We compared the effectiveness of tenofovir/emtricitabine (TDF/FTC) combined with either lopinavir/r (LPV/r) or another recommended third drug in the 2010 French guidelines in antiretroviral-naïve patients starting combination antiretroviral therapy in 2004–2008 in the French Hospital Database on HIV.3, AIDS-defining event and non-AIDS-defining hospitalization or death. Propensity scores were estimated by logistic regression based on the clinical centre and other confounders. In each clinical centre, each patient initiating LPV/r was matched with a patient initiating another third drug (efavirenz or atazanavir/r) and having a close propensity score. Cox's proportional hazards models were then used, with treatment as covariate. Time was right-censored at four years.The outcomes were stop or switch of the third component, viral load (VL) <500 copies/ml, an increase of at least 100 CD4 cells/mm3, or to the occurrence of an AIDS-defining event. Non-AIDS-defining hospitalizations or deaths were more frequent with LPV/r .1269 patients started LPV/r plus TDF/FTC, and 890 could be matched to 890 patients receiving another third drug. Baseline characteristics were well balanced between these two groups. LPV/r was associated with a higher risk of third drug stop (hazard ratio (HR): 1.69; 95% confidence interval (CI), 1.42–2.00) and with less rapid viral suppression . There was no difference in the time required for a CD4 cell increment of at least 100/mmFor first-line therapy, in this observational setting, TDF/FTC plus LPV/r were less durable than TDF/FTC plus another recommended third drug, led to a less rapid viral suppression and were associated with a higher risk of non-AIDS morbidity. The primary aims of antiretroviral therapy (ART) for HIV infection are to reduce morbidity and to prolong life by reducing viral load (VL) and increasing the CD4+ T-cell count with minimal toxicity/adverse event (AE). Combination antiretroviral therapy (cART) comprising two nucleoside reverse transcriptase inhibitors (NRTI) and a third drug, either a ritonavir-boosted protease inhibitor (PI) or a non-nucleoside reverse transcriptase inhibitor (NNRTI), has shown good virologic and immunologic efficacy in many randomized clinical trials –9.The efficacy of ritonavir-boosted PI-containing regimens relies on the additional dose of ritonavir used as a pharmacokinetic booster. Lopinavir/r (LPV/r) has been the boosted PI of choice for many years, and was the only such co-formulation available in 2011. Other boosted PI-based regimens with a more favourable toxicity profile became available as early as 2004.Between 2004 and 2008, several randomized trials compared various antiretroviral (ARV) drugs in treatment-naïve patients –9. In 20Since ARV drugs are generally not assessed on clinical criteria, because of limited-duration randomized controlled trials and low event frequency, it is important to know whether the various recommended ARV drugs have the same impact on the basis of clinical criteria defined as AIDS-related morbidity or severe non-AIDS morbidity such as malignant, cardiovascular and infectious diseases. In addition, because patients enrolled in clinical trials are selected, and for example individuals with severe comorbidities are often excluded, clinical trial findings can be less generalizable than observational study findings, so it is important to assess the effectiveness of different treatments in routine care settings, complementarily with clinical trials .The purpose of this study was to assess whether LPV/r was still a valid option for ART-naïve patients. Using a comparative effectiveness approach, LPV/r was compared to other recommended third drugs (EFV and ATV/r) in the 2010 French guidelines, always in combination with tenofovir/emtricitabine (TDF/FTC), using five criteria for effectiveness: the durability of the third component, virologic and immunologic responses, AIDS morbidity and severe non-AIDS morbidity.The FHDH-ANRS CO4  is an open hospital cohort study created in 1992. It includes 70 hospitals belonging to 26 Regional HIV/AIDS Coordination Centres (COREVIHs) located in mainland France and French overseas territories. Patients are eligible if they have documented HIV-1 or HIV-2 infection and give their written informed consent to participate. Data are collected prospectively by trained research assistants on standardized forms which include the transmission group, biological markers such as the CD4 cell count and plasma HIV RNA level, clinical manifestations, the nature and starting date of prescribed treatments, and death. The reasons for ARV drugs stopping have been collected since 2005.This study was restricted to ARV-naïve adults and adolescents living with HIV and with a VL >500 copies/ml, who started a first-line three-drug cART regimen consisting of TDF/FTC in every case, plus LPV/r, ATV/r or EFV. The study period for cART initiation was 2004–2008. We selected 2004 as this was the year atazanavir became available, and 2008 in order to provide four-year results. Women with reported pregnancy and patients infected less than six months previously were not eligible, as they qualified for specific therapeutic strategies.2) and VL (log10) and cotrimoxazole prophylaxis.The baseline for all analyses was the date of treatment initiation. The following baseline characteristics were described according to the prescribed regimen: clinical centre, age, sex transmission, sub-Saharan origin, hepatitis C virus co-infection, time after diagnosis of HIV-1 infection (<1 year or ≥1 year), AIDS status, year of treatment initiation, baseline CD4 cell count ; and severe non-AIDS morbidity . The choice of threshold (500 copies/ml) was due to assay technique changes over time in the study period. Cox's proportional hazards models were used, including the type of treatment as the only variable in the model, in the group of patients initiating LPV/r and their matched counterparts initiating another third drug, in order to compare outcomes between the two matched groups. The other third drug (EFV or ATV/r) served as the reference. Time was right-censored at four years. As a change in the third drug could be considered as a competing event (such patients are likely to be those experiencing a slower reduction in VL or a slower increase in the CD4 cell count), a competing-risk approach was adopted for virologic and immunologic responses. In this approach, when the third drug was changed, follow-up was right-censored at the date of the patient's last visit during the four-year follow-up period. This approach ensures that no endpoint can be recorded during the period between the treatment change and the end of the four-year follow-up period, thus avoiding a situation in which the majority of patients change their third drug and achieve a VL reduction (or a gain in CD4 cells) while on this alternative treatment. For both clinical endpoints, we used an intention-to-continue-treatment approach, ignoring treatment changes. We also described the reasons for stopping or switching the third drug as follows: ineffective treatment, intolerance and/or toxicity/adverse event, treatment simplification and other reasons. We used SAS software  for all statistical analyses.We evaluated four-year Kaplan-Meier estimates for all of the following outcomes: third component stop or switch; virologic success, defined as ever achieving a VL <500 copies/ml while still receiving the drug; a gain of at least 100 CD4 cells/mmn=1441) or ATV/r (n=714) plus TDF/FTC. Several characteristics of the two initial treatment groups were different (n=379) had more advanced HIV infection, with lower CD4 cell counts (median 81 vs. 223), higher VL (median 5.2 vs. 4.9) and more frequent prior AIDS-defining event (40% vs. 17%). Absolute standardized differences comparing baseline characteristics between the two groups in the unmatched and matched samples are reported in Supplementary Figure 2. After propensity score matching, the standardized differences of all the characteristics were less than 10%, indicating a successful balance.The flow chart of the study is shown in The third drug was EFV in 614 cases (69%) and ATV/r in 276 cases (31%). Median follow-up was 42.0 months (interquartile range: 26.4–55.2).No difference was found between EFV and ATV/r on any of the outcomes. Of the 890 matched patients initiating LPV/r, 517 patients changed their treatment, and of the 890 patients initiating another third drug, 310 patients changed their treatment. The flow chart in p<0.0001). Among toxicity/adverse event the proportion of patients with lipid disorders who switched after initiating LPV/r was 8% versus 0% for patients initiating another third drug (p=0.007). The proportion of switch for simplification was greater for patients initiating LPV/r than for patients initiating another third drug. Among the 44 patients who changed their third drug with VL ≥500 copies/ml, the reasons for the change did not differ between the treatment groups (p=0.36).Among the 267 patients who changed their third drug after VL <500 copies/ml and for whom the reason for the change was available, these reasons differed between the treatment groups , 1.42–2.00) a. The esp<0.0001) (p<0.0001); at month six, this rate was 76% with LPV/r versus 79% with the other third drugs (p=0.06); whereas the difference was no longer significant at later times. Overall, the proportion of virologic success (ever achieving a VL <500 copies/ml while still receiving the drug) was lower for LPV/r than for another third drug .VL fell below 500 copies/ml in 759 patients on LPV/r and in 765 patients on the other third drugs. LPV/r was associated with less rapid viral suppression (<0.0001) b. At mon3 in 658 patients initiating LPV/r and in 663 patients initiating another third drug. There was no difference between LPV/r and the other third drugs with respect to the time required for the CD4 cell count to rise by at least 100/mm3 (83% for the two groups at 48 months) (The CD4 cell count rose by at least 100/mm months) c.n=43 individuals and 52 events; 18 patients with extrapulmonary tuberculosis, 16 with pulmonary tuberculosis and 9 with both extrapulmonary and pulmonary tuberculosis during the follow-up), Kaposi's sarcoma (n=33), Pneumocystis jiroveci pneumonia (n=23), cerebral toxoplasmosis (n=16) and oesophageal candidiasis (n=15). There was no difference in the occurrence of AIDS-defining event or deaths from an AIDS-defining event between LPV/r and the other third drugs (10% vs. 9% at 48 months) . Overall, 121 patients experienced one AIDS-defining event, 31 patients experienced two, seven patients experienced three and two patients experienced four. Among the 212 AIDS-defining event, the five most frequent were tuberculosis ( months) d.n=91). The other four most common reasons for non-AIDS hospitalization were chronic viral hepatitis (n=13), non-AIDS-efining malignancies (n=12), haematologic disorders (n=12) and psychiatric disorders (n=9). Four patients on LPV/r and two of the patients on another third drug were hospitalized for cardiovascular disease. LPV/r was associated with a higher risk of non-AIDS morbidity with an HR of 1.79  compared to the other third drugs (21% vs. 12% at 48 months) . One-third of hospitalizations were for non-AIDS-defining infection ( months) e.In this large observational study, after taking into account the propensity for receiving LPV/r, LPV/r was associated with shorter treatment durability, less rapid viral suppression and a higher risk of severe non-AIDS morbidity when compared to other recommended third drugs. No difference was found between LPV/r and the other third drugs with respect to immunologic efficacy or AIDS morbidity.Two strengths of our study were the large sample size and the use of propensity scores to control for confounding factors in this observational setting. One limitation is that 30% of patients receiving LPV/r could not be matched. However, their clinical outcomes tended to be worse, and this cannot therefore explain the worse clinical outcomes we observed among the LPV/r-treated patients in our analysis.Although the propensity score method cannot control for unmeasured confounders, the most important ones in terms of prognosis were taken into account in our analyses, except for adherence as no adherence data are available in the FHDH. Our decision to compare LPV/r to all other recommended third drugs combined instead of separately limited the possibility of a strong unmeasured confounder. Our choice to combine EFV and ATV/r was clinically justified because these drugs are recommended “third drugs” in the guidelines. In the ACTG A5202 randomized trial, ATV/r was as efficacious and well tolerated as EFV .We restricted our study to a single NRTI backbone (TDF plus FTC) in order to be able to compare the impact of the third drug. Indeed, it has been reported that the choice of NRTI backbone is a significant predictor of virologic success and treatment failure –19. FinaThe rate of stop or switch was larger in patients receiving LPV/r than in patients receiving another third drug, in keeping with the results of the CORIS study . Here, tThe initial difference in virologic efficacy before six months, between LPV/r and the other third drugs, disappeared after 12 months. A comparative effectiveness study also showed that differences between regimens in terms of virologic efficacy were not as pronounced over time . LikewisDespite the more rapid virologic efficacy of the other third drugs compared to LPV/r during the first six months of our study, the gain in CD4 cells was similar. In clinical trials, no significant difference in the CD4 cell gain from baseline was found at week 48 between the ATV/r and LPV/r and the EFV and LPV/r groups ,5,9,26.Regarding clinical outcomes, although there was no significant difference in AIDS morbidity between the LPV/r and comparator regimens, we found that LPV/r was associated with a higher risk of non-AIDS morbidity. Clinical trials lacked sufficient power to detect differences in clinical outcomes ,9,24,26.This study shows that first-line cART with LPV/r is less durable, provides less rapid viral suppression and is associated with more frequent severe non-AIDS clinical events than other recommended third drugs. These findings support recommendations that LPV/r should be considered as an alternative rather than as a preferred drug for cART-naïve patients, as done in the 2013 French and European guidelines where LPV/r was listed as an alternative ,27.Click here for additional data file.


During treatment with protease inhibitor monotherapy, the number of antiretrovirals with therapeutic concentrations in the cerebrospinal fluid (CSF) is lower, compared to standard triple therapy. However, the clinical consequences are unclear.n=137) or with 2NRTIs (n=136). Neurocognitive function was evaluated in all patients by the Hopkins Verbal Learning Tests, the Colour Trail Tests and the Grooved Pegboard Test at screening, baseline and at Week 48. A global neurocognitive score (NPZ-5) was derived by averaging the standardized results of the five domains. In a central nervous system (CNS) sub-study (n=70), HIV RNA levels in the CNS were evaluated at baseline and Week 48. Clinical adverse events related to the CNS were collected at each visit.A total of 273 patients with HIV RNA <50 copies/mL for over 24 weeks on current antiretrovirals randomized to darunavir/ritonavir (DRV/r) 800/100 mg once-daily, either as monotherapy  than the triple therapy arm . At Week 48, there was no difference between the treatment arms for the five combined domains of the neurocognitive score. At Week 48, the percentage of patients with an abnormal neurocognitive score among the five domains was 12.2% for DRV/r monotherapy and 14.9% for triple therapy. However, one patient on DRV/r monotherapy with a CD4 nadir of 17 cells/µL was hospitalized with HIV encephalomyelitis at Week 24, with HIV RNA 2500 copies/mL in the CSF and 125 copies/mL in the plasma. Symptoms resolved after intensification with high dose zidovudine. A second patient on DRV/r monotherapy with CD4 nadir of 166 cells/µL had a rise in HIV RNA in CSF from <40 copies/mL at baseline to 654 copies/mL at Week 48, with concurrent plasma HIV RNA of 77 copies/mL.In this study for patients with HIV RNA <50 copies/mL at baseline, there was no difference in neurocognitive function between the treatment arms. However two patients on PI monotherapy with CD4 nadir <200 cells/µL developed viraemia in both CSF and plasma, with one symptomatic case. DRV/r monotherapy should be used with caution in patients with nadir CD4 counts below 200 cells/µL.


HCV Triple therapy opens new perspectives for HCV cure in HIV-HCV patients but data concerning the use of HVC DAA-PI in this patients in a real life setting are scarce. Our objective was to evaluate efficacy and safety of Telaprevir (TLV) and Boceprevir ( BOC) based- therapy in our cohort.We included HIV-HCV patients treated with Peg Interferon RIB (PR) plus TLV/BOC between 2011-2013 in a multicenter retrospective cohort. Demographic, clinical and imunologic characteristics were obtained, as well as adverse events and discontinuations. Treatment efficacy and safety data were collected at week (W) 4, 8, 12, 24 and 48 . Success if HCV-RNA became undetectable (PCRHVC-)72 weeks after the end of treatment (SVR). Failure if treatment was discontinued due to virologic failure (VF), adverse events (AE).31 patients were analyzed, 5 Naives and 26 re-treatments . All were Caucasian, 86% were male with a 49 years old’s mean age. Mode of transmission of HIV& HCV was IUDV for 24 patients, MSM for1. Median CD4 counts 692. All were on HAART with undetectable Viral Load in 92%. Background HIV therapy contained in 51% raltegravir (RAL), 20% ritonavir-boosted atazanavir (ATV/r), 12% etravirine (ETV) 9% darunavir (DRV/r),6% lopinavir, efavirenz and rilpivirine. Tenofovir in 72%. Genotype 1a (n=20) or 1b (n=10) or 4 (n=1), METAVIR fibrosis stage was F3F4 in 55%, F2 in 32% and F0F1 in 13% of cases. HVC was treated with PR+ BOC (33%) or TLV (67%). 25 patients reached W72. PCRVHC- was observed in 54% of patients at W4, 67% at W12, 58% at W24 and 58% at W48. SVR was obtained for 58%  and in 51% of cirrhotic patients. Six patients discontinued therapy for VF (n=1) or AE (n=5).Despite SVR increased with DAA-PI based therapy, treatment of HCV in HIV remains complex with multiple challenges, including high pill burden, higher rates of adverse events (AEs) and difficult drug-drug-interactions.


Since China has a unique system of delivering HIV care that includes all patients’ records. The factors related to CD4+ T-cell recovery and viral suppression in patients who have low CD4+ T cell counts at the initiation of HAART are understudied in the China despite subsequent virological suppression  is unknown.The authors conducted a retrospective cohort study using data from the national HIV treatment sub-database of Zhejiang province to identify records of HIV+ patients. Patient records were included if they were ≥ 16 years of age, had an initial CD4 count < 100 cells/μL, were on continuous HAART for at least one year by the end of December 31, 2014; and achieved and maintained continued maximum virological suppression (MVS) (< 50 copies/ml) by 9 months after starting HAART. The primary endpoint for analysis was time to first CD4+ T cell count recovery . Cox proportional hazard regression was used to identify the risk factors for CD4+ T cell count recovery to key thresholds  by the time of last clinical follow-up (whichever occurred first), key thresholds , with patients still unable to reach the endpoints being censored by the end December 31, 2014 .Of the 918 patients who were included in the study, and the median CD4+ T cell count was 39 cells/μL at the baseline. At the end of follow-up, 727 (79.2%), 363 (39.5%) and 149 (16.2%) patients had return to ≥ 200, 350, and 500 cells/μL, respectively. Kaplan-Meier analysis demonstrated that the rate of patients with CD4+ count recovery to ≥ 200, 350, and 500 cells/μL after 1 year on HAART was 43.6, 8.6, and 2.5%, respectively, after 3 years on treatment was 90.8, 46.3, and 17.9%, respectively, and after 5 years on HAART was 97.1, 72.2, and 36.4%, respectively. The median time to return to 200–350, 350–500, ≥ 500cells/μL was 1.11, 3.33 and 6.91 years, respectively. Factors of age , baseline CD4+ count , initial regimens, changes in regimen , and inclusion of a cotrimoxazole prophylaxis  were associated with CD4+ T cell count recovery.The proportion of patients with initially low CD4 counts after nine months of treatment and that achieved continuous virological suppression was greater than 70% for persons with CD4+ count ≥ 350. Conversely, only 35% of patients recovered to levels of 500 cells/μL after 5 years of treatment, and levels continued to rise significantly with further long-term HAART. Early HAART intervention will be necessary for achieving effective CD4+ T cell responses and optimal immunological function in HIV+ patients. Highly active antiretroviral therapy (HAART) has significantly reduced mortality rates in HIV-infected patients due to virological suppression and CD4+ T cell count recovery . ReducinIt is still not clear whether HIV patients with severely impaired immune function (CD4+ < 100 cells/μL) can return to any significant key thresholds  despite achieving a long-term continued MVL suppression (VL < 50 copies/mL) by of 9 months after starting HAART. The aim of this study was to describe CD4 count changes during HAART, and its associated factors affecting the CD4 count in complete recovery to the endpoints  while achieving and maintaining continuous MVL suppression (VL < 50 copies/mL) in patients with lower initial CD4+ baseline count prior to HAART in Zhejiang province, China.In 2014, 103,501 people were diagnosed with HIV-infection in China , with foPatients’ data were obtained from the national treatment sub-database of Zhejiang province. These included all patients who met the national treatment guidelines  and were provided free drug treatment .All patients who were ≥ 16 years before treatment, had an initial CD4 count < 100 cells/μL, and had received continuous treatment for at least one year by the end of December 31, 2014 were included in the study. Patient records were also included if they achieved and maintained continuous suppression by 9 months after starting HAART.Exclusion criteria were as follows: VL ≥ 50 copies/mL, if the VL detection had been interrupted  during the treatment, and if there was loss of follow-up such as death or discontinuation of treatment. Two sensitive PCR techniques for measuring VL with the lower limit of detection of 50 copies/mL were used in Zhejiang province. Therefore, VL < 50 copies/ml was used as the maximum virological suppression in this study.Seven drugs divided into three categories were provided in the National Free Antiretroviral treatment Programme. The initial HAART regimens included 2 nucleoside reverse-transcriptase inhibitors (NRTIs) and 1 non-nucleoside reverse-transcriptase inhibitor (NNRTI) or 1 protease inhibitor (PIs). The NRTIs consisted of Stavudine (D4T), Zidovudine (AZT), and Tenofovir (TDF), with Lamivudine (3TC), the NNRTIs included Nevirapine (NVP) and Efavirenz (EFV), the PIs was Lopinavir/r (LPV/r). TDF and LPV/r was as the secondary line drugs before 2013. In 2013, TDF could be used as the first line treatment drug according to the National Treatment Guidelines. Meanwhile owing to the side effect of treatment or drug toxicity, D4T is no longer used in China, and patients who took D4T changed to use AZT or TDF in 2013.t test, One-Way ANOVA and the chi-square (χ2) test. Semi-annual changes in CD4 counts for five years after HAART to the end of December 31, 2014 were analyzed. The calculation process of CD4 count was that, for example, calculated the CD4 count in 6 months after treatment, the CD4 tested date between 4.5–7.5 months was collected, if the patient had more than one time of CD4 results in the period, the date of CD4 results closer to the 6 months was collected. We determined the mean CD4  and median  in the absolute CD4 count at baseline and semiannually thereafter.Descriptive statistics were calculated with the Student’s The endpoint of the study was when CD4+ T counts first achieved key thresholds  and were defined complete and successful CD4 recovery. Person-years were calculated from the date of starting HAART to the time of last follow-up, whichever occurred first  key thresholds , with patients still unable to recovery the endpoints censored by the end December 31, 2014 . Kaplan-Meier plots were used to estimate the rates of CD4+ recovery to the thresholds. Cox proportional hazards regression were used to identify the factors associated with endpoints of CD4+ count recovery for participants in this study.P < 0.1 and factors previously shown to be associated with the CD4+ T cell count recovery after assessing collinearity and possible interactions were placed in full multivariable regression models, including age, gender, transmission route, presence of infection with Mycobacterium tuberculosis (TB) before treatment, initial CD4 count, WHO clinical stage, presence of change in regimen, and cotrimoxazole prophylaxis (TMP-SMZ) during the treatment and the initial regimen. Complete follow-up data were collected, which included every CD4 test results, HIV viral load measurements, and any changes in drug regimen.Univariate factors with All analyses were performed using STATA 12.1 .This study was reviewed and approved by the Institutional Review Board of the National Center for AIDS/STD Control and Prevention, China CDC . All the data was obtained from the national HIV treatment sub-database of Zhejiang province. All the patients who received the national free treatment at baseline, the local CDC or health-care providers would inform patient that all the treatment information may be used for the monitoring analysis. All the patients signed the informed consent.A total of 918 patients were included in the study, and the total follow-up was 2722.1 person-years by the deadline of Dec 31, 2014, with an average 2.97 ± 1.74 years. The median treatment time was 2.5 years (IQR 1.6–4.0 years), of which the shortest was 1.0 year and the longest was 9.5 years. The person-years of CD4+ count achieved the thresholds  were 0.99 years (IQR 0.50–1.57 years), 1.79 years (IQR 1.16–2.74 years), and 2.19 years (IQR 1.31–3.34 years). At the end of follow-up, 727 patients (79.2%) had returned to ≥ 200 cells/μL, 363 of patients (39.5%) had achieved greater than 350 cells/μL, and 149 patients (16.2%) returned to ≥ 500 cells/μL. As a result, the total rate of CD4+ count recovery the thresholds  were 83.7/100 person-years, 47.8/100 person-years, and 39.3/100 person-years, respectively.Univariate Cox regression models analysis found that the factors of greater age and baseline CD4+ count  were associated with the CD4+ count recovery to ≥ 200 cells/μL. Among patients who used first line drugs as the initial treatment regimen, the use of the AZT compared to D4T, of EFV compared to NVP, of changing regimen,  in China with lower CD4 counts at the start of the initial HAART treatment despite achieving continuous MVL suppression. Records from the national database showed that 727 79.2%), 363 (39.5%) and 149 16.2%) of patients had recovery to defined endpoints . The total proportion of CD4+ count recovery to the thresholds were 83.7/100 person-years, 47.8/100 person-years, and 39.3/100 person-years, respectively. The CD4+ count of the majority of patients was significantly increased after treatment, even at 5 years. Specifically, rapid increase was seen in the first year of treatment, while the increases in 2–5 years were gradual. Previous studies revealed that HIV+ patients with high CD4+ initial count (≥ 350 cells/μL) could have complete recovery to either HIV-negative or normal levels. However, the corresponding recovery would be lower in patients with initial CD4 count < 200 cells/μL .2% of pa. Some st.2%, 363 A study from the UK (CHIC) showed that patients with CD4+ T cell count below 100 cells/μL at initial treatment and had maintained continuous VL suppression after treatment, had over 50, 14, and 3% chance of returning to ≥ 200, 350, 500 cells/μL after 1 year of treatment, respectively, and over 90, 59, and 25% after three years of treatment, respectively [We found that factors including increasing age, baseline CD4+ count, initial regimens, changes in regimen and whether TMP-SMZ was taken during the treatment were associated with CD4+ T cell count recovery. Previous studies demonstrated that increasing age is a well-recognized protective factor for CD4+ count recovery ,21,22. CSimilar to another other study ,26, our Patients who used EFV for initial regimens had a higher rate of incomplete CD4+ recovery compared to the NVP regimen, while the AZT regimen compared to D4T regimen significantly affected CD4 recovery. Previous studies showed that EFV could produce higher virological suppression rates than NVP, whether the regime contained TDF or AZT , which mD4T as the first line drug was used in China before 2013. However, severe side effects associated with D4T use, such as peripheral neuropathy, lactic acidosis and lipodystrophy were frequently observed and accumulated over time in several African cohorts ,35. A stEver changing regimen during HAART was associated with the CD4+ count recovery. Some studies suggested first antiretroviral therapy was often switched to simpler, more potent, better-tolerated regimens than the replaced regimen ,38. Prevjirovecii pneumonia, Toxoplasmosis and malaria [Several studies have demonstrated that cotrimoxazole prophylaxis could protect against opportunistic infections, such as Pneumocystis  malaria . A study malaria , other s malaria . Study f malaria , and thaSeveral points should be considered. The CD4+ count recovery to the key endpoints  was analyzed while patients achieved MVL suppression (VL < 50 copies/ml) during the treatment, thus increasing the validity of the study. The risk factor analysis of CD4+ count recovery focused on the key thresholds. However, this study has several limitations. We identified all patients with initial CD4+ T count < 100 cells/μL in the analysis, but over half of the patients did not achieve continuous MVL suppression or did not meet other criteria, were excluded. This means that our findings focus on patients with lower CD4+ T cell count in the initial HAART, while achieving continuous MVL suppression by the time of 9 months after treatment. Owing to the side effect of treatment or drug toxicity, D4T was no longer used in China in 2013, and patients who took D4T changed to use AZT or TDF, so consideration should be given to whether TDF might affect the CD4+ count recovery. This was also an observational study therefore patients were not randomly chosen to start initial treatment regimens which were later changed during the course of treatment, as such findings should be interpreted with caution.In conclusion, this is the first study that examines the CD4+ T cell count recovery in HIV+ patients with lower CD4+ T cell count (< 100 cells/μL) at initial treatment, achieving and maintaining continuous virological suppression by the 9 months after HAART in China. The proportion of patients with initially low CD4 counts after nine months of treatment and that had achieved continuous virological suppression was greater than 70% for persons with CD4+ count ≥ 350. Conversely, only 35% of patients recovered to 500 cells/μL after 5 years of treatment, and continued to significantly rise with long-term HAART. Early HAART intervention will be necessary for achieving effective CD4+ T cell responses and optimal immunological function in HIV+ patients.


The assessment of adherence to antiretroviral therapy (ART) is important in order to predict treatment outcomes. Lamivudine (3TC) is one of the most widely used NRTIs in China, but its concentrations in hair and association with virologic failure and drug resistance have not been studied.We conducted a cross-sectional survey to investigate 3TC concentrations in hair as a predictor of virologic failure and drug resistance among HIV patients receiving free ART. We also compared the capacity of hair 3TC concentrations with self-reported adherence in predicting virologic responses. Hair 3TC concentrations were detected through the LC-MS/MS system.+ cell counts, initial treatment regimens with 3TC, and current regimens with second-line drugs, influenced the association between hair 3TC concentrations and virologic suppression. In patients who experienced virologic failure with HIVDR, with a threshold of 180 ng/g, the sensitivity and specificity were 70.0% and 74.4%, respectively. Hair 3TC concentrations had higher sensitivity and specificity in predicting virologic failure and drug resistance than self-reported adherence.In patients without HIV drug resistance (HIVDR), with a threshold hair 3TC concentration of 260 ng/g, the sensitivity and specificity in predicting virologic suppression were 76.9% and 89.9%, respectively. Some factors, including CD4The hair 3TC concentration was a stronger indicator than self-reported adherence in predicting virologic failure and drug resistance in HIV patients receiving free ART. Highly active antiretroviral therapy (HAART) effectively reduces HIV patients’ morbidity and effectively prolongs their disease-free lives. According to a previous study, antiretroviral treatment outcomes are relevant to immunologic, pharmacokinetic factors, and adherence to regimens . Strict Many methods are used to evaluate the adherence to antiretroviral therapies, such as self-reported questionnaires, pill counting, the Medication Event Monitoring System (MEMS), the visual analogue scale, and drug concentrations in plasma or urine , 4. The The current recommended regimens in China include two nucleotide or nucleoside reverse transcriptase inhibitors (NRTIs) and one non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor (PI). Since 2008, China’s National Free Antiretroviral Treatment Program (NFATP) had changed its first-line ART regimen by replacing didanosine (DDI) with lamivudine (3TC) , 20. So The IRB of Chinese Center for Disease Control and Prevention approved this study and the approval number was X120331207. We obtained written informed consents.+ cell count, HIV-1 RNA viral load testing, and genotypic drug resistance (HIVDR) testing as previously described [We conducted a cross-sectional survey in HIV patients receiving the lamivudine regimen from 2013 to 2014. 287 patients were enrolled from Zhejiang, Anhui, and Henan Provinces. The inclusion criteria were: patients ≥ 18 years old, had received national free ART treatment for ≥12 months, current treatment regimen included lamivudine, and willingness and consent to participate. Patients who were treated with second-line regimens as the initial treatment were excluded. Basic information , blood specimens, and hair specimens for lamivudine were collected. Hair samples were collected from the occipital area as previously described because it has the lowest variability in hair growth rate , 27. At escribed , 30. All15N2,13C as an internal standard) and 0.9 ml methanol were added to each sample. Samples were shaken in a 37°C water bath overnight, followed by centrifugation at 13,000 rpm for 5 minutes. 500 μL supernatant was extracted and mixed with 500 μL deionized water, and then the mixture was whirled. 10 μL of the mixture was used for LC-MS/MS analysis.The hair 3TC concentration was determined using liquid chromatography and tandem mass spectrometry (LC-MS/MS) at iPhase Pharma Services in Beijing, China. Briefly, 3TC concentrations in 1–1.5 cm hair samples near the scalp approximately represented the drug accumulation in the past month. Hair samples were cut into small segments, yielding approximately 2 mg of hair , and 50 15N2, 13C. The declustering potential and collision energy were 30 V and 18 V, respectively, for lamivudine and IS. The source temperature was 550°C. The HPLC conditions were as follows: the column was an Agela venusil ASB C18, (50 × 4.6mm), 5 μm, 150Å, and the mobile phase was composed of methanol and HPLC-grade water. Elution was achieved with an isocratic flow of water:methanol  at a flow rate of 0.8 mL/min. Data processing was performed using Analyst 1.5 software.The LC-MS/MS system consists of an Agilent 1200 Series pump (G1312A) and autosampler (G1367B), and an AB Sciex LC triple quadrupole tandem mass spectrometer. The mass spectrometer was set to electrospray ionization in a positive multiple reaction monitoring mode. The precursor/product transitions (m/z) were at 230.3 > 112.2 m/z for lamivudine and 233.2 > 115.3 m/z for the internal standard (IS) lamivudine-The calibrated hair samples were prepared as follows: 2 mg of blank cut hair samples were placed into different test tubes, and 50 μL 0.4, 0.8, 2, 5, 20, 40, 64, or 80 ng/ml standard solutions was added. Then, these samples were treated in the same way as above. We controlled the relative standard deviation (RSD) of the standard curve at less than 15%. The linear range of the standard curve was 10–2000 ng/g.Questionnaires were double-entered and validated with EpiData 3.1  and then were analyzed by the Statistical Analysis System  and SPSS Statistics 19 . Demographic variables were described with descriptive statistics and the Wilcoxon signed rank test was used to compare hair 3TC concentrations among the three groups for virologic suppression, virologic failure without HIVDR, and virologic failure with HIVDR. In order to explore the association between the 3TC concentration in hair and virologic suppression/drug resistance, we used multivariate logistic regression to calculate the odds ratios and 95% confidence intervals. At the same time, we selected cut-off concentrations with receiver operating characteristics. In addition to investigating factors which have an influence on the relationship between hair 3TC concentrations and viral load, we used stratified analysis through the Chi-square test or Fisher’s exact test to calculate the P value among different stratifications. Hypothesis testing was two-sided with α = 0.05.A total of 287 patients from Zhejiang, Anhui, and Henan Provinces of China were enrolled in the survey. The characteristics of the subjects are shown in Hair 3TC concentrations among people are shown in We then conducted a multivariate logistic regression model to examine the association of different indictors with the dichotomous outcome of virologic suppression after controlling for several variables, such as age, sex, income per month, marital status, education, occupation, HIV transmission route, initial ART regiment, current ART regiment, duration of ART, and CD4 count at the survey . The adj+ cell counts, initial ART treatment, and current ART treatment. Patients who had higher CD4+ cell counts (≥350 cells/ml) had lower positive predictive values  and higher negative predictive values . What is more, we found that patients who had received 3TC as the initial ART treatment regimen had higher sensitivity . Receiving second-line ART treatment may lower the negative predictive values .Through the receiver operating characteristic curve (ROC), the optimal cut-off (that maximized the Youden Index) was 260ng/g. The sensitivity, specificity, positive predictive value, and negative predictive values were 54.4%, 89.9%, 67.2%, and 83.9%, respectively. The large amount of false-negatives  resulted in a lower sensitivity. Thus, we constructed another receiver operating characteristic curve (ROC) among patients without HIVDR, and the optimal cut-off was also approached at 260ng/g, with 76.9% sensitivity, 89.9% specificity, 58.8% positive predictive value, and 95.4% negative predictive value. The sensitivities and specificities at different hair 3TC concentrations are listed in The threshold of hair 3TC concentrations associated with virologic failure with HIVDR is presented in In our study, we first demonstrated that 3TC concentrations in hair are significantly different among groups of virologic suppression, virologic failure without HIVDR, and virologic failure with HIVDR. Patients who had a suppressed viral load had the highest hair concentration, illustrating their favorable adherence. Intermediate concentrations in virologic failure patients were associated with the emergence of drug resistance mutations. This may be because of irregular missed doses or non-adherence , 32.In addition, we also found that hair 3TC concentrations have a strong association with virologic outcomes and are able to give a comparatively accurate prediction of virologic outcomes. According to a previous report conducted by Gandhi , the oddAccording to our previous studies, self-reported adherence variables of the questionnaire were significantly associated with HIV virologic failure and/or HIVDR, including missed doses and the ratio of on-time drug intake in the past month , 34. TheThe limitations of our study were: first, our sample recruitment from only three provinces could not guarantee a representative sample of all HIV patients in China. The size was not large enough and did not include all kinds of patients in China, which may have lowered the accuracy of the threshold value. Second, most of the participants had been treated for a long-time which could lead to more patients with HIVDR, while hair 3TC concentrations may only reflect the ART treatment adherence in the past month. The relationship between hair 3TC concentrations and HIVDR might be underestimated. Third, data collection did not include any pharmacokinetic related indicators, which may influence the association between hair 3TC concentrations and viral load. We performed this study in a cross-section manner and a longitudinal assessment is required and will be done in the future in order to show causality.However, these limitations should not affect our conclusion that hair 3TC concentrations can strongly predict virologic outcomes in HIV patients and are a better indicator than self-reported adherence questionnaires in predicting virologic outcomes and HIVDR. Testing lamivudine levels in hair is a simple and safe method for evaluating the ART adherence over a period of months in resource-limited settings. China should establish a centralized unit of drug resistance surveillance to monitor ARV adherence through testing hair concentration of drugs in HIV patients.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


The resistance profiles of first-line antiretroviral therapy (ART) regimens after virologic failure have yet to be studied in a clinic setting in the modern treatment era. Time to virologic failure among three standard first-line regimens and the resistance profiles of these failures were compared.All HIV-positive persons aged 16 and over starting a three-drug first-line ART regimen were retrospectively identified at a Toronto community clinic (1 January 2006–1 January 2013). The regimens included a backbone of two NRTIs and a third agent; a PI, an NNRTI, or an II. Patients must have been on treatment for at least 14 days and have at least one VL test within 6 months after starting treatment. The primary outcome was virologic failure defined as either: no suppression by 6 months, or after suppression, two consecutive, detectable VL200 copies/mL at least 14 days apart or one VL>200 copies/mL. Time to failure was compared using a proportional hazards model adjusting for demographic and clinical factors. Resistance profiles of NRTIs and third agents are described in patients with virologic failure who had both baseline and virologic failure genotypes.Six hundred sixty patients  were included with a mean age of 38.9 and a median follow-up period of 35.3 (32.2–39.3) months. Distribution of third agent use was: PI 37.3% (n=246), NNRTI 55.9% (n=369) and II 6.8% (n=45). Virologic failures occurred in 81/246 (33%) with PI, 87/369 (24%) with NNRTI and 11/45 (24%) with II. Compare to PIs, time to failure was longer with NNRTIs (p=0.0013) and similar for IIs (p=0.1562). No evidence that failure with NNRTIs was different from IIs (p=0.9139). Of the 660 patients, 567 (86%) had a baseline genotype. Of the 567 patients, 179 had virological failure. Of the 179, 145(81%) had a baseline genotype and only 37 (21%) had both a baseline and follow-up genotype. Upon failure, emerging ART resistance was rare. No new PI or II mutations were identified and one new NNRTI (Y181C) mutation was identified. Three patients taking PI-based regimens developed NRTI mutations .Time to virologic failure was significantly greater in the NNRTI group compared to the PI group. If failure did occur, ART resistance rarely developed with no PI mutations but a few NRTI mutations in those taking PI-based regimens, and NNRTI mutations in those taking NNRTI-based regimen.


Although the majority of HIV-infected patients who begin potent antiretroviral therapy should expect long-term virologic suppression, the realities in practice are less certain. Durability of viral suppression was examined to define the best timing of targeted adherence strategies and intensive viral load monitoring in an urban clinic population with multiple challenges to ART adherence. We examined the risk of viral rebound for patients who achieved two consecutive viral loads lower than the lower limit of quantification (LLOQ) within 390 days. For 791 patients with two viral loads below the LLOQ, viral rebound >LLOQ from the first viral load was 36.9 % (95 % CI 32.2–41.6) in the first year, 26.9 % (95 % CI 21.7–32.1) in the year following one year of viral suppression, and 24.6 % (95 % CI 18.4–30.9) in the year following 2 years of viral suppression. However, for patients with CD4 ≥300 cells/µl who had 3–6 years of virologic suppression, the risk of viral rebound was very low. At the population level, the risk of viral rebound in a complex urban clinic population is surprisingly high even out to 3 years. Intensified monitoring and adherence efforts should target this high risk period. Thereafter, confidence in truly durable virologic suppression is improved. HIV-1 RNA viral load (VL) monitoring is currently recommended every 3–4 months for patients on antiretroviral therapy (ART). Among those patients with suppressed viral load for greater than 2 years, monitoring at 6 months intervals is considered reasonable [The objective of the analysis was to describe the risk of rebound among patients with virologic suppression. We used the HIV Clinical Case Registry to describe the population of patients with HIV infection who had at least one outpatient visit to the Washington DC Veterans Affairs Medical Center from January 1, 2005 to December 31, 2011. We evaluated every paired HIV-1 viral load (VL) and CD4 count performed by the Infectious Diseases Laboratory during the period of observation. Time to rebound was computed using consecutive sequences of observations for subjects whose initial two viral loads were below the lower limit of quantification (LLOQ) and had a viral load measurement within 390 days. Although the median frequency of viral load monitoring for the clinic between 1999 and 2011 was 113 days , we aimed to be inclusive of those patients with more minimal monitoring up to a maximum of approximately 13 months between measurements.Two analyses were performed. In Analysis A, viral rebound was defined as a viral load greater than the LLOQ. In Analysis B, viral rebound was defined as a viral load greater than 200 copies/ml. Subjects were classified as censored either if they reached the end of the study while remaining virally suppressed, or if at some point a gap of 390 days between tests occurred. Only the first period of virologic suppression for each patient was included in these analyses.Kaplan–Meier and life table curves were generated to describe time to viral rebound in the cohort. Analyses were done on the cohort as a whole and also as stratified by CD4 groups <300 cells/µl and >300 cells/µl at the time of inclusion. Homogeneity of survival curves in the latter case was tested via the log rank test. Cox’s Proportional Hazards model was also used to quantify the degree and direction of relative risk between CD4 groups. The proportional hazards assumption was assessed visually using log–log survival plots. Analysis was performed using the lifetest, phreg, and freq procedures , and data management was performed using R 3.0.1.From January 2005 to December 2011, 1544 patients had at least one outpatient visit. Among these patients, 97 % were male, 75 % were black or African American, and the median age was 50 years. Reported risks for exposure to HIV included sex with a male (30 %), sex with a female (50 %) and injection drug use (20 %). Approximately 30 % of patients were co-infected with Hepatitis C and other co-morbid illness was common including drug and alcohol dependence and mental health disorders in approximately 50 % of patients. Approximately 75 % of patients received antiretroviral therapy (ART) during this period. Among those on ART, 30 % received a non-nucleoside reverse transcriptase inhibitor (NNRTI) based regimen (95 % efavirenz-based), 30 % received a protease inhibitor based regimen (85 % boosted with ritonavir and 15 % unboosted), and 3 % received an integrase inhibitor or other regimen. The remaining 37 % of patients either switched drug classes during this period or received a regimen consisting of three or more drug classes, predominantly nucleosides, NNRTIs and boosted PIs.During 2005–2011, there were a total of 14,434 paired VL and CD4 results from 1355 patients. Of these, 791 subjects met the criteria of two consecutive viral loads below the LLOQ within 390 days, then followed by at least one subsequent viral load.Among our cohort of 791 patients, 431 (55 %) experienced viral rebound. Of the 360 patients with sustained viral suppression, 317 (40 % of our cohort) were censored having reached the end of the study period without experiencing rebound, and 43 (5 % of the cohort) were censored due to having had a gap of at least 390 days between testing.334 patients experienced rebound with detectable viremia >200 copies/ml. Of the remaining 457 patients with viral suppression, 404 were censored having reached the end of the study period without rebound and 53 for having had a testing gap of 390 day or more Table .Table 1S2 = 32.26 for >LLOQ and 29.99 for >200, p < 0.0001).As shown in Fig. >300 cells/μl were at lower risk of viral rebound than those with <300 cells/μl: 29.8 % (95 % CI 28.3–35.2) versus 54.1 % (95 % CI 48.8–65.4) in the first year, 24.2 % (95 % CI 22.9–30.7) versus 35.0 % (95 % CI 31.0–49.2) in the second year and 22.9 % (95 % CI 21.3–30.8) versus 31.1 % (95 % CI 26.7–50.4) in the third year. This difference achieved statistical significance in the first year and in the second year at p < 0.05.As shown in Table >300 in the year following three years of virologic suppression, 11.3 % overall and 7.7 % for CD4 >300 in the year following four years of virologic suppression, 7.8 % overall and 6.5 % for CD4 >300 in the year following five years of virologic suppression. For 79 patients in both CD4 strata who achieved 5.7 years of virologic suppression, none had viral rebound at a median of 10 months of follow-up.After three years of virologic suppression, the risk of viral rebound dropped significantly. For patients who achieved three to five years of virologic suppression, the risk of failure were 12.8 % (95 % CI 7.3–18.2) overall and 9.7 % for CD4 The risk of viral rebound by year, defined as >200 viral copies/ml  may represent a population who may have late HIV diagnosis, with very low nadir CD4 and immune restoration failure due to inability to reconstitute depleted T cell populations despite virologic suppression. Some also have a low CD4 due to a co-morbidity such as Hepatitis C and cirrhosis despite virologic suppression. However, those with a CD4 cell count <300 are over-represented by those who are under-treated for HIV due to the failure to engage in care and attend visits to the clinic ; and those who come to their visits but fail to take prescribed antiretroviral therapy.On the other hand, after 3 years of sustained virologic suppression, the risk of rebound is quite low and our confidence in a twice yearly monitoring strategy improves. This risk declines even further by 6 years, an observation also seen by Lima et al. . In our We examined the risk of viral rebound with rebound defined both as >LLOQ and >200 copies/ml. Although the >200 definition is intended to allow for clinically insignificant “viral blips” and follows the antiretroviral guideline definition , recent For the individual patient, clinician decisions as to frequency of viral load monitoring should be informed by psychosocial and neurobehavioral factors , 17 and Viral load monitoring is costly and particularly prohibitive in resource-limited countries. We previously demonstrated that frequent CD4 monitoring among patients with CD4 ≥300 cells/µl and virologic suppression was not necessary . A less Our study had several limitations. This was a retrospective evaluation from a single, urban medical center caring for predominantly African-American men. The risk of viral rebound by antiretroviral regimen was not examined. This analysis intended to address risk for the population overall, for all patients who achieved initial virologic suppression. We examined data beginning in 2005 when efavirenz and simpler once daily regimens were more widely in use to reflect the “current” era of ART. Although the higher barrier to mutation of the newer once daily integrase strand transfer inhibitors may reduce the risk of viral mutations associated with nonadherence compared to once daily NNRTI regimens, the findings here still provide relevant guidance to a rational approach to viral load monitoring and to timing of strategies to improve adherence and reduce the risk of viral rebound.>300 cells/μL. As we enter eighteen years post approval of potent antiretroviral regimens, better defining the relative risks for viral rebound allows better and more focused use of resources and improvement of our capacity to achieve truly durable virologic suppression in all patients initiating antiretroviral therapy.In conclusion, HIV-infected patients in our urban clinic had high rates of viral rebound in the first three years following virologic suppression, highlighting the time when targeted efforts to assure antiretroviral adherence may be particularly meaningful. On the other hand, this data demonstrated that once virologic suppression is achieved and sustained for three years, the risk for rebound declines substantially, supporting guidance for reduced monitoring particularly for patients with CD4 cell counts


Although there are many potential explanations for this, we suggest that important factors include poor sampling resolution and complex B-cell dynamics that are difficult to summarize using simple summary statistics. Importantly, we find a significant association between observed Gini indices and sequencing read depth, and we conclude that more robust analytical methods and a closer integration of experimental and theoretical work is needed to further our understanding of B-cell repertoire diversity during viral infection.Advances in immunoglobulin (Ig) sequencing technology are leading to new perspectives on immune system dynamics. Much research in this nascent field has focused on resolving immune responses to viral infection. However, the dynamics of B-cell diversity in early HIV infection, and in response to anti-retroviral therapy, are still poorly understood. Here, we investigate these dynamics through bulk Ig sequencing of samples collected over 2 years from a group of eight HIV-1 infected patients, five of whom received anti-retroviral therapy during the first half of the study period. We applied previously published methods for visualizing and quantifying B-cell sequence diversity, including the Gini index, and compared their efficacy to alternative measures. While we found significantly greater clonal structure in HIV-infected patients versus healthy controls, within HIV patients, we observed no significant relationships between statistics of B-cell clonal expansion and clinical variables such as viral load and CD4 This Some of the most notable findings in this field have come from detailed investigation of the interactions between the humoral immune system and HIV-1 infection. Much of this work has focused on observing and understanding the development of broadly neutralizing antibodies (bNAbs) in order to aid the development of preventative HIV-1 vaccines . InteresDespite these advances, more general trends in B-cell diversity and clonal dynamics during HIV-1 infection are still poorly understood, particularly during early infection. While some studies have contrasted the plasmablast, naive and memory B-cell content between early and chronic infections , the divMost previous studies that investigated the repertoire of B-cell receptor (BCR) diversity in peripheral blood  have ty+ T-cell counts were measured. Three patients were untreated, while five received ART for the first 48 weeks of the study only. This study design not only allows us to track individual B-cell clones during early infection, but also to test for associations between the dynamics of B-cell sequence diversity and clinical variables, including treatment status.To better understand B-cell repertoire dynamics during early HIV infection and the degree to which it is modulated by ART, we used deep-sequencing to capture the diversity of Ig heavy-chain sequences from eight HIV patients enrolled in the short pulse anti-retroviral therapy at seroconversion (SPARTAC) trial . This isFor each patient and each time point, we used a high-throughput Illumina MiSeq platform to obtain paired-end reads from Ig heavy-chain sequences that represent the mixture of antibody classes in peripheral blood. Within each patient, we extended a previous single-linkage clustering approach  to class2.(a)Peripheral blood mononuclear cells (PBMCs) were isolated from eight patients with primary HIV-1 infection recruited from the SPARTAC study . All had(b)et al. [−1) was added. RT was performed at 50°C for 60 min before heat-inactivation at 70°C for 15 min. PCR amplification of cDNA (5 μl of the RT product) was performed with the JH reverse primer and the FR1 forward primer set pool (0.25 μM each), using 0.5 μl Phusion® High-Fidelity DNA Polymerase (Finnzymes), 1 μl dNTPs (0.25 mM), 1 μl DTT (0.25 mM), per 50 μl reaction. The following PCR programme was used: 3 min at 94°C, 35 cycles of 30 s at 94°C, 30 s at 60°C and 1 min at 72°C, with a final extension cycle of 7 min at 72°C on an MJ Thermocycler.RT-PCR reagents were purchased from Invitrogen and primers (supplied by Sigma Aldrich) are described by Van Dongen et al.  and in e(c)http://sourceforge.net/projects/quasr) [E-value thresholds of 1 × 10−10 and 1 × 10−3, respectively. Primer sequences were then trimmed from the reads, and sequences retained for analysis only if both primer sequences were identified and if both forward and reverse sequence lengths were more than 100 bp. Lastly, a second BLAST analysis was used to identify the IgHV genes of retained reads. Specifically, BLAST [E-value thresholds for IgHV and IgHJ genes were 10−70 and 10−20, respectively, due to their different gene lengths). The combined per-base error rate for the RT-PCR and sequencing process of the MiSeq platform was 2.06 × 10−4 [MiSeq libraries were prepared using Illumina protocols and sequenced by 150 bp paired-ended MiSeq (Illumina). MiSeq reads were filtered for base quality (median more than 32) using QUASR (s/quasr) . Sequencs/quasr)  were rets/quasr)  with E-vy, BLAST  was usedy, BLAST  The data comprised non-overlapping paired-end reads separated by a gap of variable and unknown length. This necessitated certain heuristic measures during data processing and the two reads of each pair were aligned separately to ensure positional homology. As above, reference IGHV and IGHJ segments were obtained from IMGT . Gaps we(e)Sequences from all time points within each patient were pooled and assigned to clones using single-linkage agglomerative clustering using the Hamming distance between two sequences , while i(f)et al. [http://igraph.sourceforge.net; see [The diversity of BCR sequences was qualitatively visualized using the network approach developed by Bashford-Rogers et al. . Brieflynet; see  for detaThree sample summary statistics were applied to the BCR sequences obtained at each time point to summarize their clonal diversity: (i) mean clone size, (ii) vertex Gini index, and (iii) the proportion of reads in ‘large clones’. Each of these three statistics is described below.et al. [For each time point and each clone, clone size was defined as the number of reads in the clone at that time point divided by the total number of reads at that time point. Mean clone size was calculated as the arithmetic mean of this distribution of clone sizes. Next, the vertex Gini index was used to summarize inequality in BCR sequence frequency; the index equals unity if all reads have the same BCR sequence , and equals zero if each BCR sequence is equally common . As defined above, vertex size equals the number of identical reads with a unique BCR sequence, so the vertex Gini index was computed directly from the vertex size distribution as formed using a clustering cut-off of zero. Bashford-Rogers et al.  exploredany of the time points in which they were found. We quantified these by calculating the proportion of reads at each time point that belong to ‘large clones'. Additionally, we wished to describe changes in the very upper tail of the clonal size distribution. To do so, we plotted the sizes of the 20 largest clones as a proportion of the total number of reads at each time point. These values are for illustrative purposes only and are not used as sample statistics.Clones were classified as ‘large clones' if they comprised at least 0.1% of the reads sequenced at (g)p = 0.02) and read depth (p = 0.001). A plot of Gini index values against read depth for each time point highlights the variation in read depth among patients . To ensure that comparisons among patients are reliable and not an artefact of read depth variation, all further analyses were undertaken on subsamples of the original data. Specifically, 70 000 sequences were randomly sampled from each time point in each HIV+ patient (the lowest number of reads available for a HIV+ patient sample was 74 861). When comparing HIV+ patients with healthy controls (see §2i), then 5000 sequences were randomly sampled from each control and HIV+ dataset (the lowest number of reads available for a control patient was 5087). In each case, random sub-sampling of reads was repeated 10 times. As variance in BCR statistics among these 10 repetitions was very low (less than 1 × 10−4), we only report the mean values of the 10 sub-sampling repetitions.Preliminary statistical analysis using ANOVA showed that Gini index values were significantly associated both with patient identity ((h)+ counts using linear regression. p-values were adjusted for multiple hypothesis testing using the Benjamini–Hochberg procedure [+ count were scaled to a mean of zero and variance of unity before linear regression and ANOVA analysis.To examine the relationship between BCR sequence diversity and clinical variables, we compared each of the above BCR statistics to log and CD4rocedure  (as impl(i)To test whether BCR sequence diversity differs between HIV-infected and uninfected individuals, we analysed previously published data from a cohort of six healthy patients . For eac3.c) appears more polyclonal than for patient 3 (figure 1a) at this time. As expected, at neither time point is the BCR population dominated by a single large clone, as was often observed in samples from B-cell lymphoma patients [figure 1patients . The plo4 to 1.0 × 106 filtered BCR reads per sample). BCR network analysis was applied to these sequencing datasets to quantify the clonal architecture of these samples according to Bashford-Rogers et al. [Full results from all patients are summarized in figures s et al. . Four pl(a)All three untreated patients (1–3) showed peak viral loads at or within four weeks of enrolment, and reduced, but persistent viraemia after 52 weeks corresponding to set point viral load. Patient 1 had an additional peak in viral load at 24 weeks, suggesting a superinfection event, and showed a higher viral load for a longer duration than patients 2 and 3. In all untreated patients, Gini indexes and the proportion of reads in large clones were typically higher during the first half of the study, when viral loads were higher. Hence at these times, a higher proportion of the BCR sequence population was composed of common sequences/clones. When ‘large clones' dominated the BCR population (e.g. week 24 in patient 2), that dominance was not the result of a single dominant clone, but rather resulted from the concurrent increase in frequency of a large number of different clones (see bottom plot of each panel in (b)−1 , coinciding with the period of ART. As expected, viral load values across all time points were significantly lower in the treated group than the untreated group . Patients 5–8 showed a rebound in viral load at week 52, after the cessation of ART, while the rebound in patient 4 was not as strong and viral loads remained relatively low (less than 21 000 copies ml−1) throughout the study period. In patients 5–7, viral load decreased in week 60 before stabilizing at 108 weeks at a similar level to that in untreated patients.All five treated patients (4–8) showed a rapid decrease in viral load soon after the start of the study, with counts in weeks 16–24 below 100 copies mlThe dynamics of B-cell diversity and clonality in the treated patients were highly variable. Patient 7 showed a striking pattern after cessation of ART: at week 60, there was a polyclonal expansion (such that most BCR sequences fell into ‘large’ clones) which remained in week 108. Patient 8 also showed polyclonal responses and an increase in the proportion of sequences in large clones at weeks 52 and 108.a). Across time points, this persistent clone occupied between 2.4 and 5.1% of all BCR sequences.BCR diversity dynamics in patient 6 in many ways resembled those of untreated patients 2 and 3, with a peak in the prevalence of ‘large clones' in week 24, and low clonality in week 108. Patient 4 exhibited high viral load and clonality at week 4, after which both remained low for the rest of the study. Patient 5 showed a comparatively stable level of clonality through time, with the proportion of sequences in large clones ranging from 0.13 to 0.45. Notably, patient 5 is the only patient to exhibit a ‘large clone’ that persisted throughout the study period (red bars in the bottom panel of figure 3(c)+ cell count . To enable direct comparisons among patients, all datasets were sub-sampled to exactly 70 000 reads (see §2g). For each patient, mean values during the early and late periods were used to account for autocorrelation (see §2h). As shown in + cell count, or estimated days since seroconversion with any of the three BCR diversity statistics. In all cases, correlations were non-significant both before and after correction for multiple hypothesis testing. The results also remained non-significant when repeated without adjusting for temporal autocorrelation (i.e. each time point in each patient counted as an independent data point).We sought to test whether statistics of BCR diversity were associated with clinical variables, such as viral load, time since seroconversion and CD4(d)To explore possible sources of variation in the three BCR statistics, we used ANOVAs to test whether each statistic was associated with patient identity, week of sampling and treatment group at each time point . All datWe also explored the effects of sub-sampling on each of the three BCR diversity statistics . As might be expected, the ‘proportion of reads in large clones' statistic was almost unaffected by sub-sampling. Although vertex Gini indices were slightly higher before sub-sampling, this inflation was relatively constant within patients. Mean clone size was substantially altered by changes in read depth, justifying our use of sub-sampling when comparing data from different patients tables .Figure (e)p = 0.01, 0.02 and 0.03, respectively). However, all comparisons between healthy controls and late-period HIV+ patients were non-significant.To enable direct comparisons between HIV+ patients and healthy controls, all datasets were sub-sampled to 5000 reads (see §2g). As before, values from HIV+ patients were grouped into two periods, early (weeks 4–24) and late (weeks 52–108) to avoid temporal autocorrelation. Comparisons of BCR sequence diversity are shown in 4.The results presented here demonstrate that BCR sequence diversity during HIV infection is highly dynamic and heterogeneous, both within and among patients. Individual clones fluctuate substantially in relative frequency, and at no time point did a single clone dominate the BCR sequence population in any patient. This suggests an actively evolving antibody response against HIV, likely due to the high turnover of HIV genetic diversity within each patient generating novel antigenic targets (e.g. ).+ count, suggesting a highly complex relationship between the adaptive immune system and viral dynamics. Previous studies have shown highly heterogeneous B-cell clonal responses to immune perturbations such as vaccines over a timescale of weeks [We observed significantly greater clonal structure in HIV+ patients than in uninfected controls during the first half of the study period, but not during the second half. This is consistent with a pronounced humoral response to viraemia during early infection. BCR diversity statistics during the late period were highly variable, suggesting that strong clonal structure was maintained in some patients but lost or significantly reduced in others . Howeverof weeks , so the There are several possible explanations for the heterogeneity we observed among HIV+ patients and through time. The first and simplest explanation is a lack of statistical power and sampling resolution. With only eight patients, the power of our study is almost certainly constrained by small sample size. However, a previous study of B-cell lymphoma patients that had a similar sample size and which used similar analytical techniques was able to establish significant associations between BCR clonality and clinical outcome in CLL patients, likely due to the exceptionally large B-cell clones generated by this cancer . AnotherThere are also biological explanations for absence of significant relationships between clinical variables and BCR diversity scores. While the BCR metrics used here were informative when applied to B-cell lymphoma patients, those patients often exhibited extreme clonality, such that one or a few B-cell clones comprised the majority of BCR reads . Howeveret al. [Our results are more successful in highlighting the potential usability and performance of different statistics of BCR diversity. Although the vertex Gini index proved informative in prior work , we founet al.  also expet al. ), althouFurther methodological challenges face the analysis of BCR repertoire data obtained through bulk sequencing. A formal, phylodynamic analysis of BCR sequence data is appealing because it would allow for model-based inference of parameters such as hypermutation rates and the relative growth rates of clonal populations. However, because BCR lineages are created through somatic V(D)J recombination, bulk BCR sequences do not coalesce to a single common ancestor and must be separated into distinct lineages before analysis can proceed. Further, probabilistic models of sequence evolution will be computationally very demanding when applied to BCR datasets, some of which—including those used here—contain millions of unique sequences per patient. If they are developed in future, phylodynamic methods may be best applied to individual B-cell lineages that have been isolated or identified by experimental, rather than computational, methods.


Tenofovir (TDF) and ritonavir-boosted lopinavir (LPV/r) were not introduced to China as second-line medications until 2009. The efficacy and safety of TDF/3TC/LPV/r based second-line regimen have not been evaluated in Chinese HIV patients who failed first-line regimens.This was a multicenter cohort study recruiting patients from Beijing, Shanghai, Guangdong, and Henan provinces between November 2008 and January 2010. Eighty HIV infected patients failing first-line regimens with serum creatinine lower than 1.5 times the upper limit of normal received TDF+ lamivudine (3TC)+ LPV/r were followed up for 120 weeks. CD4 cell count, viral load, and estimated glomerular filtration rate (eGFR) were monitored at each visit.2 at baseline to 95.6 ml/min/1.73m2 at week 24 and then recovered after week 96.At baseline, 31.2% and 48.8% of patients had moderate/high-level resistance to TDF and 3TC, respectively; while 2.5% of patients had only low-level resistance to LPV/r. During 120 weeks of follow-up, virological suppression rate reached over 70% (<40 copies/ml) and 90% (<400 copies/ml), and median CD4 cell count increased from 157 cells/μL at baseline to 307 cells/μL at week 120. Baseline drug-resistance mutations had no impact on the efficacy of second-line antiretroviral therapy. Median eGFR dropped from 104.7 ml/min/1.73mThis study for the first time demonstrated that TDF+ 3TC+ LPV/r was efficacious as second-line regimen with acceptable nephrotoxicity profiles in patients who failed zidovudine or stavudine based first-line regimens in China.NCT00872417ClinicalTrials.gov  After being introduced to China in 2002, combination antiretroviral therapy (cART) effectively reduced mortality among adult HIV-infected patients in China . At the TDF has been widely used in developed countries, though access to it is still limited in resource-limited areas, despite the fact that the World Health Organization (WHO) recommends TDF use and thatPreviously we reported a one-year observation of a prospective cohort consisting of treatment-experienced patients who received the second-line regimen. This study found that the TDF+LPV/r based regimen led to greater renal function decline compared with the control group, in which patients received AZT or d4T based regimens. However, this study did not evaluate the virological and immunological responses .To this end, we present the findings of a 120-week prospective study. We evaluated the efficacy and safety of second-line cART regimens in first-line cART-experienced adult HIV patients.Patients were recruited from Beijing, Shanghai, Guangdong, and Henan provinces between November 2008 and January 2010, as was described in our previous article . InclusiData collection was described in our previous report . The CD4Baseline drug resistance mutation was determined by using Pol sequence  and 2 [eGFR was calculated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula, which is more accurate in estimating eGFR compared with other methods, especially when patients are on cART and  GFR is >2 , 11.All patients in this study signed informed consent. This research was approved by the Institutional Review Board of Peking Union Medical College Hospital. It was in compliance with relevant local laws and the principles expressed in the Declaration of Helsinki.All analyses reflected an intention-to-treat (ITT) model or per-protocol (PP) model and were performed using Stata 11.0. PP analyses included patients who finished 120 weeks of follow-up and missed less than four visits. All continuous values were summarized as medians with interquartile ranges (IQRs). Continuous variables were assessed with the Mann-Whitney test (unpaired comparison) or Wilcoxon matched-pairs sign-rank test , and categorical variables were assessed with chi-square test or Fisher’s exact test. Statistical significance was accepted at p< 0.05 for two-sided tests.2, and only 4.9% of patients had proteinuria over 2+ in dipstick tests. Most patients were infected by HIV subtype B, and only seven (8.7%) patients were infected by non-B subtypes (six with CRF01_AE and one with CRF07_BC).As summarized in As to baseline drug resistance profiles, almost half of the patients had resistance to TDF or 3TC before the initiation of second-line regimen . Of noteWe also demonstrated transmitted drug resistance mutations in M184V/I, the major mutation accounting for resistance to 3TC, was found in 45% of patients. Of 25 (31.2%) patients with moderate-to-high levels of resistance to TDF, type 1 thymidine analog mutation (M41L and T215Y) was found in 21 patients. K65R, which was selected by d4T and ddI , was fouDuring 120 weeks of follow-up, around 70% of patients reached viral suppression to VL<40 copies/ml in ITT analysis. In addition, almost 90% of patients achieved VL<400 copies/ml in ITT analysis . PP analMedian CD4 cell count significantly increased from 157 cells/μL (IQR 69–272) at baseline to 307 cells/μL  at week 120 . Median 2 at baseline to 95.6 ml/min/1.73m2 at week 24. Median change in eGFR was -8.9 ml/min/1.73m2 at week 24 (IQR -15.7 to -2.1). It slowly increased but remained significantly lower than baseline level until week 96, when eGFR recovered to 108.6 ml/min/1.73m2, and remained at similar levels to those at baseline afterwards  achieved 92.3% . In factNotably, baseline drug-resistance profiles had no impact on virological responses . As mostIn terms of immunological response, patients in this cohort achieved CD4 cell count recovery similar to that in treatment-naïve patients receiving first-line therapy .2), we only observed fluctuation after initiation of TDF and recovery after week 96. This is consistent with our previous one-year observation and other studies in both Asian and western countries, in which moderate decrease in eGFR was noted during 48 weeks of follow-up [Although TDF has been reported to be associated with kidney injuries, in our cohort, eGFR slightly decreased at the beginning of this study and then slowly recovered to baseline levels. Interestingly, this slight decrease was only observed in patients with normal baseline eGFR levels; in patients with decreased baseline eGFR  The sample size is limited, and future studies with larger sample size are necessary to illustrate the efficacy of TDF/3TC/LPV/r based regimen in treatment-experienced patients. (2) Only patients with relatively good renal function were included in this study; therefore, it is difficult to evaluate the efficacy and safety profiles in patients with decreased eGFR. (3) Most patients in this cohort were infected via blood transmission, while in recent years, HIV infection via sexual transmission has become more common; therefore, the population characteristics might be deviated from the current situation.In conclusion, this is the first study in mainland China to demonstrate the efficacy of TDF/3TC/LPV/r based second-line therapy in patients who failed first-line cART. Since access to TDF and/or LPV/r is still restricted in resource-limited countries, and the TDF/3TC/LPV/r based regimen is a good candidate for second-line cART, this study may also be meaningful for patients who failed first-line cART in these countries.S1 Fig(TIF)Click here for additional data file.S2 Fig2.(A) Viral suppression rate (%) during 120-week follow-up. (B) CD4 cell count recovery during 120-week follow-up. (C) and (D) Estimated glomerular filtration rate (eGFR) during 120 weeks. Asterisks in (C) indicated significant differences compared with baseline level. Asterisks in (D) indicated significant differences between groups with baseline eGFR over and lower than 90 ml/min/1.73m(TIF)Click here for additional data file.S1 TableVL, viral load; N/P, no resistance or potential resistance; L, low-level resistance; M/H, moderate or high-level resistance; TDF, tenofovir; 3TC, lamivudine; LPV/r, ritonavir-boosted lopinavir. * Only two patients in our study harbored low-level resistance to LPV/r, one of whom lost to follow-up at week 84.(DOCX)Click here for additional data file.S2 TableVL, viral load; N/P, no resistance or potential resistance; L, low-level resistance; M/H, moderate or high-level resistance; TDF, tenofovir; 3TC, lamivudine; LPV/r, ritonavir-boosted lopinavir. * Only two patients in our study harbored low-level resistance to LPV/r, one of whom lost to follow-up at week 84.(DOCX)Click here for additional data file.


In resource-limited settings, routine monitoring of renal function during antiretroviral therapy (ART) has not been recommended. However, concerns for tenofovir disoproxil fumarate (TDF)-related nephrotoxicity persist with increased use.2 with >30% reduction from baseline using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation or the decision to stop TDF for reported TDF-nephrotoxicity. Predictors of S-Cr monitoring rates were assessed by Poisson regression and risk factors for developing renal dysfunction were assessed by Cox regression.We investigated serum creatinine (S-Cr) monitoring rates before and during ART and the incidence and prevalence of renal dysfunction after starting TDF by using data from a regional cohort of HIV-infected individuals in the Asia-Pacific. Time to renal dysfunction was defined as time from TDF initiation to the decline in estimated glomerular filtration rate (eGFR) to <60 ml/min/1.73m2 showed a protective effect .Among 2,425 patients who received TDF, S-Cr monitoring rates increased from 1.01 to 1.84 per person per year after starting TDF . Renal dysfunction on TDF occurred in 103 patients over 5,368 person-years of TDF use . Risk factors for developing renal dysfunction included older age . Having an eGFR prior to TDF (pre-TDF eGFR) of ≥60 ml/min/1.73mRenal dysfunction on commencing TDF use was not common, however, older age, lower baseline eGFR and PI-based ART were associated with higher risk of renal dysfunction during TDF use in adult HIV-infected individuals in the Asia-Pacific region. The widespread use of antiretroviral therapy (ART) has brought a marked decline in mortality and morbidity of HIV-infected individuals, but concerns have grown regarding the emergence of other chronic diseases associated with extended life expectancies coupled with the long-term effects of HIV disease and its treatment. One of the serious non-AIDS conditions which have increased mortality in the post-ART era is chronic kidney disease (CKD) , 2. AlthTDF is rapidly becoming one of the most widely used ARVs in the world –10. AlthOn the other hand, frequent laboratory monitoring of serum creatinine (S-Cr) may not be practical in resource-limited settings, and the World Health Organization (WHO) has yet to recommend routine S-Cr testing before and during ART . As TDF In this analysis, we evaluated the frequencies of S-Cr measurement before and during TDF use, and the incidence and factors of renal dysfunction while on TDF in a large prospective cohort in the Asia-Pacific region: the TREAT Asia HIV Observational Database (TAHOD) .Two analyses were conducted based on data collected in TAHOD . BrieflyIn this analysis, we included TAHOD patients who had ever received TDF as part of an ART regimen consisting of at least three ARVs. Factors associated with rates of S-Cr monitoring (S-Cr rates) were analyzed using a Poisson regression model with random effects on the patient to account for repeated measurements of S-Cr in individual patients. Analysis time began from ART initiation and was censored when TDF was discontinued for more than seven days, at death or the last follow-up date, whichever occurred first. Patients who re-started TDF after seven days did not re-enter the analysis risk set. Time-fixed covariates included in the model were age, weight, CD4 count, viral load (VL) and hepatitis B/C co-infection at ART initiation, mode of HIV exposure, initial ART regimen, prior AIDS defining illnesses (Centers for Disease Control and Prevention [CDC] Category C), pre-ART eGFR, and World Bank country income level . Time-upTrends in crude rates of S-Cr testing for each year on TDF were also explored using Poisson regression with follow-up time beginning from TDF initiation.2, or having ART stopped for reported renal toxicity. The eGFR value used to calculate the percentage decline was the value within six months prior to and closest to the date of TDF initiation. In order to include patients without pre-TDF S-Cr assessment, the first S-Cr after TDF initiation was used as the initial eGFR. The eGFR was calculated according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [Patient selection followed the same criteria as per analysis (i). TDF-related renal toxicity was defined as having eGFR reduction of at least 30% of the baseline value and <60 ml/min/1.73mequation . The anaequation , and codAll regression models were fitted using backward stepwise selection process. Variables significant in the univariate analysis at Wald’s test p <0.10 were chosen for inclusion in the multivariate model. Variables significant at p <0.05 were considered statistically significant in the final multivariate model. All data management and statistical analyses were performed using SAS software version 9.3  and STATA software version 12.1 .Ethics approval for the TAHOD study design, methods, and consent procedures, was granted by the University of New South Wales, Human Research Ethics Committee. Site-specific study governance was granted by site-relevant institutional review boards. Written informed consent was not sought in TAHOD unless required by a site’s local institutional review board. Informed consent was waived at some sites as information is collected via an anonymous case report form. All study procedures were developed in accordance with the revised Helsinki Declaration.The analysis included a total of 2,425 patients from Cambodia, China (including Hong Kong SAR), India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, Thailand and Vietnam. Patients initiated ART between 1996 and 2013 and contributed to 13,019 person years on ART and 5,368 years on TDF use. 2 compared to <60 ml/mim/1.73m2 ; p = 0.019).Crude rates of S-Cr monitoring for each year on TDF are shown in 2 with at least 30% reduction from the baseline. The remaining 14 patients were classified according to reported reasons for ARV discontinuation. Factors associated with time to renal dysfunction are shown in 2 showed a protective effect . ART adherence and S-Cr assessment in the previous 6-month interval were not associated with renal dysfunction.There were 649/2425 patients (27%) whose first S-Cr measurement used to estimate the baseline GFR occurred after TDF initiation. The median delay between TDF initiation and first S-Cr measurement in this subgroup of patients was 5 months (IQR: 1.4–13 months). The total number of patients with renal dysfunction during TDF use was 103/2425 (4.2%) and the crude toxicity rate was 1.75 per 100PYs. During a median time of follow-up of 2.07  and PI-based regimen are associated with higher risk of renal dysfunction in multivariate analysis, all of which were compatible with previous studies and the WHO recommendations for regular S-Cr monitoring [We found that older age (>50 years), lower pre-TDF eGFR Click here for additional data file.S2 TableIRB, institutional review board(XLSX)Click here for additional data file.


In this case report, we describe the emergence oftwo consecutive mutations (A594V and L595W) related to GCV resistance in a patientwith HCMV retinitis and long-term HIV progression after approximately 240 days of GCVuse. Following the diagnosis of retinitis, the introduction of GCV did not result inviral load reduction. The detected mutations appeared late in the treatment, and wepropose that other factors (high initial HCMV load, previous GCV exposure, lowCD4 UL97) (UL54)  was regarded as a major opportunisticvirus in patients with AIDS, and was associated with high morbidity and mortality . However) (UL54) . The eme) (UL54) .UL97 gene of HCMVfollowing ∼240 days of GCV use for treatment of retinitis. Based on the experienceacquired with this case, we propose that a combination of factors, including viral andhost characteristics, is crucial for managing HCMV infection in AIDS patients.Here, we report the management of a long-term HIV-progressor with simultaneous emergenceof two consecutive GCV-related mutations in the 5 leukocytes.Because of the elevated number of pp65-positive cells, the patient was treated withintravenous GCV (10 mg/kg daily) for 21 days. By the end of the treatment period, thepatient presented a CD4+ cell count of 65 cells/mm3 and an HIVload of 15,473 copies/mL.A 53-year-old female patient living with HIV infection for over 20 years (despite lowadherence to ART) was admitted several times to the AIDS Unit of the Hospital dasClínicas da Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, RibeirãoPreto, SP, Brazil. The first evidence of HCMV infection was registered in October 2009,when she presented with chronic diarrhea, fever, and anemia (hemoglobin=7.9 g/dL). AnHCMV pp65 antigenemia test demonstrated 90 infected cells/2×10+ cell countremained very low (19 cells/mm3), with an HIV load of 306,771 copies/mL.In July 2010, the patient developed pulmonary tuberculosis but was considered curedfollowing a 6-month treatment with 600 mg/day rifampcin, 300 mg/day isoniazid, 1.5 g/daypyrazinamide, and 1.2 mg/day ethambutol. In October of the same year, ART  was initiated. This treatmentdid not improve the patient's immunologic condition, as the CD45leukocytes, and the CD4+ cell count was 8 cells/mm3. Treatmentwith intravenous GCV (10 mg/kg daily) was initiated, and the oral ART regimen waschanged . The HCMV treatment continued for 25 daysbut no clinical resolution of the ocular infection was observed ; however, the HIV load was reduced to 292copies/mL, and the CD4+ cell count increased to 30 cells/mm3.Because of the observed failure of the HCMV treatment, GCV was withdrawn and empiricaltreatment with foscarnet was started . Interestingly, foscarnet treatment improved the patient's condition revealed a typical presentation of HCMV bilateral retinitis,characterized by focal hemorrhages, exudates in both eyes, and thinning, anddisorganization of the retinal layers .At thatkg daily .UL97 was amplified and sequenced eachmonth during the entire treatment period. Initially, no GCV resistance mutations wereobserved. However, after seven months of GCV treatment, the A594V mutation was detected.This mutation confers a GCV resistance ratio ranging from 4.5 , another mutation related to GCV resistance(L595W) was detected, with a resistance ratio of EC50=5.1 mM  and UL97R(5′-TCGCAGATGAGCAGCTTCTC-3′), andthe hydrolytic probe UL97P (5′-FAM-CACCCTGCTTTCCGAC-3′ MGB). Standard real-timeamplification conditions were applied . The reaction was performed in a 25 µLfinal volume including 250 nM of each primer and 100 nM of the probe. The detectionlimit of the reaction was 6.9 copies/reaction . ForUL97 genotyping, a 1193-bp fragment was amplified and sequenced. Thereaction was performed as a nested PCR and the initial larger fragment was amplifiedusing the outer primer pair 803F (5′-ACGACGTGCATTGCACCTGTTC-3′)/1996R (5′-ACCATGCTGCACGAATACGTCA-3′). The nested PCR wasperformed using two internal primer pairs: UL97rF (5′-AGTGTCGTGTATGCCACTTTGA-3′)/UL97rR (5′-TGCGAGCATTCGTGGTAGAA-3′) and 833F(5′-AGATCATCACCACGTCCATCCGC-3′)/1457 R (5′-TCGCTGAGGCTGTAATCGCACA-3′), which amplifiedfragments of 624 and 627 bp, respectively. The amplification protocol for the firstreaction included 10 initial cycles consisting of denaturation at 95°C/30s, annealing at55°/30s and elongation at 72°/2 min. This stage was followed by 20 cycles consisting ofdenaturation at 95°C/30s, annealing at 55°C/30s, and elongation at 72°C/2 min. Theelongation time was increased gradually by the addition of 20 s increment to each step.The second reaction consisted of initial denaturation at 95°C/5 min and 40 cycles ofdenaturation at 95°C/1 min, annealing at 58°C (primer pair 833F/1457R) or 60°C (primerpair UL97rF/UL97rR)/1 min and elongation at 72°/1 min 30 s. All the reactions wereperformed in 50 µL final volume.Each month , 6 mL of whole blood werecollected in sterile EDTA tubes . Viral (plasma) andcellular DNA (buffy coat) were extracted using a QIAamp Viral RNA mini kit , and a Gentra Puregene Purification Kit (QIAGEN), following the manufacturer'sinstructions. HCMV load was quantified in plasma and buffy coat using an in-houseoptimized TaqMan¯ real-time PCR assay, using the primers UL97F   and a Big Dye Terminator Sequencing kit  followingthe manufacturer's instructions. The obtained Germany) .+cell count. It is possible that the increase in CD4+ cell numbers was largelyresponsible for healing the retinal lesions, which also explains the continuously highHCMV load (slow immunologic reconstitution). At the time of writing, the patient wasreceiving tenofovir disoproxil fumarate, lamivudine, raltegravir, maraviroc, darunavir,and ritonavir because of HIV resistance to nucleoside, non-nucleoside reversetranscriptase, and protease inhibitors.Active HCMV infection in patients living with HIV shows generally stable initial viralloads, and its treatment with specific anti-HCMV drugs (mainly GCV), in association withstrong adherence to ART, generally leads to a reduction in HCMV plasma levels . HoweverUL97. The emergence of A594V wasobserved after ∼240 days of treatment, while L595W appeared one month later. This isconsistent with other studies examining HCMV resistance in patients with AIDS, whichdemonstrate an approximate period of 7 months for the appearance of resistance mutations revealed the emergence of two mutations related to GCVresistance: A594V and L595W in utations. Interes+ cell count was 8 CD4+cells/mm3. Therefore, we believe that the initial failure to treat theHCMV infection in this patient was caused by a combination of several factors, includinga high HCMV load and profound immunosuppression. A low serum concentration of both drugsas a possible risk factor for the emergence of HCMV resistance or failure of HCMVtreatment is unlikely in this case, as all of the antivirals (GCV and foscarnet) wereadministered in full treatment doses and not as a preemptive therapy.Surprisingly, the initial GCV treatment did not reduce the viral load, althoughresistance mutations were not detected. On the one hand, higher viral load at the timeof GCV initiation could have negatively influenced the treatment outcome ,19. Att50). It was described in 1997 by Smithet al. , is found in 90% ofHCMV-resistance cases  and has specificlaboratory requirements. The software used in the current study gives an approximateestimation of the GCV resistance ratio, and can distinguish between viral polymorphismsand resistance mutations. Therefore, a relative phenotypic image could be deduced from the obtained sequence data in just a few hours, which can haveimportant consequences for the management of an HIV-infected patient with opportunisticHCMV infection.Although consecutive resistance mutations appeared after ∼240 days of GCV treatment, webelieve that the success of the anti-HCMV treatment also depends on treatment of the HIVinfection and tight monitoring of the reconstitution of the patient's cellular immuneresponse. The mutations in this case had secondary role in treatment outcome andconferred only low-level GCV resistance. We believe that discussion of this clinicalcase will add to our understanding of the kinetics of the emergence of GCV resistancemutations in patients with AIDS and HCMV-related diseases.