Together, these tools will aid HIV researchers in the evaluating new potentially-curative strategies that target the latent reservoir.Monitoring the efficacy of novel reservoir-reducing treatments for HIV is challenging. The limited ability to sample and quantify latent infection means that supervised antiretroviral therapy (ART) interruption studies are generally required. Here we introduce a set of mathematical and statistical modeling tools to aid in the design and interpretation of ART-interruption trials. We show how the likely size of the remaining reservoir can be updated in real-time as patients continue off treatment, by combining the output of laboratory assays with insights from models of reservoir dynamics and rebound. We design an optimal schedule for viral load sampling during interruption, whereby the frequency of follow-up can be decreased as patients continue off ART without rebound. While this scheme can minimize costs when the chance of rebound between visits is low, we find that the reservoir will be almost completely reseeded before rebound is detected unless sampling occurs at least every two weeks and the most sensitive viral load assays are used. We use simulated data to predict the clinical trial size needed to estimate treatment effects in the face of highly variable patient outcomes and imperfect reservoir assays. Our findings suggest that large numbers of patients—between 40 and 150—will be necessary to reliably estimate the reservoir-reducing potential of a new therapy and to compare this across interventions. As an example, we apply these methods to the two “Boston patients”, recipients of allogeneic hematopoietic stem cell transplants who experienced large reductions in latent infection and underwent ART-interruption. We argue that the timing of viral rebound was not particularly surprising given the information available before treatment cessation. Additionally, we show how other clinical data can be used to estimate the relative contribution that remaining HIV New therapies are being developed to permanently cure HIV infection. Many aim to reduce the pool of latent virus that persists despite years of treatment with antiretroviral drugs. Because latent virus is so difficult to sample and measure, often the only way to know if these new therapies have worked is to interrupt all treatment, and wait indefinitely to see if the infection rebounds. In this study we use a set of mathematical and statistical models to suggest optimal ways to design and interpret these treatment interruption trials. For various scenarios, we predict how long patients should be followed to be confident that they are cured, how frequent viral load sampling should occur, and how large clinical trials will need to be to estimate and compare drug efficacy. We demonstrate how to infer a range for number of remaining latent cells based on the timing of rebound after a long remission. As a case study, we apply these results to data from two HIV-positive patients who underwent bone marrow transplants and remained off treatment for months before suddenly rebounding. These findings can help inform the testing of new potentially-curative HIV therapies. Note that observing rebound, as opposed to the absence of rebound, is predicted to lead to lower estimates for LR-reduction (higher estimates for size) and narrows the confidence interval on these estimates. However, all these results illustrate how the high variability between patient outcomes makes it difficult to estimate precise estimates of reservoir size reduction.Using this approach, 3 months without rebound implies an LR reduction of 500-fold , while rebound Intuition suggests that the longer a patient has been off treatment without rebound, the more likely it is that they will never experience rebound, thereby achieving a cure. As above, we can formalize this intuition using a Bayesian approach. Since the model gives a probability of cure for each possible reservoir size , we simpIf we consider a population of patients, then one major unknown is how many patients will be required in a given clinical trial to reliably estimate the reservoir reduction efficacy (i.e. to “power” the study). We can estimate this number using simulated patient data , and perhaps in in as little as five days in those without HIV-specific immunity, as seen in the example of the Boston patients  and 7  infected cells remaining.Pre-transplant chemotherapy and post-transplant graft-vs-host-disease , 30, 31  virions . Accordi virions . Moreovein vitro [in vivo [Both patients received transplants from HIV-negative donors, and so any possible contribution to the latent reservoir from donor cells must have been due to new latent infections occurring during the transplant procedure. Both patients also remained on cART during the entire engraftment procedure, which was thought to prevent any new infection. Several independent lines of evidence suggest that viral replication halts during optimal adherence to cART: treatment reduces viral replication several orders of magnitude in vitro , 34, evo[in vivo , 36, and[in vivo , 38. Yet[in vivo , or the [in vivo , may com[in vivo , 41. As Despite the considerable uncertainty in these values and the estimated reservoir reductions, they do constrain the possible causes of viral rebound. Specifically, in Patient A, it is difficult to explain the observed rebound time without positing that some donor cells were newly infected. The 95% credible interval for the posterior estimate of the LR size estimated from the observed time of rebound suggests there were many more cells in the reservoir than were likely to remain from the recipients pre-transplant infection. However, if the efficiency of donor engraftment in tissues was lower than that in the peripheral blood, then enough latently infected host cells could have remained to explain the rebound time. In Patient B, on the other hand, the presence of new infection is not necessary to explain the observed rebound, as the upper bound on the number of residual host cells is consistent with the lower bound for the reservoir size estimated from the time of rebound.r ≈ 1.24/day. This is higher than any of the values observed in non-transplant interruption studies  [r is at least 0.82/day. Overall these values suggest that viral replication is accelerated, or death of infected cells is inhibited, in HSCT patients due to loss of HIV-specific immune responses that may occur during the long period in which viral antigen is largely absent. In fact, these rates of viral increase are comparable to those observed during acute infection, prior to establishment of HIV-specific immune responses [The dynamics of viral load following rebound can be used to estimate the rate of viral replication, to compare these two patients to other treatment interruption cohorts, and to examine potential reservoir re-seeding. For Patient A, there are two consecutive viral load values above the detection limit, before peak viremia and set-point are reached (900 c/ml at Day 84 and 130 000 c/ml at Day 88). From these, we estimate that the rate of exponential increase in viral load is 0.1–0.9) , 18, 42.esponses .One of the predictions of the model of rebound dynamics is that if rebound occurs after a long delay, it is likely to be caused by a single cell that has reactivated from the latent reservoir. Significant delays in the rebound time only occur when the waiting time between latent cells reactivating is long, and since we assume that cells reactivate independently, the chance that more than one cell would start producing virus at nearly the same time is very low . If this5 c/ml, and suboptimal adherence led to even higher values before suppression was eventually achieved. In contrast, for Patient B the first positive viral load value was already likely near the pretreatment peak, at 1.9 × 106 c/ml, so even though treatment was initiated promptly leading to rapid viral decline, near-complete reservoir reseeding may have been inevitable.At the time of rebound, both patients had viral load measurements taken every 2 weeks with a detection limit of 20 RNA copies/ml. According to the model behind One of the proposed strategies to cure HIV infection is to reduce or eliminate populations of latent virus that persist despite long-term antiretroviral therapy. The goal of these strategies is to allow individuals to stop cART without experiencing rebound of viremia. However, case studies such as the “Mississippi baby”  and the One of the most useful features of our approach is that it offers a formal way to combine information from pre-interruption assays of the latent reservoir size, even if they are all negative, with observations during treatment interruption. Our analyses predict that even if no infection is detected among approximately 100 million cells assayed, 4 years of follow-up are needed before there is a 50% chance of cure, and over 10 years to be 90% sure. The higher cell samples that could be obtained with leukophoresis (≈ 1 billion) only decrease these follow-up times by around a year. An implicit assumption of this approach is that there is a dynamic equilibrium between latently infected cells in the tissues and those circulating in the peripheral blood. If a reduction observed in the blood does not correspond to the reduction in the tissues, these estimates will be biased. Consistent patient monitoring during treatment interruption is necessary, and how the frequency of sampling should be scaled-back as time progresses and cure becomes more likely is not intuitive. We used the model predictions to design a sampling schedule so that the chance of patient rebound between samples remained at a constant low level. It suggests times after which sampling frequency could be reduced to weekly (5 months), monthly (1.5 years), quarterly (5 years), and annually (10 years). However, even when the risk of rebound between samples is low, if it does occur, the risk of reaching high-level viremia and completely reseeding the reservoir before the infection is detected may be high.Even when the post-intervention reservoir size is informed by negative assay results and a precise measurement of viral rebound time, there is considerable uncertainty in its size. This uncertainty in residual HIV reservoir size follows from the stochastic nature of viral rebound from small latent reservoirs. This stochastic process produces large variability in viral rebound times, even for patients starting with identical reservoir sizes . As a reMany of our estimates  be the fraction of patients who have not yet rebounded at a time t after treatment is stopped. Since we do not know the true function S(t ∣ q), we rely on the predictions calculated from the model. For any fixed q value, the function S(t ∣ q) describes “survival curves” that can be calculated from the model (If he model . The detτ days after ART-interruption (rebound time tr is greater than τ). We define P(q) to be the probability distribution for our existing knowledge about the likelihood of a given q value being the true value (the prior). This function can be estimated using data from experimental assays, as detailed in the next section. The function S(τ ∣ q) forms the likelihood of the Bayesian approach, which gives the probability of the data (τ) given a particular model (the unknown reduction-efficacy parameter q). Then, the posterior probability distribution for the reduction efficacy q becomes:We first approach the question of how to estimate the amount by which the reservoir has been reduced, when we cannot measure reservoir size directly from assays but have observed delayed viral rebound. We consider a patient who has still not experienced viral rebound after at a time τ, then the formula is slightly modified. The likelihood function for the time of rebound is given by the slope of the survival curves, ∂S(τ ∣ q)/∂t, so the posterior probability for the reduction efficacy q becomesAlternatively, if a patient rebounded q when a patient has survived without rebound for a time τ, for a given prior distribution. We combine this with the fact that the probability of cure is given by the limiting value of the survival curve as time increases to infinity, pcure(q) = S(∞ ∣ q), and that the conditional probability of cure, given only those individuals who have not yet rebounded at time τ, is pcure(q ∣ tr > τ) = S(∞ ∣ q)/S(τ ∣ q). Then, we can derive the probability of a cure, given the absence of rebound until time τ, asWe next turn to determining the probability that a patient is cured , as a function of the current time they have been off cART without rebounding. We can also estimate how many patients would be needed in a trial to narrow down the estimated reservoir-reduction to something close to its actual value. We say that this is the trial size required to adequately “power” the study, where we imagine that the main goal of the study is to determine how much some novel intervention reduces the reservoir, and that this can only be done by observing rebound times.n patients in a trial and a set of rebound times {τi} = {τ1, τ2…τn} are observed, then the posterior distribution for the reduction efficacy q is given by:If there are q is high enough so that after some time τmax, m patients still have not rebounded, then the estimated reduction efficacy becomesHere we assume a uniform prior, as a worst case scenario where no other information on reservoir size is available. If n can be calculated for particular requirements on the posterior estimate, by repeatedly simulating patient data and using it to construct Ppost. For example, we defined a study as adequately powered if 95% of trials of this size would result in 95% (centered) credible intervals for q that that contain the true value and are less than 1 log wide. We determined n by doing a binary search though trial sizes from the list {5, 10, 15, 20, 25, 20, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 500, 600, 700, 800, 900, 1000}. Here we assume τmax = 10 years.The required number of patients We additionally use these methods to estimate the optimal frequency of sampling subjects in a cART-interruption trial. One method to optimally choose sampling time points is to determine intervals between which the chance of a participant experiencing viral rebound is equal.q is known, then the probability that someone who has survived until timepoint ti rebounds before time ti+1 isIf the reduction efficacy q is unknown, we must again weight this probability with the posterior likelihood of q, given that the patient has already survived without rebound until time tiF(t) is defined as in Preb to the pre-defined “tolerance” δ—the fraction of suppressed trial participants expected to rebound between each sampling timepoint. Using t0 = 0 and F(t0) = 1, we can iteratively solve for tn using the implicit equation F(tn) = (1 − δ)n.However, in the general case that S(t ∣ q), which means we cannot analytically calculate any of the integrals described above. Instead we use the simulated model output to numerically construct S(t ∣ q), using 10,000 patients for each q value and q values between 10−6 and 1 in increments of 0.05 logs. We then calculated the integrals as Reimann sums.We do not have analytic functions for the model output q) as a function of rebound time can incorporate any prior knowledge we may have about the likely reservoir size (P(q)). This prior distribution can be constructed based on the results of virologic assays that were used to measure the size of the reservoir before cART was interrupted.The Bayesian approach to estimate the post-treatment reservoir size (P(q), we imagine an assay was performed that measured the frequency of latently infected cells in a sample . We assume that cells used in the assay were randomly sampled from a much larger pool in a patient’s body. We can then construct the likelihood distribution for the true frequency of latently infected cells, based on the actual number of infected cells observed in the sample. We define the true frequency of latently infected cells to be θq, where θ is the frequency before reservoir-reduction, and q is the fractional reduction. If C cells are sampled and zero infected cells are observed, then the likelihood for q goes as P(q) ∝ eθCq−. . This distribution shows that taking only negative assay results into account, any q value is possible, but q = 0 (no remaining reservoir) is mostly likely and higher q values (larger reservoir sizes) are less likely, although as q becomes very small, the distribution flattens out.Briefly, to construct http://silicianolab.johnshopkins.edu.More details of this calculation can be found in separate manuscript . Simple C = 108 and θ = 10−6 (i.e. the reservoir was sampled at a level of 100 times the pre-reduction frequency of latency), then if no infected cells are detected, the resulting prior distribution is shown in q = 0 (Q → ∞).Using Other priors may also be possible, depending on the nature of the assay. The most uninformative prior would be to assume that we have no information on reservoir size before cART interruption, and so every reservoir size is equally likely. We think this is unrealistic, since an interruption trial would likely not be conducted unless the reservoir was undetectable or at least very low by standard assays.θq < 1/C, or q < 1/(Cθ). For the scenario with C = 108 and θ = 10−6 used above, this would lead to the conclusion that there was at least a 2-log reduction in the reservoir size. However, this “detection limit” actually represents a very weak confidence interval, because in repeat sampling, it is expected that 63% of all draws will from a sample with an infected frequency at this “limit” will give at least one infected cell.Note that it is common practice in clinical studies to interpret the results of the types of assay described above as a hard cut-off for the reservoir size. It is often said that if no infected cells are detected, then the frequency is less than the inverse of the sample size, i.e. S1 Text(PDF)Click here for additional data file.S2 Text(PDF)Click here for additional data file.S3 Text(PDF)Click here for additional data file.


In 2013, the World Health Organization (WHO) recommended scaling up of routine viral load (VL) monitoring for patients on antiretroviral therapy (ART) in resource-limited settings [Data derive from a cross-sectional study providing multi-disease screening as well as VL testing to adult patients (≥16 years old) on first-line ART ≥6 months . VF was Data from 1,488 patients were analyzed. Overall VF-prevalence was 6.9% (95% CI 5.7–8.3). In univariate analysis, the following were associated with VF: age <30, lower wealth-quintile, no primary education, history of treatment interruption, nevirapine-base, zidovudine-backbone, history of drug substitution, travel-time to clinic ≥2 hours, disclosure of HIV status to <5 persons, clinical failure, presence of PPE and immunological failure. In multivariate analysis, 6 out of the above 12 variables were independent predictors: age <30 years , history of treatment interruption , PPE , immunological failure , history of drug substitution , disclosure of HIV status to <5 persons .In this cohort in rural Lesotho, several socio-demographic and clinical predictors were associated with VF. Particularly age <30 years, history of treatment interruption, PPE and immunological failure were strongly associated with VF. These patients may be prioritized for targeted VL-testing.


PRINCE-1 is an ongoing prospective, international, multicentre, nonrandomized, two-stage clinical trial assessing safety and efficacy of once-daily atazanavir (ATV) powder boosted with ritonavir (RTV) liquid plus optimized dual nucleoside reverse-transcriptase inhibitor (NRTI) background therapy in antiretroviral (ARV)-naïve and -experienced children with HIV-1 infection aged ≥3 months to <6 years.Children with HIV-1 infection without prior ATV exposure and with a screening HIV-1 RNA ≥1000 copies/mL were enrolled. The dosing of ATV powder, boosted with 80 mg RTV liquid, was based on three baseline weight bands .3, and the median change from baseline in CD4 percent was +7.5%.Of the 56 treated patients, 46 completed 48 weeks of therapy, 67.9% were from Africa and 60.7% were ART-naïve. Median ages at baseline were 6, 35 and 55 months, and proportions with HIV-1 RNA >100,000 were 85.7, 52.6 and 25% in the three baseline weight bands, respectively. No unexpected safety events occurred and no deaths were reported. Over 48 weeks, upper respiratory tract infections, diarrhoea, vomiting and Grade 3 to 4 hyperbilirubinaemia occurred in 35.7, 35.7, 28.6, and 9.4% of patients, respectively; five patients (8.9%) discontinued due to adverse events (AEs); and 11 patients (19.6%) experienced serious adverse events. At Week 48, using a modified intent-to-treat analysis (two patients were excluded because they switched to ATV capsules before Week 48), 61.1 and 74.1% of patients overall had an HIV-1 RNA level <50 copies/mL and <400 copies/mL, respectively. Virologic suppression rates increased across the lowest to highest baseline weight bands  but did not differ meaningfully between ARV-naïve and -experienced patients. Overall, the median change from baseline in CD4 cell count was +363 cells/mmATV powder boosted with RTV liquid once daily plus optimized dual NRTI background therapy was effective and well tolerated in this ART-naïve or -experienced paediatric population aged ≥3 months to <6 years. No unexpected safety findings compared with those from previous ATV paediatric and adult studies were identified. Of the estimated 35.3 million people living with HIV-1 infection in 2012, 3.3 million were children aged <15 years  and chilWorld Health Organization (WHO) treatment guidelines for HIV-1-infected infants and children recommend a cART regimen containing lopinavir (LPV) boosted with ritonavir (RTV) as a first-line treatment option for those aged <3 years . SimilarOnly a few ARV drugs are available as palatable formulations  suitable for administration to children. PIs currently available as liquid formulations/reconstituted oral suspensions for the treatment of paediatric patients in the United States include fosamprenavir (aged 2 to 18 years) , coformuet al. conducted model-based simulations to identify weight-based ATV doses that were predicted to produce ATV exposures in children similar to those achieved in adults receiving the recommended adult ATV/r dose of 300/100 mg  and pulmonary tuberculosis [n=1] considered unrelated to study therapy by the investigator; increased transaminases [n=1] and lymphadenitis [n=1] considered as related events) and 1 in the 10 to <15 kg group . The patient discontinuing ATV due to increased transaminases had a history of nevirapine-induced hepatitis and was receiving concomitant hydroxyzine, an agent known to cause liver dysfunction [Five patients (8.9%) had AEs leading to discontinuation of study therapy: four in the 5 to <10 kg group  had at least one AE, with the most common being upper respiratory tract infection, diarrhoea and vomiting . The mosThree patients (5.4%) had cardiac disorders. Two of these events were considered related to the study therapy by the investigator: ECG QT prolongation in one patient in the 10 to <15 kg group (described above in the section on AEs leading to discontinuation) and first-degree atrioventricular block in one patient in the 15 to <25 kg group. Eight patients (14.3%) had rash events, none of which were considered related to the study therapy by the investigator. One patient (1.8%) in the 5 to <10 kg group had pulmonary tuberculosis, a CDC Class C AIDS event , which wThe most common Grade 3 to 4 laboratory abnormality was elevated total serum amylase (26.4%); however, all of these patients had normal fractionated pancreatic amylase levels. Grade 3 to 4 elevations in total bilirubin were present in 5/53 (9.4%) of patients and appeared not to systematically vary by baseline weight band. Grade 3 to 4 elevations in serum transaminases were present in 7/53 (13.2%) of patients, but no instance of drug-induced liver injury was reported. Other Grade 3 to 4 laboratory abnormalities are summarized in Using a modified ITT approach based on the Week 48 ATV powder cohort (patients who did not switch to the ATV capsule at or before Week 48), 61.1% of patients had HIV-1 RNA levels of <50 copies/mL and 74.1% had HIV-1 RNA levels of <400 copies/mL. Virologic suppression rates increased progressively across the lowest to highest baseline weight bands . VirologVirologic suppression rates showed no clear numeric differences between ARV-naïve and -experienced patients .Virologic suppression rates improved progressively over time for all patients a, regard10 copies/mL .At Week 48, the overall mean change from baseline in HIV-1 RNA levels was −2.66 logThe acceptability of ATV powder was higher than that for RTV liquid over the first 24 weeks. Drug acceptability tended to improve over time for both treatments b but remImmunologic recovery was observed across all baseline weight bands, with a trend to greater changes from baseline in CD4 percent in the higher versus the lower baseline weight bands . DespiteBy Week 48, 14 of 46 (30.4%) patients met the criteria for virologic failure. Of these 14 patients, six (42.9%) were ARV-experienced and eight (57.1%) were ARV-naïve. Nine patients had paired genotypic resistance data (baseline and on-treatment data) and six had paired phenotypic data. None of the patients acquired phenotypic resistance to ATV, ATV/RTV or any NRTI or NNRTI. One patient developed phenotypic resistance to saquinavir. None of the patients developed any major PI substitution to ATV or ATV/RTV.ATV powder boosted with liquid RTV in combination with optimized NRTI background therapy in infants and children aged three months to six years with HIV-1 infection was generally safe and well tolerated, with a safety profile similar to that reported using ATV capsules in adult studies –30 and iVirologic suppression  and immunologic response  at Week 48 was observed across all three baseline weight bands, regardless of prior ARV treatment experience. Results for the 10 to <15 kg and 15 to <25 kg baseline weight bands were consistent with results obtained in the PACTG 1020A trial using ATV capsules boosted with RTV in ARV-naïve patients aged 6 to <18 years with HIV-1 infection, for whom HIV-1 RNA levels of <50 or <400 copies/mL at Week 48 were achieved by 81 and 88% of patients, respectively [Virologic suppression rate was lower in the 5 to <10 kg baseline weight band, which most likely resulted from the higher proportion of patients with a baseline plasma HIV-1 RNA level >100,000 seen in this group . A high plasma HIV-1 RNA level is commonly seen in infancy (the median age of patients in the 5 to <10 kg baseline weight band was six months), which, together with immunological immaturity, makes virologic suppression in infants more difficult to achieve and results in longer times to reach undetectable levels ,33.Potential alternative explanations for the lower virologic suppression rate in the 5 to <10 kg baseline weight band, such as the effect of prior ARV exposure, emergent resistance, differences in discontinuation rate or differences in acceptability/palatability were not supported by the available evidence. We found no difference in virologic suppression between ARV-naïve and -experienced patients. None of the patients who underwent resistance testing for virologic failure or discontinuation from the study acquired phenotypic resistance to ATV, ATV/RTV or any NRTI or NNRTI, and no major mutations associated with ATV resistance were reported. Discontinuation rates were not numerically different between the 5 to <10 kg and 10 to <15 kg baseline weight bands and, when analyzed using observed values, virologic suppression rates in the 5 to <10 kg baseline weight band remained numerically lower than those in the other baseline weight bands. Patients in the lowest baseline weight band had neither more trouble completing their doses, nor a greater dislike of the taste of study treatments compared with patients in the higher baseline weight bands. Whether pharmacokinetic differences could explain the lower virological suppression rate in the 5 to <10 kg baseline weight, especially because drug metabolism is known to differ substantially in infancy , will be10 copies/mL below the baseline level at 12 to 24 weeks after treatment initiation or a confirmed plasma HIV-1 RNA level of >400 copies/mL at 24 weeks) or treatment discontinuation occurred in 19.3% of patients randomized to LPV/r [Although making comparisons with paediatric clinical studies of other PIs is difficult owing to differences in trial design and endpoint definitions, the results of the current study are consistent with those from studies evaluating LPV/r and other PIs in paediatric populations. In the original study in children aged 6 months to 12 years with HIV-1 infection evaluating LPV/r, either added to stavudine and lamivudine (ARV-naïve) or nevirapine plus one or two NRTIs (ARV-experienced), overall, 79% had HIV-1 RNA levels <400 copies/mL at Week 48 using an ITT analysis. Similarly, in the PENPACT-1 trial, rates of virologic suppression with PIs (mainly LPV/r or nelfinavir) plus two NRTIs at Week 24 were 73% using an ITT analysis . The morto LPV/r . In patito LPV/r . Recent to LPV/r , 65% in to LPV/r  and 74% to LPV/r . Data onThe acceptability of ATV powder boosted with RTV liquid was high among caregivers of the children in this study, with acceptability over 48 weeks ranging from 71.7 to 91.1% with ATV powder and from 62.3 to 86.7% with RTV liquid. The proportion of children reported by their caregivers as disliking the taste of ATV powder boosted with RTV liquid was low, with up to 12.5% disliking the taste of ATV powder over 48 weeks and up to 27.5% disliking the taste of RTV liquid over 48 weeks. These results compare favourably with the recently evaluated minitab sprinkle formulation of LPV/r, for which 38 to 53% of children <4 years of age were reported by their caregivers to have disliked the taste of the sprinkles .Taken together, these findings on efficacy, safety and acceptability/palatability indicate that a regimen including ATV powder boosted with RTV liquid represents a new treatment option for infants and children aged ≥3 months to <6 years with HIV-1 infection. Indeed, data for this study have contributed to the recent FDA approval of ATV powder formulation for use for use in paediatric patients with HIV-1 infection ≥3 months of age and weighing ≥10 kg to <25 kg .This study has limitations. The study enrolled a relatively small number of patients with HIV-1 infection, was non-randomized, and no statistical comparisons between subgroups were performed (by baseline weight band or ARV treatment experience). Numerically, virologic suppression rates were lower in patients in the lowest baseline weight band compared with the higher weight bands, and immunological recovery was less evident in ARV-experienced patients compared with ARV-naïve patients. However, the study design and small sample size did not allow these observations to be statistically verified. Over 48 weeks, up to 27.5% of patients were reported by their caregivers to have disliked the taste of RTV liquid. This percentage is lower than in a previous study assessing ARV adherence and palatability in children, of whom 50% disliked the taste of RTV liquid . It shouIn conclusion, no new safety findings were identified that had not been previously reported in other ATV paediatric or adult studies. ATV powder boosted with liquid RTV in combination with optimized NRTI background therapy achieved adequate virologic suppression and immunologic response, was highly acceptable to caregivers, and was generally safe and well tolerated by infants and children aged three months to six years, regardless of prior ARV treatment experience or baseline weight band. No major PI substitutions associated with ATV resistance were reported. As recognized by the recent FDA approval, ATV powder is an available treatment option for use in paediatric patients with HIV-1 infection ≥3 months of age and weighing ≥10 kg to <25 kg.


Human albumin is the most abundant protein in sera and a valuable biomarker in monitoring a variety of diseases. In this study we investigated the relationship between serum albumin concentrations and effects of initiation of highly active antiretroviral therapy (HAART). Serum albumin concentrations amongst 70 HIV-infected patients from diverse ethnicities were analyzed, in the absence of any other confounding comorbidities, over a period of 8 years in South East London, United Kingdom. Serum albumin data was collected, on average, every 4–6 weeks during routine visits. Serum albumin was measured prior to starting HAART, and measured at the first clinic visit after commencing HAART. These were compared to a control group of untreated individuals. Based on our analyses we conclude that serum albumin concentrations increase significantly after the initiation of therapy. Chauhan et al. 2011 studied HIV-positive Indian patients and found that serum albumin levels increased after the commencement of HAART.Our study investigated serum albumin concentrations in a cohort of HIV-positive patients in South East London, United Kingdom. We investigated whether the initiation of HAART impacts upon serum albumin concentrations, compared to a control group of untreated HIV-positive individuals.11 at King's College London were investigated. Thirty-nine of these patients commenced HAART, and baseline serum albumin levels immediately prior to treatment and the first measurement after treatment were used, generally within 4–6 weeks. These were analyzed against the control group of 31 untreated patients, where the baseline serum albumin level was the earliest recorded measurement. The median measurement from multiple clinic visits was taken in the control group to compare to post-HAART serum albumin in the treated group. Of the 70 patients, none were known to be hepatitis B virus positive. Data between July 2004 and June 2013 was included, and on average, serum albumin concentrations were measured every 4–6 weeks for each patient. Normal serum albumin concentrations were considered to be between 35 and 50g/L.12Seventy HIV-1 positive patients recruited to the Infectious Diseases BioBank (IDB)Baseline CD4 T-cell count data was measured in the treated cohort immediately prior to treatment, and measured again after treatment, generally within 4–6 weeks. These were analyzed against the untreated control group, where the baseline CD4 T-cell count was the earliest recorded measurement. The median measurement from multiple clinic visits was taken in the control group to compare to post-HAART CD4 T-cell count in the treated group. Serum albumin concentrations and CD4 T-cell counts were measured by GSTS Pathology. Patients infected with a variety of HIV clade strains were represented in both cohorts.Ethical approval for all aspects of this study was obtained through the King's College London Infectious Disease BioBank Local Research Ethics Committee . Statistical testing was done by comparing the mean change from baseline level of serum albumin/CD4 T-cell count to post-HAART or median measurement between treatment groups, using a t test with change scores, and statistical analyses were performed using Stata 13.1.Of the 70 patients, the majority were men (85.7%) and white (67.1%), followed by black Africans (14.3%) and other black (10%). The mean age at diagnosis was 33.7 (±8.4) years. Patient characteristics are listed in There was sufficient data to compare initiation of HAART for 39 patients. The majority of patients were male (92.3%) and white (76.9%). The mean age at diagnosis was 35.5 (±9.3) years, and the mean age at commencement of HAART in the 39 patients was 38.6 (±9.6) years.p=0.0166) (3 (95% CI −83.01 to 87.24), compared to pre- and post-treatment change in the treated group of 191.16 cells/mm3 (95% CI 126.57 to 255.75). Strong evidence suggests that this change between the two time points differed between the treated and untreated groups (p=0.0005) , compared with pre- and post-treatment change of 2.15 g/L (95% CI 1.06 to 3.25) in the treated group. The mean change was 1.91g/L (95% CI 0.36 to 3.47) in the treated group compared with the untreated group. There was strong evidence that this change between the two time points differed between the treated and untreated groups (=0.0166) . The mea=0.0005) .9 The difference in baseline hypoalbuminaemia between our cohort and the Indian cohort may be due to dietary, geographic, and/or ethnic group differences. Additionally, there is little information on the HIV-1 clade in the other comparable studies to be able to investigate any potential correlation.Our data shows that serum albumin levels increase significantly after commencement of HAART, compared with a control cohort of untreated individuals. In comparison with the closest equivalent study, our patients were more ethnically diverse and presented with no hypoalbuminaemia at the baseline visit.13 Our data shows a significant increase in CD4 T-cell count after the initiation of HAART. In patients coinfected with other viruses, the beneficial effect of HAART on the immune system can result in lowering of viral loads in chronic infections such as hepatitis B14, C15, and G16. Despite the number of studies looking into coinfected individuals, most patients are likely to be HIV positive and hepatitis B/C negative, and the effect of HAART on liver function in monoinfected patients is of greatest clinical relevance.HAART has a profound impact on HIV, lowering viral loads and allowing CD4 T-cells to increase in number.6 and post-HAART7 eras supporting their relevance in HIV medicine. Mehta et al. (2006) reported that hypoalbuminaemia after HIV seroconversion was associated with faster disease progression, and a likely consequence of HIV infection.17 Additionally, in resource-poor settings, the potential use of serum albumin levels as an alternative to the more costly and specialized CD4 T-cell counts and viral load assays has been recognized.19 However, serum albumin levels are unlikely to respond as acutely as CD4 T-cell count and viral load assays, and where available, these should always be used as first line assays.Serum albumin levels are a good prognostic marker in HIV infection, with studies from both the pre-HAARTWe hypothesize that in our control group of untreated individuals, the stress of their HIV infection may affect the rate of production for some proteins such as albumin, or increase their rate of loss. The observed differences in albumin levels may be due to multiple factors. Some of the possible explanations for the change in serum albumin levels include: (1) the fact that it is a “negative” acute phase protein and levels fall during inflammation, (2) excessive excretion via the kidney, (3) loss to the bowel, and (4) liver disease. The latter is unlikely as we excluded patients with known hepatitis B or C virus infections. Integrity of the bowel wall is damaged during the acute phase of HIV infection resulting in bacterial translocation into the plasma, and HIV infection causes inflammation of the bowel. The paradox in both of these cases is that such damage is believed to occur early during the disease process, yet we noted that albumin concentrations were lowest amongs those with chronic disease.20 Although an increase of 2.15g/L may seem clinically small, this rise in serum albumin level is a likely indicator of the overall benefit of HAART in mitigating the systemic effects of HIV infection, as described above. In conclusion, commencement of HAART in HIV infected individuals exhibits benefits to the circulating serum albumin levels.The presented data supports an observed benefit of HAART on circulating serum albumin levels and CD4 T-cell count. The relationship between HAART and the liver, the site of albumin synthesis, is a balance of the beneficiary effect of immune system reconstitution versus the potential long-term toxic nature of the antiviral drugs that constitute HAART.


PI susceptibility results from a complex interplay between protease and Gag proteins, with Gag showing wide variation across HIV-1 subtypes. We explored the impact of pre-treatment susceptibility on the outcome of lopinavir/ritonavir monotherapy.in vitro phenotypic susceptibility testing, with susceptibility expressed as fold change (FC) relative to a subtype B reference strain.Treatment-naive individuals who experienced lopinavir/ritonavir monotherapy failure from the MONARK study were matched  with those who achieved virological response (‘successes’). Successes were defined by viral load <400 copies/mL after week 24 and <50 copies/mL from week 48 to week 96. Full-length Gag–protease was amplified from patient samples for P = 0.17). Among CRF02_AG/G patients, there was a significant difference in lopinavir susceptibility between the two groups , while in subtype B the difference was not significant . Subtype CRF02_AG/G viruses had a median lopinavir FC of 8.7 compared with 3.1 for subtype B (P = 0.001).Baseline lopinavir susceptibility was lower in viral failures compared with viral successes, but the differences were not statistically significant  at baseline and subsequent virological failure on lopinavir/ritonavir monotherapy in antiretroviral-naive patients harbouring subtype CRF02_AG/G viruses. We speculate that this may be important in the context of suboptimal adherence in determining viral failure. Simplification strategies have been investigated to reduce the number of antiretroviral drugs required as part of treatment regimens without compromising treatment efficacy. Boosted PI (bPI) monotherapy has been studied in a small number of randomized trials, with poorer outcomes compared with standard triple therapy when used as initial therapy in the MONARK study9 and a virological failure rate of 20%,10 around 2 million patients worldwide qualify for PI-based second-line treatment, most likely lopinavir boosted with ritonavir. Widespread use of this class of drug raises some concerns, given our poor understanding of virological failure. Indeed, the majority of patients experiencing failure of first-line combined ART with ritonavir-boosted PIs do so without evidence of major PI-associated drug resistance by standard methods.12 Studies have provided evidence for the role of Gag in PI susceptibility15 and have been reviewed.16 In addition, the inclusion of full-length patient-derived Gag alongside its co-evolved protease in in vitro phenotypic assays has been shown to affect PI susceptibility in both treatment-naive and treatment-experienced patients.19 More recently, Env has been implicated in drug resistance following PI exposure.20Based on an estimated 10 million HIV-1-infected patients on antiretroviral therapy2 HIV-1 subtypes B and CRF02_AG were the dominant subtypes, and a higher failure rate was observed in the latter.22 This subtype is prevalent in West Africa and is also present in migrant HIV-1-infected populations in Europe, where subtype B otherwise dominates. Given the evidence for the importance of the inclusion of full-length Gag alongside its co-evolved protease in phenotypic assays and our previous study demonstrating reduced phenotypic susceptibility in patients experiencing virological failure in the MONARK trial, we hypothesized that Gag–protease-mediated susceptibility would differ between patients failing therapy and those with viral suppression, as well as between divergent strains (subtypes).23 This study sought to investigate the viral determinants of treatment failure in the MONARK lopinavir/ritonavir monotherapy arm trial by studying co-evolved, full-length Gag–protease from patients achieving virological response and experiencing virological failure in phenotypic PI susceptibility assays.MONARK investigated lopinavir/ritonavir monotherapy in comparison with lopinavir/ritonavir plus two NRTIs at treatment initiation in treatment-naive patients, with the monotherapy arm showing higher rates of virological failure.JAC OnlineFigure S1, available as Supplementary data at ) and to these we matched eight patients  who achieved virological response (‘successes’). Successes were defined by viral load <400 copies/mL after week 24 and <50 copies/mL from week 48 to week 96  (Table S1).25Full-length Gag–protease was amplified from patient samples as previously described.24 Briefly, 293 T cells were co-transfected with p8.9NSX+-derived test vector containing patient gag–protease, pMDG expressing vesicular stomatitis virus envelope glycoprotein (VSV-g) and pCSFLW expressing the firefly luciferase reporter gene with HIV-1 packaging signal. To determine PI susceptibility, transfected cells were seeded with serial dilutions of lopinavir and harvested pseudovirions used to infect fresh 293 T cells. To determine strain infectivity, transfected cells were seeded in the absence of drug. Infectivity was monitored by measuring luciferase activity 48 h after infection. All experiments were performed in duplicate.PI susceptibility and infectivity were determined using previously described single-cycle assays.We compared baseline characteristics of viral failures and successes using the Mann–Whitney rank sum test for continuous variables and Fisher's exact test for categorical variables. For analyses of lopinavir susceptibility, we defined each individual's susceptibility as the geometric mean of the two measurements. We compared lopinavir susceptibility between viral failures and successes by the Mann–Whitney rank sum test, which is robust for data that are not normally distributed. To check the sensitivity of our results to the choice of analytical method, we repeated the analyses using conditional logistic regression on the matched participants using viral failure or success as the outcome variable and log lopinavir fold change (FC) as the exposure. These sensitivity analyses gave concordant results.Table S1). Baseline CD4 and viral load were marginally higher in cases, but these differences were not statistically significant  and 8 were controls (successes). Ten participants harboured HIV subtype CRF02_AG or G and six harboured subtype B, with subtypes split evenly between cases and controls. No patient harboured virus with major or minor resistance mutations to lopinavir, although a number of polymorphisms were present in protease, some of which are considered consensus amino acid positions in subtype CRF02_AG and G viruses , lopinavir susceptibility appeared lower in virological failures than successes, while the difference was not significant   lopinavir susceptibility in virological successes versus failures: 4.4 (2.9–7.7) versus 8.5 3.6–11), 1, P = 0.P = 0.001)  or failures (P = 0.025).These data suggest there may be an inherent difference in susceptibility between subtypes AG/G and B. Subtype CRF02_AG /G viruses had a median (IQR) lopinavir FC of 8.7 (7.1–10.4), compared with 3.1 (2.7–3.4) for subtype B (in vitro replication capacity (ρ = −0.15)  was not significantly associated with virological failure, with marginally lower levels in virological failures compared with successes .Finally, we also examined the relationship between drug susceptibility and replication of the viruses from each patient. Lopinavir FC showed a weak negative association with ) Figure a, and wa) Figure b. Replic22 The evaluation of a dual regimen of tenofovir plus lopinavir/ritonavir as first line in West Africa in the DAYANA trial also showed poor virological responses relative to standard NNRTI-based regimens,26 while the non-inferiority of another dual regimen, lopinavir/ritonavir plus lamivudine compared with a lopinavir/ritonavir-based triple regimen was demonstrated in other settings in the GARDEL trial.27 Here, we performed a case–control study within MONARK to test the hypothesis that baseline susceptibility, as determined by a full-length cognate Gag–protease assay, is correlated with outcome. In the primary analysis, in which subtype B and CRF02_AG/G were analysed together, we found a non-significant association between lopinavir susceptibility and failure (P = 0.14). In a subtype CRF02_AG/G-specific analysis, we found a significant difference between the two groups despite a relatively small sample size. Furthermore, subtype CRF02_AG/G viruses are substantially less susceptible to lopinavir than subtype B and this may have contributed to the findings of the MONARK investigators that subtype CRF02_AG patients were more likely to experience virological failure than those harbouring subtype B.A previous analysis of the MONARK study suggested an association between the HIV-1 subtype AG (circulating in West Africa) and poorer outcome of lopinavir/ritonavir monotherapy, although there were confounding factors such as treatment adherence.28 This analysis showed that in three patients with subtype CRF02_AG virus the pre-therapy EC50 FC was 0.57, 0.59 and 0.87 relative to the subtype B reference strain. In two subtype B-infected individuals, FCs of 1.46 and 1.49 were reported pre-therapy. The Phenosense assay result would suggest that subtype CRF02_AG viruses in MONARK are more susceptible than subtype B, in direct contradiction to our data using matched Gag and protease sequences .To date, phenotypic analysis using the commercial Phenosense assay (using a patient-derived protease with a subtype-mismatched Gag) had been performed on viruses derived from patients experiencing virological failure in the lopinavir/ritonavir monotherapy arm with the appearance of major PI resistance mutations.29However, the reduced PI susceptibility present in the variants from viral failure patients at baseline does not fully explain the subsequent treatment failure experienced. Six of the eight failure patients did initially achieve virological suppression <400 copies/mL on lopinavir/ritonavir monotherapy at week 24, before experiencing virological failure after >40 weeks of the trial. We hypothesize that PI monotherapy is potent enough to suppress viral replication with high adherence initially, but that reduced PI susceptibility lowers the tolerance or ‘buffer zone’ for subsequent suboptimal adherence. It is possible that patients with viruses demonstrating reduced PI susceptibility at baseline may be better suited to standard combined ART, which is likely to be more forgiving of reduced adherence, as three active agents are present. Alternatively, identification of these patients before treatment initiation would enable interventions to increase adherence and reduce this risk of failure. A third possibility is to closely monitor patients on PI monotherapy and intensify if low-level viraemia or viral rebound occurs.20Limitations of our study include the relatively small sample size, the inclusion of more subtype CRF02_AG viruses in comparison with B and the possibility of viral recombination through our PCR and cloning strategy. Finally, our assay system did not incorporate the native gp160 envelope.In conclusion, we report an association between reduced PI susceptibility at baseline in the absence of known resistance mutations and subsequent virological failure on lopinavir/ritonavir monotherapy in patients harbouring subtype CRF02_AG/G viruses. This is an important finding as it indicates that it may be possible to predict treatment outcome on lopinavir/ritonavir monotherapy from baseline PI susceptibility. We hypothesize that reduced baseline PI susceptibility renders patients more vulnerable to virological rebound when their adherence is sub-optimal. This study suggests that lopinavir/ritonavir monotherapy should not be used in antiretroviral-naive patients infected with CRF02_AG. In maintenance therapy, studies are still needed to evaluate the impact of HIV-1 subtypes on virological response to PI/ritonavir monotherapy, as this regimen may be considered as a treatment option for individual patients in whom real-time viral load monitoring is available.Wellcome Trust and a grant from AbbVie Laboratories. R. K. G. is funded by a Wellcome Trust Fellowship (WT093722MA). K. A. S. was funded by Public Health England (formerly the HPA). I. C. C. was involved in interpretation of data and review of the manuscript, but final content was decided by the principal investigator.This study was funded by I. C. C. is an employee of AbbVie Laboratories and holds stock or options in AbbVie. The remaining authors have none to declare.JAC Online .Table S1 and Figure S1 are available as Supplementary data at


Consistently, both cumulative immunological and virological failure rates  were the lowest in MSM compared with other population groups. Survival analysis indicated that initial CD4 counts ≤200 cells/mm3  significantly contributed to HIV-related mortality during treatment. Timely diagnosis and treatment of HIV patients are vital for improving CD4 level and health outcomes.This study assesses association between CD4 level at initiation of antiretroviral treatment (ART) on subsequent treatment outcomes and mortality among people infected with HIV via various routes in Hunan province, China. Over a period of 10 years, a total of 7333 HIV-positive patients, including 553 (7.5%) MSM, 5484 (74.8%) heterosexuals, 1164 (15.9%) injection drug users (IDU) and 132 (1.8%) former plasma donors (FPD), were recruited. MSM substantially demonstrated higher initial CD4 cell level  than other populations . During subsequent long-term follow up, the median CD4 level in all participants increased significantly from 151 cells/mm Antiretroviral therapy (ART) can significantly reduce mortality and prevent opportunistic infections in HIV-positive patients by strengthening immune response that suppress virus replication ,2. Timel3. This threshold has increased gradually over time in national treatment guidelines [3 in 2008 [China launched its national ART program in 2002 with a treatment threshold of CD4 cell level below 200 cells/mmidelines . In 2004idelines . The ART in 2008 . Previou in 2008 ,10. Not  in 2008 ,11.HIV prevalence among men who have sex with men (MSM) in China has reportedly increased from 1.8% in 2000 to 7.3% in 2013 ,13. MSM We conducted our study in the Hunan province, Central China, which has a population of 66 million . The HIVChina established its national ART database in 2002, which was then managed by the National Centre for AIDS/STD Control and Prevention (NCAIDS), Chinese Centre for Disease Control and Prevention (CDC) . The datIn this study, data was collected from Hunan province of national free ART database. All PLHIV older than 18 who newly enrolled in ART from any treatment provision sites in Hunan province were included in this study. The cohort started from 1 January 2003 and ended at the 31 December 2013. We only used the baseline, follow-up and treatment status information for the purpose of this study.Demographic information, mode of infection, medical history and laboratory test results of patients were collected only once by the health workers at ART initiation, but CD4 count level was monitored after positive confirmation and throughout the course of treatment. Viral load was only recorded at baseline and followed up on a voluntary basis as the detection cost was high. Patients who have experienced immunological failure previously were recommended to receive viral load test, but recently more patients with strong health consciousness also requested for viral load tests. Disease progression stages were classified according to WHO guidelines . Days fr(1)CD4 and HIV viral levels. The median with interquartile range (IQR) of CD4 counts and viral load were calculated every three months in the first year then every six months over the remaining course of follow-up.(2)3 after receiving ART for three months without a concomitant diseases that may sharply decrease the CD4 counts [Treatment failure . Immunological failure was defined as CD4 Cell count of the patient fell below 100 cells/mm4 counts ; virolog4 counts .Three key outcome indicators were collected to evaluate the effects of ART:(3)HIV-related mortality. All death cases were recorded until the end of the study (December 2013). Mortality was compared across different CD4 count strata and transmission route categories. Factors associated with mortality were identified with Cox regression.Considering that the majority of participants  initiated ART after 2010, only a few people have CD4 and viral load test more than 43 months of follow-up, we categorized records beyond 43 months as a single time interval.p-value of less than 0.05 was considered significant in the final model. The patients with missing data were included in the “unknown group”.All surveyed patients were stratified according to their transmission route . All data were entered and analysed using statistical software SAS 9.2 . Descriptive and inferential statistical analyses were performed. The mean, median and IQR were used to summarise numerical variables; whereas frequencies and percentages were used to describe categorical variables. A linear regression model was constructed to verify whether the ascending trend of CD4 Cell counts during the follow-up was significant. The survival analysis was performed to compare the survival probability across transmission groups. A multivariable Cox proportional hazards model was used to identify the hazard factor contributing to HIV-related mortality, immunological failure and virological failure. A This study was reviewed and approved by the Monash University Human Research Ethics Committee . No personal information about the patients were disclosed in this research. The collected data were analysed only for the purposes of this study. Besides the members of the experimental group, no other individual, group, or institution had access to this data. No further informed consent about this study was required.3 . Female has significantly higher CD4 count than male . CD4 count is substantially higher among MSM than other population groups  were included in this study over the period of 2003–2013. A maximum of 82 months follow-up has been recorded after ART enrolment . At treatment initiation, the sample has a median age of 40 years . The median CD4 cell count was 151 cells/mmn groups a. Specifn groups b. Baselin groups .3 (IQR 41–243) to 344 cells/mm3 (IQR 234–477) over the first 42-month of treatment. Out of the 228 patients who received viral load tests, viral load level declined 430 folds from 4.73 log10 copies/mL (IQR 3.69–5.47) at treatment initiation to 2.1 log10 copies/mL (IQR 1.60–3.18) in the same period  to 386 cells/mm3 (IQR 292–470) over the first 42-month of treatment. Similarly, heterosexuals and IDU also showed an upward trend from 144 cells/mm3 (IQR 40–242) to 354 cells/mm3 (IQR 246–485) and 134 cells/mm3 (IQR 38–224) to 332 cells/mm3 (IQR 213–477) respectively, but the level is substantially less than that of MSM at the study end point. CD4 level in FPD have demonstrated the fluctuation in a narrow range during the follow-up, overall it rose from 86 cells/mm3 (IQR 36–181) to 264 cells/mm3 (IQR 177–383) (CD4 level in MSM had a steady increase from 242 cells/mm177–383) a.MSM had consistently the lowest immunological and virological failure rates over time, reached 10.4% and 16.4% at the end of the follow-up. This is followed by FPD . Notably, among the 1164 IDU patients, the percentage increased to 30.1% (134/446) among IDU who retained in treatment for at least 42 months. Similarly, virological failure was found among 45.8% (11/24) IDU during the same period .A total of 1040 patients (14.2%) deceased during treatment . MSM had the highest survival rate (98.3%), followed by the heterosexuals (84.2%) and FPD (66.5%), while IDU had the lowest survival rate (64.5%) at 42 months follow-up .3 were protective factors against treatment failure. In particular, the rate of immunological failure in IDU, MSM and FPD during the 48-month follow-up was approximately 17%, 8% and 12%, respectively. These corresponded to 1.43 (1.35–1.51), 0.54 (0.49–0.59) and 0.66 (0.64–0.69) times higher risk in comparison with heterosexuals. Similarly, MSM and FPD were 47% and 23%  less likely to experience virological failure compared with heterosexuals, whereas IDU was at 39%  higher risk. Patients with CD4 level below 200 cells/mm3 had a 35.6% higher risk of immunological failure  and 25% higher risk of virological failure  than otherwise  than female, and the mortality risk in MSM was only about 20%  of the heterosexuals while the risk is more than double in IDUs . Patients with CD4 level below 200 cells/mm3 had three times higher risk of death  than otherwise. Aging patients have slightly elevated mortality risk   c.This retrospective cohort study demonstrated that MSM in Hunan have higher median CD4 T-cell counts at baseline and retained better health outcomes than other populations throughout the course of ART treatment. MSM consistently demonstrated lower rates of immunological failure, virological failure and mortality compared with the patients infected via other routes. The robust CD4 response and viral suppression presented in MSM are comparable to findings of long-term ART patients in developed countries ,30. Our study confirmed that high CD4 cell level at treatment initiation among MSM can lead to improved treatment outcomes. On the contrary, previous MSM studies in other Chinese settings have consistently reported low testing coverage, which resulted in delayed diagnosis and treatment, and rapid progression to AIDS ,31,32. IMaintaining high CD4 count at early phrase of treatment plays an important role for subsequent treatment outcomes. This is consistent with previous findings in China ,36 and i3, mostly IDU, have the lowest survival probability. Similarly, FPD, with lowest median CD4 level at baseline, demonstrated similar survival probability as IDU. As HIV transmission through illegal blood transfusion occurred mostly during the early stage of HIV epidemics in China, FPD likely experienced delayed diagnosis and treatment due to the absence of a national ART program then [The analysis of HIV-related mortality demonstrated similar results. Participants with baseline CD4 <200 cells/mmram then ,50. Thisram then ,52,53. Iram then ,55. The ram then ,57,58. Tram then ,60. In aA number of limitations of this study should be noted. First, the routes of HIV infection were self-reported by the participants; as such, it is difficult to determine the accuracy of the information. In particular, MSM may choose to conceal their sexual identity due to social stigma. Second, most MSM started ART after 2007, so the record of follow-up was not as complete as that for IDU, FPD and heterosexuals. Besides, the record prior to 2007 may be less accurate than more recent data, owing to the immature reporting mechanism then. This may affect data quality of FPD and comparability between study populations. Third, the study design did not capture risk factors for HIV exposure or information on past interventions that participants might have received. This prevents us from investigating the reasons for their early or late diagnoses. Fourth, as a retrospective study, the recorded information is subjected to recall bias by participants. Fifth, only 228 (3.11%) patients received viral testing at baseline. Given the high out-of-pocket cost of the test, this may have led to overestimation of the actual virological failure rate.Conclusively, our study indicated that HIV-positive MSM can achieve better treatment outcomes and reduced mortality than other at-risk populations over the long-term course of ART if they have high CD4 count at ART initiation. This conveys an important message, that diagnosis and early treatment are possible in an opaque population that is often stigmatised in a developing country setting.


The cohort consisted of 882 patients with 661 subjects presenting with persistent HIV viral load after a self-reported 12 month history of ART use. In this sub-cohort a higher viral load was seen across time (p < 0.05). Illicit drug use, IV drug use, alcohol use, loss of work were associated to having higher viral load means (p < 0.05). HIV viral load mean was lower as BMI increased (p < 0.001). It is imperative to readdress antiretroviral adherence protocols and further study ART tolerance and compliance.The introduction of antiretroviral therapy (ART) has allowed human immunodeficiency virus (HIV) suppression in patients. We present data of a cohort of Puerto Rican patients with HIV who were under treatment with a steady regime of ART across a time horizon of eleven years. The time periods were categorized into four year stratums: 2000 to 2002; 2003 to 2005; 2006 to 2008 and 2009 to 2011. Socio-demographic profile, HIV risk factors, co-morbid conditions were included as study variables. One year mortality was defined. The  In the absence of antiretroviral therapy (ART), human immunodeficiency virus HIV-1) infection causes a longitudinal decline in the CD4 helper T cells with deterioration of the immune system. The lack of effective immunological response increases vulnerability to multiple opportunistic infections  infectio,3,4. Peret al. reported that persistent viral load between 50 and 999 copies/mL was associated to an increased risk of virologic failure [n = 26,567) [The effectiveness of ART in reducing HIV viral load and improvement in CD4 cell counts is well documented . Neverth failure . In addi failure . Ineffec failure . HIV inf 26,567) ,12,13.In 1992, the Retrovirus Research Center (RRC) initiated a longitudinal HIV registry which continues to recruit subjects. Our HIV ambulatory care facility is a public multidisciplinary clinic that accepts patients with diverse clinical history. We receive newly diagnosed patients, patients who have been previously treated with ART or are currently on therapy with ART from other health care facilities in the island. We also receive subjects who have migrated to the island from other states or countries. The profile of our subjects reveal that they are generally from a lower economic stratum, have drug/alcohol HIV risk practices and often have a lower formal education history. For this study, we selected a cohort of subjects which were new to our ambulatory care clinic and had a one year history of stable ART use. We have compared the group according to presence or absence of detectable HIV viral load and have analyzed the profile of subjects with detectable viral load according to sociodemographic variables, HIV risk factors, presence of comorbid clinical conditions, psychological profile and one year mortality. Considering that protease inhibitors became widely available in the island in 1998 and that we were interested in defining the one year mortality, the time period selected was 1st January 2000 through 31th December 2011.We organized our cohort according to year of entry into the ambulatory clinic. The group was stratified in four chronological brackets: January 2000 to December 2002; January 2003 to December 2005; January 2006 to December 2008; January 2009 to December 2011. The dependent variable was detectable viral load defined as greater than fifty (50) copies/mL. Thus the inclusion criteria were newly seen subjects in our ambulatory care clinic and a self-reported twelve (12) month steady use of antiretroviral therapies (ART). Steady use of ART was defined as use of at least three antiretroviral drugs in a daily basis. Additional analyses were made according to the presence or absence of detectable HIV viral load.A total of 882 new subjects with a 12 month self reported history of ART were seen in the HIV ambulatory care clinic in the defined period. A subcohort of 661 patients had detectable HIV viral load. After written informed consent, an initial questionnaire was completed via interview, the medical record was abstracted and data tabulated into our data base. The data abstraction protocol included past medical data from twelve (12) months prior to the initial interview.Study variables were gender, age, body mass index, risk behavior variables and co-morbid conditions. We established the one year mortality amongst the different groups in our cohort. The body mass index (BMI) at study entry was calculated using the following formula The Statistical Package of Social Sciences program version 21.0.1  was used to perform univariate, bivariate and multivariate analyses. Descriptive analyses included frequencies, percentages, central tendency measures (mean and median) and dispersion measures (standard deviation measures and quartiles). A normality test using the Shapiro-Wilk estimate was performed in all variables in order to select the correct parametric or non-parametric test. Differences between mean viral load and year bracket were analyzed with an ordinary one-way ANOVA with a Bonferroni correction. Differences among proportions were assessed using a chi-square test approach or Fisher’s exact test with a linear-by-linear correction.Y is a matrix with series of p multivariate measurements; X is a design matrix; B is a parameter matrix and U is the error/noise matrix. In this study, a GLM mixed design ANOVA was built in order to assess the change of estimated marginal mean viral load through a time trend within groups, controlled by use of antiretroviral therapy. Inclusion of factors into the model was mediated by having ≤0.05 at a bivariate level. A Box’s M test was performed to assess if our models have the assumption of equality of covariance homogeneity (p > 0.05). The Pillai’s Trace estimator was used in order to know if the fixed factors contribute in the variability of the dependent variable (p ≤ 0.05).The general linear model (GLM) is a statistical linear model derived from the multiple regression model: A test of between-subjects effect with a pairwise comparison using a Bonferroni adjustment for multiple comparisons was applied to perceive statistical differences between and within the groups. The significance level (α) was set at ≤0.05.p < 0.05). There was no difference in the one year mortality between groups. In p < 0.0001). Bonferroni post hoc test demonstrated that all three time periods significantly differ from the initial one (2000–2002).There were 661 (75%) patients with steady ART use and detectable HIV viral load and 221 (25%) subjects without detectable viral load. p > 0.005). All fixed factors contributes to the model . We use estimated marginal means (EMM) for the expression of the HIV viral load. We were interested in defining variables relevant in explaining the incremental values of HIV viral load across time. For the model, we included variables reported in the literature to be relevant for patients with high HIV viral load in subjects in the context of ART use. A significant association with higher HIV viral load and all the selected variables were seen. In the group of males a significant steady increase mean viral load was seen (p < 0.001). When examined independently all levels of BMI were associated to increased HIV viral load, although a low BMI was associated with the steepest increase in detectable viral load across time. Intravenous drug use, cocaine, crack and cannabis use were also associated with an increase in mean viral load (p < 0.05). Alcohol abuse and loss of work were seen to be associated to having higher viral load means across time (p < 0.05). Our analysis suggests that the increment of HIV viral load across the time had a stronger association with the selected variables in the last period examined. The group of factors  which have been traditionally associated to ART failure, appears to be present in a higher frequency in the last period studied. We have identified loss of work as an additional factor associated to ART failure.In The majority of newly registered subjects in our cohort have detectable HIV levels in spite of prescribed ART. We believe this is a reflection of the particular HIV risk profile of patients who receive health care in our ambulatory clinic. Our center is one of the few facilities in the island which are government sponsored and predominantly serve a population with government sponsored health care insurance ,15. The The problem of medication adherence and toxicity is a serious issue in our cohort. We have demonstrated that the combination of risky behavior and being underweight resulted is a detrimental scenario that may contribute to ART inefficacy. Previous studies have also linked the association of viremic suppression failure, IV drug use and alcohol abuse with lack of medication adherence ,16. We hWe demonstrate that in a time horizon of eleven years, the risk scenarios associated to detectable HIV viral load, have increased in prevalence in the population of patients we serve. Similar to our findings, other studies suggest that illicit drug use, a low socio demographic profile and high rate of abnormal psychological profile are factors which correlate with ART failure . Issues We were interested in comparing variations across time of detectable viral load within each gender group. Our study reveals that within males the proportion with detectable viral loads has been progressive increasing. In the last period examined, a large percent of males who entered the cohort had detectable viral levels. In contrast, although females who present with detectable viral load represent more than half percent of the cohort, the rate with detectable virus tend to stabilize in the last time bracket of the eleven years study period ,19. In oEfforts to restructure the medication adherence protocols, along with introduction of innovative methods to improve medication adherence are essential for our community. This issue has been identified in other communities leading to innovative interventions . Our stuAccess to the necessary ART drugs is not an important issue in our center since all medications prescribed to the subjects are offered free of charge to the patients. Nevertheless adverse drug effects and the issue of toxicity are likely important factors in our patients since a substantial number of subjects have comorbidities in the form of diabetes mellitus and cardiovascular diseases . Our datThe finding that the presence of detectable HIV viral load is not associated to increased 1 year mortality has been described in other studies . We seleOther studies have also suggested that underweight subjects in the high risk category for ART failure, are partly responsible for lack of control of the HIV epidemic in spite of improvement in ART therapy . In addiThe subjects in our cohort are not representative of the HIV infected population at large; however they remain a relevant and important cohort in the community of infected patients, which will continue to defeat the efforts to control the rate of new HIV infections. Present prevention and intervention strategies must be reevaluated and readdress in order to redirect the efforts of stopping the HIV epidemic. Further intervention protocols will need to consider the cohort of subjects with the high HIV risk practices associated to ART failure.


Access to highly active antiretroviral therapy (HAART) is expanding in Latin America. Many patients require second and third line therapy due to toxicity, tolerability, failure, or a combination of factors. The need for third line HAART, essential for program planning, is not known.Antiretroviral-naïve patients ≥18 years who started first HAART after January 1, 2000 in Caribbean, Central and South America Network (CCASAnet) sites in Argentina, Brazil, Honduras, Mexico, and Peru were included. Clinical trials participants were excluded. Third line HAART was defined as use of darunavir, tipranavir, etravirine, enfuvirtide, maraviroc or raltegravir. Need for third line HAART was defined as virologic failure while on second line HAART.Of 5853 HAART initiators followed for a median of 3.5 years, 310 (5.3%) failed a second line regimen and 44 (0.8%) received a third line regimen. Cumulative incidence of failing a 2nd or starting a 3rd line regimen was 2.7% and 6.0% three and five years after HAART initiation, respectively. Predictors at HAART initiation for failing a second or starting a third line included female sex , younger age , and prior AIDS .Third line regimens may be needed for at least 6% of patients in Latin America within 5 years of starting HAART, a substantial proportion given the large numbers of patients on HAART in the region. Improved accessibility to third line regimens is warranted. Unprecedented global efforts have resulted in the rapid expansion of access to highly active antiretroviral therapy (HAART) throughout the world. In 2002 only 300,000 people living with HIV were receiving HAART in low- and middle-income countries; in 2012 this figure increased to 9.7 million Compared to other resource-limited settings (RLS), Latin America and the Caribbean (LAC) have had higher rates of HAART coverage. In 2012, 715,000 people were receiving HAART in low and middle income countries within LAC, accounting for a regional coverage of more than 70% At a global level, increased attention is being paid towards second line HAART regimens, particularly their outcomes and associated factors Therefore, the objectives of this study were to estimate the current need and use of third line regimens among patients initiating antiretroviral therapy in Latin America and to determine factors associated with need for third line drugs.The Caribbean, Central and South America Network (CCASAnet) has been described elsewhere The primary outcomes were: 1) starting a third line regimen and 2) virologic failure after starting a second line regimen. A third line regimen was defined as any regimen containing one of the following drugs: darunavir, tipranavir, etravirine, enfuvirtide, maraviroc or raltegravir. A second line regimen was defined as a regimen containing a boosted protease inhibitor (PI) preceded by a regimen containing either a different PI or a non-nucleoside reverse transcriptase inhibitor (NNRTI). Virologic failure after starting a second line regimen was defined as one of the following: 1) HIV-1 RNA level never dropped below 400 copies/ml after 6 months of therapy, 2) HIV-1 RNA level dropped below 400 copies/ml but then there were two consecutive values>400 copies/ml (without regards to time between measurements), 3) HIV-1 RNA level dropped below 400 copies/ml but then there was a single measurement>1000 copies/ml. The sensitivity of the results to this definition of virologic failure was investigated by removing the third criterion. The cutoff of 400 copies/ml was chosen because it was the HIV-1 RNA detection limit for many of the sites over much of the study period.Clinical stage prior to initiation of first HAART was categorized as AIDS or not AIDS; clinical AIDS was defined as CDC stage C, WHO stage IV, or a specification of AIDS at first visit. CD4 at HAART initiation was defined as the CD4 cell count closest to HAART initiation but no more than 180 days prior to or 7 days after. HIV-1 RNA at HAART initiation was defined as the measurement closest to initiating HAART but no more than 180 days before; any HIV-1 RNA measurement after initiating was not included. HIV-1 RNA at the start of the second line regimen was similarly defined.http://biostat.mc.vanderbilt.edu/ArchivedAnalyses.The time until either of the two outcomes (starting a third line regimen or virologic failure while on a second line regimen) was assessed as an approximate measure of the time until the need for third line HAART. The cumulative incidence after HAART initiation (time 0) of the composite endpoint was estimated treating death as a competing event. The cumulative incidence of loss to follow-up, defined as no patient laboratory or medical visit within the year prior to the database closing date, was also estimated treating death as a competing event. Risk factors for the composite endpoint were assessed using Cox proportional hazards models. All models (both unadjusted and adjusted) were stratified by site. The primary adjusted models included sex, probable route of infection , and calendar year, age, CD4 count, and AIDS at HAART initiation. Covariates were chosen a priori based on availability and perceived relevance. Secondary analyses also included pre-cHAART log-transformed HIV-1 RNA levels. The adjusted analyses used multiple imputation to account for missing data. Age, pre-HAART CD4 count, calendar year, and log-transformed HIV-1 RNA levels were included in the models using restricted cubic splines with 3 knots to relax linearity assumptions. The proportional hazards assumption was assessed using a global test for correlation between scaled Schoenfeld residuals and time; proportional hazards was deemed reasonable (p>0.05). All analyses were performed using R Statistical Software; analysis scripts are available at 3, and 41% had AIDS prior to HAART initiation. The vast majority of patients (85%) started a regimen containing an NNRTI; boosted PIs were prescribed as the first regimen for 697patients (12%). The median follow-up was 3.5 years (interquartile range [IQR] 1.5–6.0). The cumulative incidence of loss to follow-up was 8% at 3 years, 14% at 5 years, and 21% at 7 years. The average frequency of HIV-1 RNA measurements recorded in the database was 2.6 per year, although this varied by site (ranging from a median of 0.8 measurements per year in IHSS/HE-Honduras to a median of 3.4 in CMH-Argentina).A total of 5853 HAART initiating patients were included in this study: 882 from CMH-Argentina, 1382 from FC-Brazil, 918 from IHSS/HE-Honduras, 674 from INCMNSZ-Mexico, and 1997 from IMTAvH-Peru. Patient characteristics at HAART initiation are shown in 3 (IQR 38 to 246) and 62% experienced a prior AIDS event. Thirty-six (12%) of these patients subsequently died. Of note, 32 (10%) of these failures occurred while there was a reported treatment interruption. In secondary analyses defining virologic failure as two consecutive HIV-1 RNA measurements>400 copies/ml, 174 (18% of those starting a second line or 3% of HAART initiators) experienced virologic failure after starting a second line regimen.Over the course of follow-up, 993 patients (17%) started a second line regimen. Of these patients, 310 (31% of those starting a second line) experienced virologic failure after starting the second line regimen. Characteristics of these patients are shown in 3 (IQR 26 to 130) and 26 (63%) having had prior AIDS. Notably, no patient from IMTAvH-Peru and only one from IHSS/HE-Honduras started a third line regimen. Five (11%) patients starting third line therapy subsequently died; deaths occurred 0.5, 3.2, 3.2, 4.8, and 6.3 months after starting the third line regimen. Of those who failed a second line regimen who did not start a third line regimen or die (n = 256), 51% (n = 131) changed to at least one additional subsequent regimen during follow-up, but none of these regimens met the definition for third line. Of the 68 who had only 1 subsequent regimen, 61 experienced virologic failure, 4 re-suppressed and 3 did not have viral load determinations.Over the entire follow-up period, 44 (0.8%) patients started a third line regimen. Among the 44 third line regimens started, 37 (84%) contained raltegravir, 20 (45%) contained darunavir, 10 (23%) contained etravirine, and 1 (2%) contained enfuvirtide. More common third-line regimens were: raltegravir + boosted PI not darunavir , raltegravir + darunavir , darunavir + NRTIs  and raltegravir + NRTIs . Characteristics of patients starting a third line regimen are shown in As a crude measure for the need for third line therapy, we considered the composite endpoint, failure of a second line or start of a third line regimen. A total of 333 patients (5.7% of HAART initiators) experienced this composite event. The cumulative incidence of starting a third line or failing a second line regimen is shown in In a sensitivity analysis, we repeated the primary analysis limited to the subset of 4988 patients whose first HAART regimen contained an NNRTI. Results remained largely consistent. Two hundred and forty-nine patients (5.0%) failed a second line regimen and 29 patients  started a third line regimen. The estimated incidence of the composite endpoint was 2.8%, 5.6% and 8.5% at 3, 5, and 7 years. We also performed an additional sensitivity analysis including clinical trial participants (n = 635), excluding those who used third-line drugs as part of their initial regimen. The estimated incidence of the composite endpoint when including clinical trial participants was similar, albeit slightly higher, than the primary analysis: 3.0%, 6.4%, and 9.6% at 3, 5, and 7 years  were not accounted for.We found that female sex, younger age, prior AIDS, and a lower CD4 count at baseline were associated with a higher hazard of experiencing the composite endpoint. This is the first time we have seen worse HAART outcomes among females in our cohort; in previous studies female sex was not associated with mortality, HAART change, or late presentation to care This analysis has several limitations in addition to those already mentioned. Our measure of need for third line is a crude measure, which is certainly not completely accurate. It is a function of the frequency of viral load measurements in the database, highly variable between sites, and we do not have data on adherence. The former limitation may lead to under-estimation of need for third line regimens, the latter to unpredictable changes. Indeed, the site in Honduras had both the lowest estimated rate of the composite endpoint (data not shown) and the lowest frequency of viral load measurements. HIV/AIDS programs with limited access to virologic monitoring also tend to be those with limited access to third line regimens. Expansion of access to viral load monitoring should also prompt access to third line drugs for those in need. Adherence and drug resistance, well-established as determinants of treatment failure in other cohort studies Our sites by no means represent all of Latin America; we only have included a small number of sites in a portion of the countries in the region. Sites in CCASAnet are mainly referral centers in their respective countries and included patients may therefore have a different predisposition to requiring third-line drugs compared to those patients who do not participate in these cohorts. CCASAnet sites belong to different public health systems and follow local or national guidelines, which differ across countries. With only five sites we were not able to study the potential association between rates of failure and site-level variables, such as availability of food and transport subsidies and peer and other adherence support.With the limitations noted, this study is the first to investigate need for third line regimens in Latin America and may be useful to policy makers for rough estimates of third line need