to RPV/FTC/TDF due to intolerance of previous regimen, were included. Analyses were performed by ITT. Presence/magnitude of symptoms (ACTG-HIV Symptom Index), quality of life , adherence (SMAQ), preference of treatment and perceived ease of medication (ESTAR) through 48 weeks were performed.Interim analysis of 125 patients with 16 weeks of follow up was performed. 100 (80%) were male, mean age 46 years. Mean CD4 at baseline was 629.5±307.29 and 123 (98.4%) had viral load <50 copies/mL; 15% were HCV co-infected. Ninety two (73.6%) patients switched from a NNRTI (84.8% from EFV/FTC/TDF) and 33 (26.4%) from a PI/r. The most frequent reasons for switching were psychiatric disorders (51.2%), CNS adverse events (40.8%), gastrointestinal (19.2%) and metabolic disorders (19.2%). At the time of this analysis (week 16), four patients (3.2%) discontinued treatment: one due to adverse events, two virologic failures and one with no data. A total of 104 patients (83.2%) were virologically suppressed (<50 copies/mL). The average degree of discomfort in the ACTG-HIV Symptom Index significantly decreased from baseline (21±15.55) to week 4 (10.89±12.36) & week 16 (10.81±12.62), p<0.001. In all the patients, quality of life tools showed a significant benefit in well-being of the patients . AdherenSwitching to RPV/FTC/TDF from another ARV regimen due to toxicity, significantly improved the quality of life of HIV-infected patients, both in mental and physical components, and improved adherence to therapy while maintaining a good immune and virological response.


We assessed trends in the proportion of transmitted (TDR) and acquired (ADR) HIV drug resistance and associated mutations between 2001 and 2011 in the German ClinSurv-HIV Drug Resistance Study.The German ClinSurv-HIV Drug Resistance Study is a subset of the German ClinSurv-HIV Cohort. For the ClinSurv-HIV Drug Resistance Study all available sequences isolated from patients in five study centres of the long term observational ClinSurv-HIV Cohort were included. TDR was estimated using the first viral sequence of antiretroviral treatment (ART) naïve patients. One HIV sequence/patient/year of ART experienced patients was considered to estimate the proportion of ADR. Trends in the proportion of HIV drug resistance were calculated by logistic regression.for trend = 0.6; 2001–2011). The proportion of ADR among all treated patients was 16%, whereas it was high among those with available HIV genotypic resistance test  but declined significantly over time . Viral load monitoring subsequent to resistance testing was performed in the majority of treated patients (96%) and most of them (67%) were treated successfully.9,528 patients were included into the analysis. HIV-sequences of antiretroviral naïve and treatment experienced patients were available from 34%  of patients. The proportion of TDR over time was stable at 10.4% (95% CI 9.1–11.8; p The proportion of TDR was stable in this study population. ADR declined significantly over time. This decline might have been influenced by broader resistance testing, resistance test guided therapy and the availability of more therapeutic options and not by a decline in the proportion of TDR within the study population. Since the introduction of combination antiretroviral therapy the morbidity and mortality among people infected with HIV has been reduced dramatically HIV drug resistance surveillance has been performed in many Western European countries within different study populations and settings. Most studies were performed in patients during primary HIV infection or in patients chronically infected with HIV prior to ART initiation st 1999. The cohort comprises all individuals infected with HIV in the participating clinical centres. Only basic data are reported every six months. The data set is anonymized and comprises demographic data, time-related variables on clinical events, AIDS-defining diagnoses, and detailed data on antiretroviral treatment. Patients with available sequences were identified at the five ClinSurv-HIV Drug Resistance Study centres participating in this analysis. Any identifying information was removed at the local study centres, the sequences were labelled with a new identifier allowing linkage with anonymized patient data in the ClinSurv data base. All data analyses were performed on the anonymized data set.The ClinSurv-HIV project protocol was approved by the German Federal Commissioner for Data Protection. ClinSurv-HIV is an ongoing, prospective, long-term observational cohort study. The study design has been described in detail elsewhere The Robert Koch Institute (RKI) is the German national public health institute, therefore the Federal Commissioner for Data Protection is the responsible entity for studies which are conducted by the Robert Koch Institute. Information on HIV infection collected in ClinSurv corresponds to the data reported to the RKI according to legal requirements implemented by the national Protection against Infection act (IfSG) of 2001. All patient data collected in ClinSurv are generated during routine care. The German Federal Commissioner for Data Protection therefore waived the need for ethical approval for the ClinSurv study. No written informed consent is required from patients.www.hivdb.stanford.edu; HIVdb version 6.2.0; 2012) in order to identify amino acid substitutions and to determine drug susceptibility. For epidemiological analysis, HIV sequences isolated from ART naïve patients were analysed using the surveillance HIV drug resistance mutation list, SDRM For the ClinSurv-HIV Drug Resistance substudy, all patients infected with HIV under care in five study sites  of the ClinSurv-HIV Cohort study group with at least one HIV genotypic resistance analysis result were identified. The nucleotide sequences were processed through the Stanford University Genotypic Resistance Interpretation Algorithm (for trendp) were calculated by logistic regression. All p-values were two sided, and a p-value of <0.05 was considered significant. Data were analysed using SPSS 18.0.3 and R 2.12.1.Viral sequences available between 1998 and 2011 were collected and analysed. For the estimation of trends in the proportion of HIV drug resistance over time viral sequences sampled between 2001 and 2011 were included into the analyses. The characteristics of patients with available sequences compared to those who were not genotyped were compared with simple logistic regression. Patients and viral sequences were categorised into ART naïve and treatment experienced. Viral sequences were considered to originate from treatment naïve patients in case of ART start ≤15 days prior to the date of resistance testing, to account for delays in the documentation of the date of resistance testing results and the actual date of blood sampling. The time between resistance testing and antiretroviral treatment start and the proportion of patients with resistance test before ART start were analysed by using data from patients with documented first-line treatment start. The proportion of patients with antiretroviral treatment failure undergoing resistance testing was calculated for patients with first line treatment start in one of the resistance study centres who had >180 days of treatment experience and a resistance test within 90 days after virologic failure. Virologic failure was defined as two consecutive viral load measurements with >50 copies/ml within 180 days or one viral load measurement with >1000 copies/ml. For different drug classes the proportion of cumulative ART exposure per year, the median days of previous ART exposure and the proportion of patients showing history of exposure to the respective drug class were calculated, excluding treatment interruption time. A simple linear regression was performed on the duration of antiretroviral treatment exposure in days prior to resistance testing with increasing year of genotyping for different drug classes and on the total treatment exposure. In a univariate analysis of factors associated with HIV drug resistance the following covariates were separately included: age, gender, transmission group category, HIV subtype, ART interruption, duration of previous ART exposure, CD4 cell count, and plasma viral load at the time point of testing or 30 days prior to or 15 days after testing, year of resistance test at documented ART start. Factors significantly associated with acquired HIV drug resistance in a univariate analysis were included into multiple logistic regression. For the analysis of factors associated with acquired HIV drug resistance only the last sequence of ART experienced patients was included. The proportion of patients showing a history of exposure to a drug class, trends in the proportion of patients with ART interruption, gender, transmission group category, HIV subtype were calculated by simple logistic regression. Median plasma viral loads and CD4 cell counts were calculated for ART naïve and treated patients. The Mann-Whitney-U-test (MWT) was used to compare viral loads, CD4 cell counts and the age at ART start for patients with resistant and susceptible HIV. Confidence intervals were calculated using a Wilson score confidence interval. Trends in the prevalence of HIV drug resistance mutations, DRMs,  of these patients. Nearly half of these HIV sequences  were generated while patients were ART naïve, the other half of viral sequences  were produced while patients were treated with antiretroviral drugs. The ART status of the patients could not be clarified for 3%  of the HIV sequence data. Of the patients who have not been genotyped , 4,895 patients were seen in the resistance study centres while ART naïve, and of 5,262 patients data were collected while treated with antiretroviral drugs . In totaPatients were predominantly male ; 18%  were female. Median age at the time point of HIV genotypic resistance testing was 40 years (33.0–47.0). Median CD4 cell count at first visit was 310 cells/µl (IQR: 147–490). The main transmission group category was sex between men , followed by heterosexual contacts  and by patients originating from high-prevalence countries . Median time between first HIV genotypic resistance test and ART start was 33 days (IQR: 13–169). The proportion of patients with resistance test before ART start in the five study centres increased from 0.4% in 2000 to 69% in 2009 and declined thereafter to 46% in 2010 and 21% in 2011. The duration between HIV diagnosis and first resistance test was in median 45 days (IQR: 16–481) for ART naïve patients.vs. subtype-B: 33%; 192/584), predominantly subtype A . Nearly half of the female study population originated from high-prevalence countries: 46% (270/584). At time point of HIV genotypic resistance testing, the median viral load (VL) for ART naïve patients was 4.73 log10 copies/ml (IQR: 4.1–5.3), median CD4 cell count was 285 cells/µl (IQR: 151–437). Both VL and CD4 cell counts did not differ significantly between patients infected with susceptible or resistant viruses . The median VL of treated patients with detectable plasma virus was 4.02 log10 copies/ml (IQR: 3.1–4.8), median CD4 cell count of treated patients was 271 cells/µl (IQR: 150–423). VL and CD4 cell count did not differ significantly between patients infected with susceptible or resistant viruses .The characteristics of patients with resistance test and those without differed as follows: within the category risk of transmission in the Resistance study group we observed more patients with heterosexual contacts , more patients from high prevalence countries  and fewer patients with intravenous drug use ; within the category region of origin in the Resistance study group we observed more patients being from Africa, Near East (with resistance test: 11.6% vs. 9.1% without test) . Patientfor trend = 0.6; 2001–2011)  and remained stable over time  . Nucleos01–2011) .for trend<0.001; 2001–2011)   but declined significantly over time  . To esti01–2011) . INI res01–2011) . The mos01–2011) .Factors significantly associated with a lower risk of ADR by using a univariate model were being female compared to male, transmission group category IDU compared to MSM, being infected with non-B subtype compared to subtype B, reported ART interruption at genotyping compared to reported continuous antiretroviral treatment at the time of genotyping and the cumulative duration of ART interruption . In a muTo investigate the reduced risk for women to carry resistant viral strains, the duration of previous ART exposure was analysed. Results showed, that women had a significantly lower ART exposure time than men .The majority of antiretroviral treated patients  showed a history of exposure to NRTIs, 67%  to NNRTIs, 80%  to PIs and 5%  to INIs.Over time there was a small but significant decrease in the proportion of patients with exposure to NRTI , NNRTI use remained stable during the period of observation . PI exposure increased significantly over time . INI use increased significantly over time .2: 0.00; coefficient B: 6.6; 95% CI −19–32; p = 0.62), a significant increase for NNRTI , for PI  and for INI . The duration of total ART exposure prior to resistance testing increased but not significantly over time .The simple linear regression showed a non-significant slight increase in the duration of ART exposure in days prior to resistance testing with increasing year of genotyping for NRTI .Considering the regimen at resistance testing there was an increase in boosted PI containing regimens, especially for ritonavir boosted NRTI/PI combinations . PI regimens without booster almost disappeared over time. Triple class combinations like NRTI/NNRTI/PI declined over time whereas newer drug class containing regimens increased . Combination of NRTI/NNRTI showed a decline over time . Treatment interruption at the time of resistance testing was highly frequent in this study population but remained stable over time  of ART experienced patients. HIV drug resistance was observed in 60%  of this study population whereas 40%  showed no resistance associated mutations. However, the proportion of patients with successful viral suppression after resistance testing did not differ between those patients with susceptible and resistant HIV strains . A switch of therapy between different drug classes was observed significantly more frequent for patients harbouring resistant strains  than for patients with susceptible viruses .Results of this study showed that the estimated prevalence of TDR over time among ART naïve patients remained stable at a high level, whereas overall prevalence of ADR as well as drug resistance within different drug classes in patients under antiretroviral treatment declined significantly over time. The decline of ADR could be influenced by several factors. Presumably antiretroviral drug related effects like enhanced treatment optimization and resistance test guided therapy as well as broader resistance testing in the study population are considered to be reasonable factors influencing this decline.The high but stable level of TDR is comparable to other prevalence estimates in long term observational cohorts in Germany as well as in other European countries As expected the time a patient was exposed to ART prior to resistance testing was significantly associated with a higher risk of ADR in the univariate and multivariate analysis. The significantly lower risk of ADR for women was most likely caused by their significantly shorter duration of ART exposure prior genotyping.Regarding the duration of ART exposure prior to resistance testing there was a significant increase in treatment exposure for NNRTIs, PIs and INIs whereas NRTI exposure and the complete duration of treatment exposure increased without a level of significance. Therefore the highly significant decline in ADR observed among treated patients with available resistance test was not influenced by a declining duration of previous ART exposure or by increasing ART interruptions over time in the study population. In this study population PI exposure increased significantly over time. In contrast, PI associated HIV drug resistance in treated patients declined significantly. The enhanced use of PI containing regimens and the increasing variety of second generation PIs with higher resistance barriers might influence this phenomenon Currently only HIV resistance data from long term observational studies in different study populations before ART initiation is available in Germany This study has some limitations. First, it is a convenience sample of data collected from 5 urban sites of Germany. Therefore, the study is only able to describe the situation based on the information that has been provided by those study centers, and did not reflect the overall situation for Germany. Furthermore, the data was collected over time periods where resistance testing became more widely used in routine clinical care. As we see the majority of the tests were performed after statutory introduction of resistance testing in 2005. Since the proportion of patients tested is correlated with the proportion of observed cases this is important to keep in mind in view of the findings. In addition, certain information is not retrieved, such as the reasons why, despite indication, no test was performed or the reasons for resistance testing, e.g. in view of future treatment options after interruption or due to an actual treatment failure. Evidence exists that in the participating centers more HIV drug resistance tests were performed than we observed by recording the data. It might be that resistance tests were carried out in other laboratories that we have not reached.However, this report is the first description of HIV drug resistance for both ART naïve and treatment experienced persons infected with HIV in Germany. With all constraints, it is nevertheless one of the most comprehensive reports currently available and gives insight into clinical resistance testing practices and prevalence of HIV drug resistance of people infected with HIV in Germany.


No data are available on removal of one NRTI in subjects effectively treated with unboosted atazanavir+2NRTIs. We present the 48-week virological efficacy and safety of unboosted atazanavir plus lamivudine (3TC) or emtricitabine (FTC) . Changes between baseline (BL) and week 48 assessed by the Wilcoxon signed rank test.3, virologically suppressed since 4.2 (2.2–5.4) years; 53 patients switched from a tenofovir (TDF)-based regimens; ATV was associated with 3TC in 83% patients. No virological failures or discontinuations were observed; three patients had a single viral blip in the range 50–250 copies/mL; CD4+ increased from 610 (518–829) cells/mm3 at BL to 697 (579–858) cells/mm3 at week 48 [48-week change: 39 (−63/+160) cells/mm3 p=0.081]. Three clinical events were observed  in absence of renal lithiasis, AIDS-defining or drug-related events or death. Overall, significant 48-week amelioration of ALP  and CKD-EPI  were observed. Patients switching from TDF  years, 14% HCV co-infected, infected with HIV since 16 (9–21) years, on antiretroviral therapy since 13 (5–16) years, with a nadir CD4+ of 254 (157–307) cells/mmfrom TDF  significSwitch from an unboosted atazanavir-based regimen to ATV+3TC or FTC regimen was effective and safe in this small sample, supporting the hypothesis of a potential two-steps de-intensification  in patients on long-lasting virological suppression.


We report an economic analysis of Human Immunodeficiency Virus (HIV) care and treatment in Indonesia to assess the options and limitations of costs reduction, improving access, and scaling up services.3); time of treatment; HIV care and opportunistic infections cost components; and the costs of patients for seeking and undergoing care.We calculated the cost of providing HIV care and treatment in a main referral hospital in West Java, Indonesia from 2008 to 2010, differentiated by initiation of treatment at different CD4 cell count levels . Higher CD4 cell counts at initiation resulted in lower laboratory and opportunistic infection treatment costs. Transportation cost dominated the costs of patients for seeking and undergoing care (>40 %).Before antiretroviral treatment (ART) initiation, costs were dominated by laboratory tests (>65 %), and after initiation, by antiretroviral drugs (≥60 %). Average treatment costs per patient decreased with time on treatment (e.g. from US$580 per patient in the first 6 month to US$473 per patient in months 19–24 for those with CD4 cell counts under 50 cells/mmCosts of providing ART are highest during the early phase of treatment. Costs reductions can potentially be realized by early treatment initiation and applying alternative laboratory tests with caution. Scaling up ART at the community level in certain high prevalence settings may improve early uptake, adherence, and reduce transportation costs. The face of the HIV/AIDS epidemic in Indonesia is changing. While the epidemic started among injecting drug users, now it is shifting towards the general population. The percentage of HIV transmission through injecting drug use decreased from 13 % in 2010 to 7 % in 2014, and heterosexual transmission increased from 31 to 52% during the same period [3, with the exception of pregnant women with HIV, babies born from women with HIV, and PLHIV with TB and Hepatitis B who are not yet on ART (these PLHIV received ART regardless of their CD4 cell count) [Indonesia’s national response to the epidemic focuses on a wide range of programs, including continuing support for care and treatment programs . The neel count) , 6. In 2l count) . In thisThere is an urgent need to address the following research questions. First, what are the present treatment costs per person per year, by time of treatment and stage of disease, and is there any potential to reduce these costs? There is very little evidence on this question from the Indonesian context. Yet, in recent years, much evidence has become forward from African studies. For example, a recent multi-country study including 161 facilities has shown that facility-level ART costs on average $208 per patient-year across Ethiopia, Malawi, Rwanda and Zambia. Costs were higher in South Africa, at $682 . Also, tSecond, what are the costs of scaling up ART? International evidence suggests that cost increases stemming from increased patient numbers can partly be offset by reduced average treatment costs as patients are treated earlier ; howeverThird, what is the financial burden of patients accessing care? Although international studies have shown that the financial burden on patients may constitute a barrier to treatment  and may This paper presents an economic analysis of the provision of ART and care for HIV/AIDS patients from both the health care provider and patient perspectives. It presents a cost profile differentiated by initiation of treatment at different CD4 cell count levels; time on treatment; cost components  for HIV care and opportunistic infections (OIs); and finally patient costs of seeking and undergoing care. We believe our approach is unique in the context of Indonesia and Asia and can be generalized to other settings with similar HIV/AIDS epidemics and health system profiles.The study was conducted in Bandung, at an HIV/AIDS clinic in the largest public referral and teaching hospital (Hasan Sadikin) in West Java province (43 million inhabitants). The clinic is visited by high risk groups and the general population, and delivers HIV-related services such as voluntary counseling and testing, ART, and sexually transmitted infections services. The clinic operates at full capacity because it is among the few clinics that deliver ART in Bandung. The clinic generates its own revenues through government, hospital, and private funding; ART-related services are free, except hospitalization and the registration fee.3. The starting point of every patient initiating ART was uniformed as month 1, and patients were analyzed at 6, 12, 18, and 24 months on ART. We also observed the pre-ART period when patients received HIV care and treatment but had not yet initiated ART, which ranged from 1 week to 6 months before treatment initiation. Based on these starting points, each patient’s treatment pattern was tracked from available medical and financial records and all costs were calculated. Patients were required to visit the clinic monthly to take their antiretroviral drugs (ARVs), and undergo CD4 cell count, viral load, and routine laboratory tests approximately every 6 months.The study included all records on inpatients and outpatients starting ART in the clinic between 2008 and 2010. The study population was divided into five groups by CD4 cell count: 0–50, 50–100, 100–150, 150–200, and >200 cells/mmThe cost estimation was divided into health care costs  and patient costs . Health care costs were divided into hospitalization, outpatient visits, OI treatment, and ARVs, as well as CD4 cell count, viral load, and routine laboratory test costs. The micro-costing approach  was usedOutpatient costs were calculated based on the total recurrent and capital costs of the clinic. Recurrent personnel costs were estimated based on actual wages or government salary scales . Other rThe OI treatment costs were calculated based on the medical resources consumed by OI treatment , excluding hospitalization. Medical records and the physician’s patient database were used to estimate resource utilization, and the official hospital prices issued in 2011 were used to calculate the unit costs of drugs and equipment. We obtained the unit cost of OI treatment by dividing the total cost of OI treatment for each CD4 cell count group by its population. We were unable to retrieve data regarding the specific OIs that drugs and equipment were used to treat. The average unit cost of OI treatment is presented in Kimia Farma  were used as the unit costs of ARVs, while the price of Tenofovir was based on Bender et al. [Because the data was limited, we did not perform micro-costing when calculating the costs of hospitalization, ARVs, or laboratory tests. We used the World Health Organization’s Choosing Interventions that are Cost Effective (WHO-CHOICE) estimates  to estimr et al. . The uniThe patient costs were estimated by conducting a survey among 41 patients undergoing ART at the hospital. We collected information including (but not limited to) clinic service fee, travel costs, travelling time, the average number of daily working hours, and monthly expenditures. Based on this information, first we calculated the amount of productive time per patient (in minutes), basically total time spent at work per month in minutes. Second, we calculated patient productivity per minute (i.e. monthly expenditure per minute as a proxy for income/productivity per minute). Third, we estimated the total productivity loss per patient as the amount of minutes spent to undergo the treatment  times patient productivity per minute. Patients did not have to pay for ARV, ARV monitoring, other lab tests, or OI medication/treatment. To avoid double counting in calculating treatment costs from the societal perspective, we exempted the clinic service fee from this specific calculation .All costs were measured in Rupiah, and converted to US$ using the 2010 exchange rate . Both thSecondary data related to patients (e.g. ARV and OI drugs intake per patient) were taken from the clinic’s patients database (in the form of an Excel file). The database was anonymized prior to analysis , and none of the patients personal identity was published in any part of the study. On the event of patient costs (primary) data collection, all patients were asked to fill in written informed consent forms prior to participating in the survey and the survey was anonymous (no patient names were collected). The survey was conducted by a group of enumerators and authors only received the results. The study was approved by the Padjadjaran University Indonesia, Medical Faculty ethical committee.3 group are males , while females dominate the >150 cells/mm3 group . In average, there are more males across the CD4 cell count groups (72 %). The average age of patients across the groups is 30 years old, and the majority are married, employed, and have experience with injecting drug use. The highest education level attained by patients was the secondary level (high school).Patient characteristics are presented in Table 3 and 15 % of those with 50 − 100 cells/mm3. Few patients with CD4 cell counts >200 cells/mm3 were hospitalized and received OI treatment. Details regarding unit costs per item are summarized in the Table 3, which increased from US$725 in 1–6 months to US$2099 in 7–12 months. A relatively high CD4 cell count at treatment initiation relates to relatively low costs of ARVs, laboratory tests, and OI drugs/treatment. Figure 3. The distribution of cost is provided in the 3, 50 – 100 cells/mm3, and those with >200 cells/mm3. The average 2 year treatment costs difference between the patients with CD4 cell count < 50 cells/mm3 and the groups with higher CD4 cell count is also statistically significant, except with patients with CD4 cell count between 100 – 150 cells/mm3. The statistical significance test is summarized in Table 3, respectively. Transportation cost and the clinic fee dominated the costs, while productivity loss accounted for less than 25 % of the total cost per visit. Per visit, almost all patients spent US$2 for the registration fee and US$5 − US$6 for transportation. The mean time to reach the clinic was approximately 1 h (most patients lived < 20 km away) and the average time spent in the clinic was approximately 100 min. There were no major differences in patient costs between patients with CD4 cell counts less than or greater than 200 cells/mm3 . Most patients in our survey travelled using either public transport (54 %) or motorcycle (42 %).Table To our knowledge, this study is the first in Indonesia and among the few in Asia , 23 to e3appear to be at lower risk for the majority of OIs, compared with patients with <200 cells/mm3 [Early ART initiation. Most cost items are lower when patients’ CD4 cell counts are higher at ART initiation and especially the total cost share of hospitalization and OI treatment was reduced. CD4 cell counts can predict the likelihood of OIs; patients with CD4 cell counts >200 cells/mmells/mm3 –28 and tells/mm3 , 29, 30.ells/mm3 . WHO is ells/mm3 . Thus, oAlternative diagnostics. Before ART initiation, costs are dominated by laboratory tests  followed by outpatient visits and hospitalization. After ART initiation, costs were dominated by ARV drugs followed by laboratory tests. Although costs reductions in hospitalization and ARV use might be difficult to realize, reductions are possible for laboratory test costs, as is found in the DART trial in four African countries , which sThese findings lead to several observations in response to the research questions. Regarding the cost of treatment and potential cost reduction, the study confirms the hypothesis that the following measures have potential to reduce cost in ART delivery:Regarding our second research question about scaling up ART, the study indicates that although increased ART coverage may cause a large increase in health expenditure in the short run , 42, it 3 could also obtain ART at the community health care center, as our analysis suggests that hospitalization and OIs are rare in this population. In addition, patients mostly utilize first line ARV, and no patients with CD4 cell counts >100 cells/mm3 switch to second line ARV , respectively. Especially for patients with CD4 cell counts <200 cells/mm3 these costs could be a barrier, as it exceeds 10 % of their monthly expenditure and can be considered to be catastrophic for a household economy [Regarding our third research question about patients’ financial burden, the study shows that patient costs per visit are US$10 and US$11, for patients with CD4 cell counts below and above 200 cells/mm economy .3, respectively, and this is comparable with the finding of Riyarto et al. [3.Transportation comprises the highest proportion of costs: 62 and 43 % for patients with CD4 cell counts below and above 200 cells/mmo et al.  in Indono et al.  in Banduo et al. , Brinkhoo et al. , and Poso et al.  have shoOur results should be interpreted with some caution. First, this study has evaluated a contextualized ART service delivery model, which may hamper the generalizability of its results. Cost structures and levels as well as patient populations are likely to vary between clinics, and specific costing studies for other settings  should be considered. Caution should be exercised when interpreting our result in other resource limited settings. Second, we may have overestimated the total patient costs of seeking and undergoing care as this was based on assumptions regarding patients’ labour productivity losses, and not on empirical data collection on these losses per se. Third, although we have conducted a time motion study to control for inefficiency in personnel performance and equipment use related to ART delivery in the clinic, discrepancies may still exist, and we may have over- or undervalued the total costs. Fourth, we did not perform any comparison between WHO CHOICE estimates  and any local data. Although this is an important aspect, currently there is very limited local data available to do this comparison. Fifth, it is important to note that the unit costs and prices data that we used are from year 2010–2012, depending on availability. As such, we believe these unit costs have changed overtime and our results should be interpreted with this note in mind  and by applying alternative laboratory tests with caution. Third, scaling up ART at the community level in certain high prevalence settings has potential to save costs and improve uptake and adherence. However, provision of ART at all community clinics seems inefficient due to the low prevalence in the general population and options to select certain clinics in high prevalence areas need further investigation.


Cobicistat (COBI) is a pharmacoenhancer and one of the components of ECF/TDF (elvitegravir/cobicistat/emtricitabine/tenofovir DF), which is approved in treatment-naïve HIV patients with creatinine clearance (CrCl) ≥70 mL/min. Study 118 assessed the renal safety of COBI-containing regimens in HIV patients with mild to moderate renal impairment.Phase 3, open label study in HIV-1-infected patients with CrCl 50–89 mL/min who are virologically suppressed on a stable regimen containing ritonavir (RTV)-boosted atazanavir (ATV) or darunavir (DRV). Patients switched RTV to COBI, while keeping the rest of their regimen unchanged. We present the 96-week (Wk) data.2). Actual GFR assessment using CLiohexol (n=14) was unaffected over 24 Wks . Three renal discontinuations occurred (two worsening CrCl and one proteinuria/hematuria); none had proximal renal tubulopathy [PRT]. No patient had laboratory evidence of PRT .Seventy-three patients were enrolled. Mean age was 54 years; male 82%; white 77%; hypertension 38%; diabetes 18%; baseline proteinuria (≥trace) 51%; median CrCl 71 mL/min (range: 42–98). At Wk 96, 89% maintained virologic suppression (95% CI 77.4–95.8%). No emergent resistance developed. Reductions in CrCl (median [IQR]) were observed as early as Wk 2, after which they were nonprogressive through Wk 96 . Changes in CrCl by baseline CrCl (<70 vs ≥70) at Wk 96 were: −3.1 [−5.1–0.5] vs −7.6 [−15.2 to −3.6], respectively. Cystatin C-based eGFR remained stable through Wk 96  from the phase 3 studies of COBI-containing regimens.