A low body mass index (BMI) at antiretroviral therapy (ART) initiation is a strong predictor of mortality among HIV-infected adults in resource-constrained settings. The relationship between nutrition and inflammation-related serum biomarkers and early treatment outcomes  in this population is not well described.2 or CD4+ lymphocyte counts of less than 50 cells/mm3, or both, was followed prospectively during the first 12 weeks of ART. Baseline and serial post-treatment phosphate, albumin, ferritin and highly sensitive C-reactive protein (hsCRP) serum levels were measured. The primary outcome was mortality.An observational cohort of 142 HIV-infected adults in Lusaka, Zambia, with BMI under 16 kg/mLower baseline phosphate and albumin serum levels, and higher ferritin and hsCRP, were significantly associated with mortality prior to 12 weeks , independent of known risk factors for early ART-associated mortality in sub-Saharan Africa. The time-dependent interval change in albumin was associated with mortality after adjusting for the baseline value , but changes in the other biomarkers were not.The predictive value of serum biomarkers for early mortality in a cohort of adults with malnutrition and advanced HIV in a resource-constrained setting was primarily driven by pre-treatment values, rather than post-ART changes. Interventions to promote earlier HIV diagnosis and treatment, address nutritional deficiencies, and identify the etiologies of increased systemic inflammation may improve ART outcomes in this vulnerable population. A reducsettings -12.2) and/or immunosuppressed (CD4+ lymphocyte count below 50 cells/mm3) adults initiating treatment in Lusaka, Zambia [We previously demonstrated that serum phosphate levels at ART initiation are independently and negatively associated with early mortality in an observational cohort of severely malnourished  changes in inflammatory biomarkers or albumin, and subsequent health outcomes in persons living with HIV ,17, but 2 or a CD4+ lymphocyte count below 50 cells/mm3 initiating ART at a public sector clinic in Lusaka, Zambia, in an observational, prospective cohort study to assess metabolic predictors of all-cause mortality in the first 12 weeks of treatment. The study setting, eligibility criteria, design and procedures have been previously described [+ lymphocyte count below 200 cells/mm3, or WHO stage 3 disease and a CD4+ lymphocyte count below 350 cells/mm3); were intending to start therapy the same day; met the BMI and/or CD4+ threshold criteria; and agreed to adhere to the study visit schedule and laboratory testing requirements.We enrolled 142 HIV-infected adults with a BMI of less than 16 kg/mescribed . BrieflyAt the enrolment visit and the subsequent study visits at one, two, four, eight and 12 weeks post-ART initiation, participants were evaluated by a research nurse and a clinical officer and/or a supervising physician. The first-line ART regimen was selected from the national programme formulary: two nucleoside reverse transcriptase inhibitors in combination with one non-nucleoside reverse transcriptase inhibitor.At the initial visit, a detailed health history, review of systems, physical examination and laboratory testing  were performed. Phosphate and albumin were measured at each subsequent study visit, while ferritin measurements were repeated at one, two, four and 12 weeks, and highly sensitive C-reactive protein (hsCRP) measurements were repeated at one, four and 12 weeks post-ART initiation. Thirteen participants received phosphate supplementation according to predetermined algorithm based on serum level .Participant deaths were reported to the study staff by the health clinic. If a participant missed a study visit and could not be contacted by phone, community outreach teams attempted to locate the individual or a close relative to determine the vital status . If the + lymphocyte counts were performed using a Beckman Coulter Epics XL-MCL flow cytometer , and hemogram using a Horiba ABX Pentra 80 .Routine and study-specific chemistry assays were measured using a Roche COBAS Integra 400+  or a Pointe 180 Chemistry Analyzer . CD4+ lymphocyte count and BMI to extract the first principal factor to represent these variables at baseline. All Cox models were adjusted for sex and this principal component.Cox proportional hazards models were used to assess the relationship between the baseline nutrition or inflammation serum biomarker values and time to death. The biomarkers were modelled as continuous variables and expanded using restricted cubic splines to avoid linearity assumptions. To reduce the number of variables in the Cox models, we used a principal component analysis with age, hemoglobin, CD4If the vital status at 90 days was unknown , the participant was censored at the last study visit date. A second multivariable regression used similar techniques to model the relationship between the baseline biomarkers and a composite endpoint of time to death or loss to follow up. We accounted for missing baseline status values  and serum biomarkers  using multiple imputation techniques . The proTo visualize longitudinal data, we plotted the serum indicators of interest for the alive, deceased and deceased/lost cohorts against the number of days on ART; each participant required a minimum of two recorded values for inclusion . For each variable, we sketched a locally weighted scatterplot smoothing (LOWESS) curve by fitting a polynomial surface using local (weighted) least squares regression .http://www.r-project.org) was used for data analyses.Cox models with baseline and time-dependent covariates were used to assess the relationship between serial biomarker values and time to death, or the composite endpoint of time to death or loss to follow up. Each biomarker was modelled separately, and the model was adjusted for the biomarker baseline serum value, in addition to sex and the principal component . If the participant had no recorded serum level within a given time interval , he or she was dropped from the risk set for that interval. R-software 2.11.0 , and the Institutional Review Boards at the University of Alabama at Birmingham  and Vanderbilt University .2 and 110 (77%) had CD4+ lymphocyte counts below 50 cells/mm3 . Twenty-five participants died over the 12-week follow-up period ; 10 (40%) participants died within four weeks of starting ART, although none died in the first week. The median time to death was 34 days . Thirty-three participants (23%) were lost to follow up; the median follow-up time for those lost was 58 days . Table We enrolled 142 participants between 6 November 2006 and 12 November 2007; 59 (42%) participants had BMI below 16.0 kg/mTable Conversely, higher baseline serum ferritin and hsCRP levels were associated with increased mortality; compared with a ferritin value of 25 μg/L, a baseline serum level of 250 μg/L was associated with an approximate 67% increased hazard of mortality at 12 weeks , and a value of 1000 μg/L was associated with a nearly 10-fold increased hazard . A baseline hsCRP level of 15 mg/L was associated with a nearly two-fold increased hazard of death compared with a value of 5 mg/L .All adjusted hazard ratios were significantly different from zero (p < 0.05). The calculated hazard of reaching the combined endpoint of mortality or loss to follow up for each gradation of the serum indicators was less pronounced compared with the hazard of mortality alone, and the association was not statistically significant for phosphate or hsCRP.Figure Table For interval increases in phosphate, ferritin and hsCRP, the adjusted hazard ratios demonstrated a trend in the same direction as the hazard ratios for interval changes in the baseline biomarker values Table , but theWe previously reported that baseline serum phosphate predicted early mortality in our cohort , so we iWe also repeated the time-dependent Cox analyses by "carrying forward" the last recorded laboratory value for each serum biomarker until the next recorded value or until death, loss to follow up or study termination occurred . An interval increase in albumin remained a significant predictor of mortality and the composite endpoint  while interval changes in phosphate, ferritin and hsCRP remained non-significant.We found that pre-treatment nutrition and inflammation serum biomarker levels were associated with mortality prior to 12 weeks among adults with advanced malnutrition and/or immunosuppression initiating ART in a resource-constrained setting. A post-treatment interval change in albumin was also a significant predictor of early mortality, while changes in phosphate, ferritin and hsCRP were not. Our study is the first to describe the relationship of these biomarkers to survival in the immediate post-ART period among patients in the advanced stages of HIV disease, but our findings support similar prior studies investigating longer term health outcomes ,17,22.These findings do not imply a causal relationship between elevated inflammation biomarkers or low phosphate or albumin and health outcomes, as individuals with untreated HIV and advanced malnutrition likely have multiple complex metabolic and physiologic derangements. Systemic inflammation in the setting of HIV infection may be a response to occult opportunistic infections, HIV-1 replication, immune reconstitution inflammatory syndrome, or other conditions. Elevated ferritin, in particular, may principally represent a reaction to infectious agents. The pathophysiologic processes contributing to mortality in the immediate post-ART period are a critical research uncertainty and likely differ from those present after several months or years on treatment.Prior studies have reported greater baseline immune activation in cohorts of HIV-infected and non-infected African adults compared with similar groups in the US and Europe -25. ThisWe previously reported that the absolute value of one-week serum phosphate and the change from the pre-treatment level were not significantly associated with mortality in this cohort, as might be observed in the refeeding syndrome . This coRelative long-term  declines in serum albumin are associated with increased mortality among HIV-infected women (both with and without ART) , but abs+ lymphocyte count, BMI and hemoglobin, but residual confounding and/or other unmeasured variables may have affected the associations between serum biomarkers and mortality. Our study investigated relatively few biomarkers of inflammation and nutrition; future studies of early mortality should include a wider range of variables .The time-dependent analyses of interval changes in phosphate, ferritin and hsCRP demonstrated non-significant hazard ratios that uniformly trended in the same direction as the ratios for the baseline values, suggesting that our study cohort was potentially not large enough to detect a true association. Additionally, our analyses adjusted for potential confounding variables, including sex, age, CD4Our cohort also had a high rate of participant attrition, but the observed loss rates are similar to reports from other programmatic cohorts in sub-Saharan Africa . It is lIn this observational cohort study, pre-treatment phosphate, albumin, ferritin and hsCRP serum levels were associated with mortality in the first 12 weeks on ART, but only the interval change in post-treatment albumin was associated with this outcome, while changes in the remaining biomarkers were not. The presence of increased baseline inflammation biomarkers among those deceased at 12 weeks may indicate the presence of undiagnosed secondary infections, such as tuberculosis, fungi and parasites.Measurement of pre-treatment phosphate, albumin, ferritin and hsCRP serum levels may have a role in the risk stratification of low BMI adults starting ART, and in the future, could prompt additional diagnostic procedures, trials of anti-inflammatory therapies, nutritional supplementation, or other targeted intervention strategies. The role of post-treatment monitoring of phosphate and inflammation biomarkers should be explored in larger studies.Low BMI individuals represent a considerable proportion of adults requiring HIV care in resource-constrained settings, and further study of the metabolic and physiologic derangements, co-morbid infections, and potential therapeutic interventions to improve outcomes in this vulnerable population are necessary.The authors declare that they have no competing interests.DH, CN, EK, IZ and LM were responsible for study design and data collection. MB, BS and JK performed the statistical analyses. JC and EK performed the laboratory analyses. JK, MB, EK, CW, JC and AM drafted the manuscript, which all authors reviewed, edited and approved.


Changes in CD4 cell counts are poorly documented in individuals with low or moderate-level viremia while on antiretroviral treatment (ART) in resource-limited settings. We assessed the impact of on-going HIV-RNA replication on CD4 cell count slopes in patients treated with a first-line combination ART.Naïve patients on a first-line ART regimen with at least two measures of HIV-RNA available after ART initiation were included in the study. The relationships between mean CD4 cell count change and HIV-RNA at 6 and 12 months after ART initiation (M6 and M12) were assessed by linear mixed models adjusted for gender, age, clinical stage and year of starting ART.3,338 patients were included  and the group had the following characteristics: a median follow-up time of 1.6 years, a median age of 34 years, and a median CD4 cell count at ART initiation of 107 cells/μL. All patients with suppressed HIV-RNA at M12 had a continuous increase in CD4 cell count up to 18 months after treatment initiation. By contrast, any degree of HIV-RNA replication both at M6 and M12 was associated with a flat or a decreasing CD4 cell count slope. Multivariable analysis using HIV-RNA thresholds of 10,000 and 5,000 copies confirmed the significant effect of HIV-RNA on CD4 cell counts both at M6 and M12.In routinely monitored patients on an NNRTI-based first-line ART, on-going low-level HIV-RNA replication was associated with a poor immune outcome in patients who had detectable levels of the virus after one year of ART. Antiretroviral Therapy (ART) has undoubtedly changed lives, both in resource-rich and in resource-limited settings (RLS). While a large majority of patients on antiretroviral (ARV) drugs achieve sustained virological suppression, some experience a treatment failure eventually leading to treatment change. Treatment switches to second–line ARV regimens in RLS occur at a lower rate than expected due to several constraints: limited access to virological monitoring, limited availability of suitable ARV drugs, pill burden, toxicity and cost, thus limiting the use of second-line ART regimens even in failing patients-4. OveraCurrently, most treatment failures are diagnosed by a CD4 cell count decrease, or by a clinical event as per the 2006 World Health Organization (WHO) guidelines,8.Home-Based AIDS Care [HBAC] and Development of Antiretroviral Therapy in Africa [DART][Two randomised trials,  based first-line ARV regimen in RLS. For this purpose, we analysed changes in CD4 cell counts in patients with an incomplete virological response or with a virological failure to two ARV drug classes.http://www.iedea-hiv.org/). Data sources, the merging of data and quality control procedures have been described elsewhere[The Antiretroviral Therapy in Low-Income Countries (ART-LINC) Collaboration is a network of antiretroviral treatment programs in Africa, Latin America and Asia. This project has been reorganised in the International epidemiological Database to Evaluate AIDS (IeDEA) initiative  with gender and date of ART initiation known, treated with a first–line ARV combination including two nucleoside analogues (NRTIs) and one protease inhibitor (PI) or one NNRTI. Patients needed to have an HIV-RNA measurement at least six and 12 months after ART initiation (plus or minus three months) and to have at least one CD4 cell count measure between six months (or within the three months before) and 18 months following ART commencement. We excluded all patients with undetectable HIV-RNA levels (<500 copies/ml) at ART initiation.We examined the data for these subjects up to 18 months after ART initiation or at the date of switch to a second-line ARV regimen. Second-line ART was defined by at least one therapeutic class modification and at least one NRTI modification. A patient was considered lost to follow-up if the patient was not known to have died and the time interval between the last date he (she) was known to be alive and the closure date of cohorts  was >6 months.a priori) three HIV-RNA thresholds  6 and 12 months after ART initiation.We assessed the CD4 cell count response to treatment between six and 18 months after ART initiation, using linear mixed models. The changes in CD4 cell count were modeled with two slopes: the first slope was for the six to 12 months after ART initiation and the second slope was for the 12 to 18 months after ART initiation. An intercept at the initial time of the analysis (six months after ART initiation) was also included in the linear mixed models. To take into account the correlation of the repeated measurements within each patient, the parameters were allowed to vary from one patient to another through the random intercept and the two random slopes. An unstructured covariance matrix was used for random effects, allowing a correlation between the individual baseline level and the slopes. To avoid any collider bias CD4 count changes were not adjust for initial CD4 count as fixed effects. We considered  women starting ART in 2004 or later at clinical stage A, B (CDC classification) or I, II (WHO classification) and with a viral load at M6 and M12 <500 copies/mL as the reference group. We compared mixed models using these HIV-RNA thresholds with the Akaike Information Criterion (AIC).All analyses were performed using SAS version 9.1 .We included 3,338 patients from 14 different cohorts in this analysis ; 3,038, 2,969 and 814 individuals had an HIV-RNA level below the threshold of 500 copies/ml at M6, M12 and M18, respectively, after starting ART .A majority of patients (83.9%) had three or more HIV-RNA determinations during the study period. Similarly, 87.8% had at least three CD4 cell counts and 46.2% had a greater number of measurements up to 18 months. Median HIV-RNA level (log10) at ART initiation was 5.07 (IQR 4.53-5.54) and the median CD4 cell count was 107 cells/mmAmong patients initiating ART with HIV-RNA levels above 10,000 copies/ml, 91.7%  and 90.0%  achieved HIV-RNA levels below 500 copies/ml six months and 12 months, respectively, after ART commencement. Among patients with undetectable (<500 copies/ml) HIV-RNA levels  at M6, 93.0%  remained with an undetectable HIV-RNA level and 3.0% (n = 92) had an HIV-RNA level ≥10,000 copies/ml at M12. Among patients with undetectable HIV-RNA levels six and 12 months after starting ART , 750 (94.1% of patients with available data) remained with an undetectable HIV-RNA at M18.We assessed the effect of the HIV-RNA level while on ART on the mean CD4 cell count slope. Figure TableOur data demonstrates that among patients initiating therapy in RLS with (mainly) an NNRTI-based regimen, CD4 cell count recovery is impaired in the presence of on-going HIV-RNA replication over an 18-month period. We were not able to find a minimal HIV-RNA threshold below which viral replication had no impact on immunological restoration. Our analysis showed an impact of HIV-RNA replication at 12 months on the direction of the CD4 cell count slope; thresholds of 10,000 or 5,000 copies were equally predictive of the direction of the CD4 cell count slope in the adjusted analysis.Current ART guidelines recommend changing therapy when virological failure occurs-16. The The optimal response to low or moderate-level viremia in patients on ART in RLS has been controversial. Analyses performed in countries with regular and frequent HIV-RNA monitoring and using PI-based ARV regimens tend to suggest that the use of an HIV-RNA threshold of 5,000-10,000 copies/mL to define failure in a regimen-adherent patient with no other reasons for an elevated HIV-RNA  is not associated with clinical and immunological deterioration in cohort studies,18,22. TIt is thus critical to accumulate data from countries where the majority of patients are now receiving ART, where the treatment switch is going to occur late and where first-line ARV combinations are different from the standard practice in high-income countries from where most clinical guidelines have been issued.Because the WHO now recommends using targeted or sometimes routine use of HIV-RNA measurements in public-health oriented programs, much effort needs to go into making HIV-RNA determination available in RLS. However, the cut-off describing when to switch patients failing an NNRTI first-line regimen with few remaining therapeutic options has not been firmly established and depends on the objective: if the aim is to impact on HIV transmission or to prevent viral resistance-28, thenIn this large multicohort study, we observed that in patients experiencing virological failure, the impact on immune restoration was observed after the first year of ARV treatment; CD4 cell count slope one year after ART initiation was altered by any (even low-level) HIV-RNA replication, regardless of the threshold considered . By contrast, all patients who had a suppressed viral load 12 months after ART commencement experienced a rise in CD4 cell counts  had a better immune recovery when compared with the middle-age group. Additionally, the calendar year of starting ART and the stage at ART initiation were good predictors of early immunological outcome. Considering an HIV-RNA threshold of 10,000 copies/mL, which provided in our multivariate model the best prognostic value for immunological response, elevated HIV-RNA levels were always associated with impaired immune reconstitution.We recognise several limitations in our analysis. Patients have been included in our study according to the existence of frequent HIV-RNA monitoring, but only a minority of patients fulfilled our criteria of biological monitoring. Selection bias is therefore possible, although we verified that none of the patients in our study had entered specific therapeutic trial protocols but were rather prescribed viral load testing during specific periods when this laboratory exam was available in the clinic. In addition, we were unable to detect differences between treatment regimens, as patients in RLS are generally prescribed with standard NNRTI-based first-line regimens. However, treatment homogeneity is helpful in controlling confounding factors related to different drug regimens. Finally, we could not consider clinical endpoints, as we had a very limited number of deaths in the selected patient population, possibly due to the short follow-up. For this reason, the clinical significance of the differences in CD4 slope reported in our analysis cannot be evaluated – although many cohorts from resource limited settings clearly assessed the relationship between AIDS-related events, non AIDS related events and death and CD4 cells.Our data suggest that a failing regimen with documented HIV-RNA replication should be switched onto a second-line regimen, in line with recently issued WHO guidelines requesting a decrease in the HIV-RNA threshold to inform the switching decision . We recognise that immune recovery is not the only factor to consider regarding HIV disease management in the short-term after ART initiation. Whenever possible, HIV-RNA levels should be fully suppressed, not only to prevent accumulation of resistance mutations but also to prevent HIV transmission. It is tWe have no competing interests to declare in relation to this paper. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.AB, ES, RW, ED, EM, JM, KMEF, MS, NK, DB, PM, SVDB, and CZ contributed the necessary data from their health facilities. EB collected the data. AC, FB, FD contributed to the study design. EB and RT carried out the statistical analysis and EB, RT, AC, FB and FD interpreted the results. FD, AC and RT contributed to the study coordination. AC first drafted the manuscript. All authors had a critical revision of the manuscript for important intellectual content. All authors have read and approved the final manuscript.Agence Nationale de Recherches sur le Sida et les hepatites virales (ANRS). Centre de Prise en Charge de Recherches et de Formation (CEPREF)/Agence Nationale de Recherches sur le Sida et les hepatitis virales (ANRS) 1203 COTRAME Cohort ; Senegalese Antiretroviral Access Initiative (ISAARV), ANRS 1290 ; Academic Model for the Prevention and Treatment of HIV/AIDS (AMPATH), Moi University College of Health Sciences/University of Indiana ; Adherence Monitoring Uganda (AMU) cohort, Makerere-University of California in San Francisco ; Kamuzu Central Hospital/Lighthouse Trust ; Connaught Clinic ; Gugulethu ART Programme, ; Khayelitsha ART Programme, ; Operational Research on ART (OPERA), Perinatal HIV Research Unit ; Morocco Antiretroviral Treatment 14 Cohort, Centre Hospitalier Universitaire ; MTCT-Plus Initiative, International Center for AIDS Care and Treatment Programs, Mailman School of Public Health, Columbia University, New York, USA; Prospective Evaluation in the Use and Monitoring of Antiretrovirals in Argentina (PUMA), Buenos Aires, Argentina; South Brazil HIV Cohort (SOBRHIV), Hospital de Clinicas ; Rio de Janeiro HIV Cohort, Hospital Universitario Clementino Fraga Filho ; Y R Gaitonde Centre for AIDS Research and Education (YRG) Care Cohort ; HIV-NAT, Thai Red Cross AIDS Research Centre .The ART-LINC collaboration of the International epidemiological Databases to Evaluate AIDS (IeDEA) is funded by the US National Institutes of Health  and the French Agence Nationale de Recherches sur le Sida et les hépatites virales (ANRS – grants 12101 and 12138). The IeDEA network is now funded through collaborative agreements by the National Cancer Institute (NCI), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute of Allergy And Infectious Diseases (NIAID).The ART-LINC of IeDEA Collaboration was funded by the United States National Institute of Health (NIH - Office of AIDS Research) together with the French Eric Balestre, Martin Brinkhof, François Dabis , Matthias Egger , Claire Graber, Beatrice Fatzer, Olivia Keiser, Charlotte Lewden, Mar Pujades, Mauro Schechter .The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/12/147/prepub


In 2001, Cuba launched a national ARV access program to provide ARV therapy free of cost. The first-line therapy combinations are composed of two nucleoside reverse transcriptase (RT) inhibitors (NRTIs) (AZT+3TC or d4T+3TC) associated with a non-nucleoside RT inhibitor (NNRTI) (NVP or EFV) or a protease inhibitor (PI) (IDV).To identify resistance mutations in HIV-1 isolated obtained from Cuban treated patients presenting clinical and/or immunological failure.Plasma samples from 84 HIV-1 infected patients were collected from June to November 2009 at the Tropical Medicine Institute from Havana City. Viral RNA fragments corresponding to the PR and RT region were amplified, sequenced and sub typed. Drug resistance was interpreted according to http//hivdb.stanford.edu.The most frequently found subtypes and recombinants were: B (40.4%), D , C (9.5%) and CRF18_cpx (8.3%). The PI mutations, I54VML, M46IL and L90MVL were found in 61.7, 57.4 and 53.1% of cases, respectively. Whereas for RTI, primary mutations at positions M184V, T215Y, D67N, Y181C and K103N were present in 98.6, 67.1, 43.8, 47.5 and 40.9% of subjects, respectively. A high level resistance to antiretroviral drug was observed . Full class resistance (NRTI/NRTI/PI) was found in 22 patients (26.1%), who presented history of several changes of treatment .The present study reveals a high rate of resistance compared with other international reports suggesting that alternative strategies for initial therapy and lab monitoring should be considered. These findings also warrant the study of antiviral resistance in therapy-naïve patients.


In developing nations, the use of operational parameters (OPs) in the prediction of clinical care represents a missed opportunity to enhance the care process. We modeled the impact of multiple measurements of antiretroviral treatment (ART) adherence on antiretroviral treatment outcomes in Peru.Retrospective cohort study including ART naïve, non-pregnant, adults initiating therapy at Hospital Nacional Cayetano Heredia, Lima-Peru (2006-2010). Three OPs were defined: 1) Medication possession ratio (MPR): days with antiretrovirals dispensed/days on first-line therapy; 2) Laboratory monitory constancy (LMC): proportion of 6 months intervals with ≥1 viral load or CD4 reported; 3) Clinic visit constancy (CVC): proportion of 6 months intervals with ≥1 clinic visit.Three multi-variable Cox proportional hazard (PH) models (one per OP) were fit for (1) time of first-line ART persistence and (2) time to second-line virologic failure. All models were adjusted for socio-demographic, clinical and laboratory variables.856 patients were included in first-line persistence analyses, median age was 35.6 years [29.4-42.9] and most were male . In multivariable PH models, MPR  and LMC  were associated with prolonged time on first-line therapies.Among 79 individuals included in time to second-line virologic failure analyses, MPR was the only OP independently associated with prolonged time to second-line virologic failure .The capture and utilization of program level parameters such as MPR can provide valuable insight into patient-level treatment outcomes. HIV treatment programs have been established throughout the developing world resulting in rapid expansion of the number of individuals receiving therapy and significant decrements in HIV related morbidity and mortality . PresentIn the last decade, several operational parameters (OPs) such as medication possession ratio (MPR), laboratory monitoring constancy (LMC) and clinic visit constancy (CVC) have emerged as objective methods of measuring retention in HIV care and have been shown to be good predictors of important clinical outcomes including HIV drug resistance ,6,7, virAll patients enrolled in the Hospital Nacional Cayetano Heredia (HNCH) HIV cohort sign an informed consent allowing the use of their data in clinical research. We used de-identified data previously recorded in the HNCH HIV cohort; as such patients were not contacted for this particular study. Institutional review boards at HNCH and the University of Alabama at Birmingham (UAB) approved this study.The HNCH is part of the Peruvian National HIV program and includes a cohort of over 1600 patients receiving HIV/AIDS care. This prospective cohort collects detailed socio-demographic, psychosocial, and clinical information on all patients enrolled in care. All HIV care is provided on-site, and is coordinated by a team of infectious disease specialists. For patients prescribed ART during the observation period from January 2006 through December 2010 (CD4<200 cells/ml or symptomatic), patients are scheduled for visits in three concurrent facets of the system: medication pick-up, laboratory appointments and clinic visits. Medications are dispensed free of charge, directly to patients by a team of nurses. Initially, however, a 1-week supply of ART supply is dispensed for the first 2 weeks of therapy and monthly supplies are dispensed thereafter if there are no complications. Patients are scheduled for separate laboratory monitoring  visits every six months (HIV genotyping is not routinely obtained). Patients also attend clinic visits for evaluation by an infectious disease provider at least once every six months. Both laboratory testing and clinic visit frequency take place as recommended by the Peruvian Ministry of Health guidelines . Due to All treatment-naive patients 18 years or older and initiating ART between January 2, 2006 and December 30, 2010 were included. Treatment initiation was defined as the start of a first-line regimen (2 nucleoside reverse transcriptase inhibitors (NRTI) and 1 non nucleoside reverse transcriptase inhibitor (NNRTI))  and contPatients who discontinue ART during the first two weeks primarily do so for adverse side effects and were excluded from the analysis. Also excluded were pregnant women , patients whose initial regimens included a protease inhibitor  and patients purchasing their medications privately .2. Socio-economic variables included travel distance from home district to hospital , and income   and categorical variables are reported as frequencies and percentages. Univariate analyses (UV) were performed to identify factors affecting initial regimen longevity and time to second-line regimen failure. Next, three multi-variable proportional hazard (PH) models (one per each OP) were fit for each of our study outcomes:1Time to second-line ART initiation;2Time to virologic failure of second-line ART.Each model was adjusted for socio-demographic, clinical and laboratory variables. OPs were treated as time-varying covariates for first-line persistence assessments but fixed for second-line regimen time to virologic failure. We carried out sensitivity analyses using MPR as a continuous and as a categorical variable (using 85% as the cut off), both were time-varying measures over the preceding 180 days; thus, Hazard Ratios (HR) for these two analyses can be interpreted at any given time during the first-line period (≥180 days). Analyses were performed using SAS V9.1.3 software .From January 2006 to December 2009; 965 patients started initial ART at HNCH in Lima Peru; 109 individuals did not meet study entry criteria  and 856 We included 856 patients in first-line regimen persistence analyses. Among these, age was 35.6 years [interquartile range (IQR) 29.4-42.9]; most were male  and baseline CD4 was 95 cells/ml (IQR 42-200) . In UV aFor first-line regimen persistence we fit three multivariable proportional hazard models, one for each OP . The firIn the second model, fit for LMC, only this OP  was associated with prolonged first-line regimen persistence while other demographic, clinical and laboratory characteristics were not associated with increased first-line longevity in this model. In the third model, CVC showed a trend towards longer first-line regimens  but failed to reach statistical significance. No other demographic, clinical or laboratory variables in this model were associated with this outcome.We included 79 individuals switching to a PI including regimen in the analyses of factors associated with second-line regimens virologic failure (See We again fit three separate multivariable Cox PH models, one including each OP . In the In our study, MPR measured during first-line regimens, predicted prolonged persistence of these regimens and its prognostic value endured beyond first-line therapy and was associated with time to virologic failure of second-line regimens. Laboratory monitoring constancy predicted first-line persistence but showed no association with time to second-line regimens virologic failure while CVC was not associated with either study outcome. Data collection for OPs was feasible in Peru in the context of routine care provision. The use of such OPs, in particular MPR, could be helpful to treatment programs in developing nations providing tools to identify patients at higher risk of needing a switch to more expensive second-line regimens and help identify those individuals subsequently at risk of failing those regimens. Such early warning data can be used to target resource allocation to high-risk individuals who are at need for additional interventions to ensure treatment success.Medication possession ratio has been associated with a broad range of clinical outcomes such as virologic and immunologic treatment response , mortaliLaboratory monitoring constancy is an underutilized tool for measuring adherence to care ,21. ThisClinic visit constancy has mainly been studied in the developed world ,22, haviSeveral patient characteristics have been associated with decreased regimen persistence in the extant literature ,16-18, aOur findings should be interpreted in the context of our limitations. We report the experience of one center in Peru and our findings may not be generalizable to other settings. Our sample size could have prevented us from detecting existing associations a larger dataset would be able to. Unmeasured patient, treatment and administrative factors may affect persistence on a first-line regimen. Lastly, we measured second-line virologic failure at 90 days rather than the more commonly used 180 days. As with all observational studies, we are able to identify associations but could not attribute causality, and unmeasured confounding may have affected our findings.Despite our limitations, our study advances the knowledge of HIV regimen persistence in several ways. We demonstrated the feasibility of constructing OPs with data currently available in a RLS and we present a head to head comparison among three OPs regarding their predictive value of initial ART regimen persistence.In conclusion, OPs such as MPR were associated with first-line regimen persistence and time to second-line regimen virologic failure in Peru. We propose that the use of operational parameters derived from routinely captured programmatic data hold the potential for enhancing patient care by detecting individuals at risk for abbreviated first or second-line regimen persistency. While the nature of interventions to categorize and intervene in at risk patients will need to be tailored to different populations and environments, the tactical use of data captured routinely for programmatic reporting purposes can favorably impact individual care.


Antiviral pre-exposure prophylaxis (PrEP) through daily drug administration can protect healthy individuals from HIV-1 infection. While PrEP was recently approved by the FDA, the potential long-term consequences of PrEP implementation remain entirely unclear. The aim of this study is to predict the efficacy of different prophylactic strategies with the pro-drug tenofovir-disoproxil-fumarate (TDF) and to assess the sensitivity towards timing- and mode of TDF administration (daily- vs. single dose), adherence and the number of transmitted viruses. We developed a pharmacokinetic model for TDF and its active anabolite tenofovir-diphosphate (TFV-DP) and validated it with data from 4 different trials, including 4 distinct dosing regimes. Pharmacokinetics were coupled to an HIV model and viral decay following TDF mono-therapy was predicted, consistent with available data. Subsequently, a stochastic approach was used to estimate the % infections prevented by (i) daily TDF-based PrEP, (ii) one week TDF started either shortly before, or -after viral exposure and (iii) a single dose oral TDF before viral challenge (sd-PrEP). Analytical solutions were derived to assess the relation between intracellular TFV-DP concentrations and prophylactic efficacy. The predicted efficacy of TDF was limited by a slow accumulation of active compound (TFV-DP) and variable TFV-DP half-life and decreased with increasing numbers of transmitted viruses. Once daily TDF-based PrEP yielded  Tenofovir disoproxil fumerate (TDF) is an antiviral pro-drug, belonging to the class of nucleoside reverse transcriptase inhibitors (NRTIs) used for the treatment of the human immunodeficiency virus 1 (HIV-1) in silico model exists to the authors’ knowledge, which integrates dosing, pharmacokinetics and antiviral response.While most studies characterize the pharmacokinetics of TFV in the blood plasma e.g. While TDF is an important drug for HIV treatment, it is also being evaluated as a core component of pre-exposure prophylaxis regimens (PrEP) to prevent HIV infection in silico model that consistently predicts intracellular TFV-DP pharmacokinetics based on different TDF dosing schemes. Subsequently, we use previously published direct pharmacodynamic models to ultimately link the pharmacokinetics of oral TDF to its clinical response. Once this link is established, we use stochastic simulation to predict the relative infection risk, when TDF-based PrEP or mixed PrEP/PEP strategies are applied with different levels of adherence and timing of TDF administration and we point out factors that may impair TDF-based PrEP. In view of the recent approval of truvada (300 mg TDF + 200 mg emitricitabine (FTC)) for PrEP by the FDA, this may raise awareness, encourage experimental assessment and help to avoid the misuse of TDF-based PrEP.The goal of the present study is to provide an TFV concentrations in blood plasma following either doses of 75, 150, 300 or 600 mg oral TDF were taken from three independent clinical trials We assessed different pharmacokinetic models for TFV in plasma after 75-, 150- 300- and 600 mg dosing in line with available trial data The pharmacokinetic model building process was guided by goodness-of-fit and comparative model assessment in terms of Akaike information. Pharmacokinetic parameters were estimated by minimizing the weighted residual sum of squared errors Based on predictive performance and Akaike information (see Table 3) we found that two compartments (plus a dosing compartment) best described TFV plasma pharmacokinetics, in line with previous studies ics  see , which bics  see . The finThe ordinary differential equations for the final model are displayed below:ents see . The conIn order to predict (i) viral load kinetics following TDF treatment in HIV-infected patients and (ii) the infection probability for uninfected individuals, we adopted the virus dynamics model from prior to proviral genomic integration  can be regarded by an inhibition of the rate of successful cell infection Although per-contact infection probabilities have previously been estimated for different routes of HIV transmission In the simulations, infection was irreversible by the time that the predicted number of viruses exceeded 1 million particles . Therefore, we recorded an infection event during our simulations, whenever the viral population crossed this threshold in a previously uninfected ‘virtual patient’ at risk. The percentage infections prevented, when TDF is taken prophylactically was then calculated using the following formula:During strategy a)  adherence was implemented using a “roulette-wheel selection” technique: A uniformly distributed random number Modeling the infection probability requires to regard the intrinsic stochasticity and discreteness of the infection event: Either the transmitted virus becomes entirely cleared by the immune system before establishing stable infection, or the infection expands and disseminates throughout the body Predicted concentration-time profiles of TFV after 75-, 150-, 300- and 600 mg once daily dosing of TDF using the final pharmacokinetic model (eqs. (3)-(6)) are shown in The predicted concentration time profile of TFV-DP after a single dose of 300 mg oral TDF is shown in The accumulation of intracellular TFV-DP in the case of daily 300 mg oral TDF is shown in Methods section) and subsequently predicted the 56 days viral dynamics in asymptomatically HIV infected individuals following a 28 days mono-therapy (day 0–28) with either 75-, 150-, 300- and 600 mg TDF. Our predictions are shown in For further model evaluation and estimation of the remaining parameters The predicted percent infections prevented by continuous once daily 300 mg TDF PrEP are shown in ence see . The inoIn summary, the protective effect of TDF appears to be much less sensitive to poor adherence (as long as adherence is above 40%), but is dependent on the actual mode of transmission, i.e. how many viruses become transmitted. Notably, in a substudy of Partners PrEP (serodiscordant couples in Kenya/Uganda) using TDF only, an overall efficacy of 62%  was reported, which corresponds to our predictions for the case when small numbers of viruses become transmitted . The results see  indicateA recent investigation showed that 28 days of a post-exposure prophylactic triple drug regimen containing TDF We tested the efficacy of single dose 300- and 600 mg oral TDF given either 1, 6, 12, 24 or 48 h before viral exposure in 01 level , S6. Des01 level  dosing e01 level  to reachWe also tested whether the effect of single dose TDF PrEP could be potentiated, if the standard dose was doubled see . The proWe have derived an analytical formula in vely see .The plasma pharmacokinetics of TFV were best described by a two compartment model ⋅TU+βM(t)⋅MU. For the parameters used pharmacologically, single dose PrEP drugs taken shortly before potential viral exposure are required to accumulate rapidly in target cells, but may not have to persist for more than 3 days, in line with the pharmacological attributes of most NNRTIs.Based on the model parameters, the duration of action required to ensure that virus particles are eliminated with e.g. 99% probability, In contrast to our predictions , some noIt is not precisely known how much virus is being transmitted from an infected to an uninfected individual during e.g. sexual contact. Moreover, it is not known how many transmitted viruses actually reach a target cellular environment that allows their reproduction, and what types of cells are relevant for the initial infection. Also, the number of transmitted viruses, the availability of target cells and the subset of viruses that reach a cellular environment that facilitates their reproduction may be altered by the circumstances of HIV-1 transmission and several unknown co-factors. While the earliest stages of mucosal transmission of HIV-1 have not been directly observed in human and are not fully understood, animal experiments suggest that CD4Our predictions revealed that the prophylactic efficacy of TDF decreases with an increasing number of inoculated viruses see , making While it has recently been suggested to combine antiviral strategies for HIV-1 prevention The developed model is based on several assumptions, which we outline in the following:relevant to HIV-1 infection or only in those not relevant to infection. Human studies, which analyze TFV-DP levels in purified CD4We used intracellular TFV-DP concentrations in PBMCs as a marker of efficacy. PBMCs are surrogate markers, which consist of different cell types of which the majority, however, is susceptible to HIV-1 infection Recent work suggests that the efficacy of NRTIs like TDF is affected by the levels of endogenous competing nucleotides dNTP  in silico in the future.Vaginal TFV gel has been used successfully to prevent heterosexual HIV-1 infection In the absence of data elucidating the levels of TFV-DP in uninfected individuals, we assumed that TFV-DP levels in PBMCs from infected individuals vs. uninfected individuals are similar. Since TFV pharmacokinetics (parent compound) have been reported to be similar in healthy- and HIV-infected individuals It has recently been reported that TFV may become phosphorylated within red blood cells (RBCs) In individuals with established infection, the rates of viral elimination day] see , which rThe presented modeling approach may be extended to e.g. assess the consequences of TDF-based PrEP intervention on drug resistance emergence, or TDF-based PrEP efficacy in the case when resistant virus becomes transmitted. Also, the combined effects of emtricitabine (FTC) and TDF remain to be elucidated, but can be studied by extending the presented model with the pharmacokinetics of FTC, once data on intracellular FTC-triphosphate becomes available.Table S1Assessment of alternative models for plasma TFV pharmacokinetics. Goodness-of-fit in terms of the weighted residual sum of squared errors (WRSE) of model predicted vs. experimental data following either doses of 75, 150, 300 or 600 mg oral TDF from three independent clinical trials (PDF)Click here for additional data file.Table S2Predicted individual TFV-DP elimination kinetics. Estimated individual plateau concentrations (PDF)Click here for additional data file.Table S3Contingency table for infection events during once daily PrEP with 300 mg TDF. Predictions are based on 2000 ‘virtual patients’ simulations respectively. The first number in the brackets in columns 2–6 indicates the number of ‘virtual patients’ that remained uninfected after viral challenge, whereas the second number indicates the number of patients that became infected. For example, when 20% of once daily 300 mg TDF pills are ingested and patients are challenged with inoculum size one (one virus reaches a target cell environment), 1927 ‘virtual patients’ remain uninfected, whereas 73 became infected.(PDF)Click here for additional data file.Table S4Contingency table of infection events for one week of TDF-based PrEP with 300 mg started around the time of exposure (1w-PrEP/PEP). Predictions are based on 2000 ‘virtual patients’ simulations respectively. The first number in the brackets in columns 2–6 indicates the number of ‘virtual patients’ that remained uninfected after viral challenge, whereas the second number indicates the number of patients that became infected. For example, when 300 mg TDF is taken 6 hours before viral challenge, continued for one week and patients are challenged with inoculum size one (one virus reaches a target cell environment), 1866 ‘virtual patients’ remain uninfected, whereas 134 became infected.(PDF)Click here for additional data file.Table S5Contingency table of infection events for a single oral TDF dose 300 mg (sd-PrEP). Predictions are based on 2000 ‘virtual patients’ simulations respectively. The first number in the brackets in columns 2–6 indicates the number of ‘virtual patients’ that remained uninfected after viral challenge, whereas the second number indicates the number of patients that became infected. For example, when 300 mg TDF are taken 1 hour before viral challenge and patients are challenged with inoculum size one (one virus reaches a target cell environment), 1818 virtual patients remain uninfected, whereas 182 became infected.(PDF)Click here for additional data file.Table S6Contingency table of infection events for a single oral TDF dose 600mg (sd-PrEP). Predictions are based on 2000 ‘virtual patients’ simulations respectively. The first number in the brackets in columns 2–6 indicates the number of ‘virtual patients’ that remained uninfected after viral challenge, whereas the second number indicates the number of patients that became infected. For example, when 600mg TDF are taken 1hour before viral challenge and patients are challenged with inoculum size one (one virus reaches a target cell environment), 1839 virtual patients remain uninfected, whereas 161 became infected. (PDF)Click here for additional data file.Table S7Statistical test of difference of prophylactic efficacy between 300 mg sd-PrEP and 600 mg sd-PrEP with TDF. The distinct fields show the p-value for a (PDF)Click here for additional data file.Text S1The supplementary text contains the derivation of the model for intracellular TFV-DP uptake and anabolism as well as a model evaluation.(PDF)Click here for additional data file.Text S2The supplementary text contains the derivation of an approximate analytical formula for the computation of the probability of infection with distinct virus inoculum sizes in relation to the concentration of TFV-DP present.(PDF)Click here for additional data file.


Updated World Health Organization guidelines have amplified debate about how resource constraints should impact monitoring strategies for HIV-infected persons on combination antiretroviral therapy (cART). We estimated the incremental benefit and cost effectiveness of alternative monitoring strategies for east Africans with known HIV infection.3 rather than 200 cells/mm3).Using a validated HIV computer simulation based on resource-limited data (USAID and AMPATH) and circumstances (east Africa), we compared alternative monitoring strategies for HIV-infected persons newly started on cART. We evaluated clinical, immunologic and virologic monitoring strategies, including combinations and conditional logic . We calculated incremental cost-effectiveness ratios (ICER) in units of cost per quality-adjusted life year (QALY), using a societal perspective and a lifetime horizon. Costs were measured in 2008 US dollars, and costs and benefits were discounted at 3%. We compared the ICER of monitoring strategies with those of other resource-constrained decisions, in particular earlier cART initiation . Monitoring strategies employing routine virologic testing alone only maximized health benefits at willingness-to-pay levels (> $4400/QALY) that greatly exceeded the ICER of earlier cART initiation.CD4 testing alone never maximized health benefits regardless of resource limitations. Programmes routinely performing virologic testing but deferring cART initiation may increase health benefits by reallocating monitoring resources towards earlier cART initiation. Considerable debate exists about how resource constraints should impact laboratory monitoring for HIV-infected patients on combination antiretroviral therapy (cART) -6. This Published decision models have broadly suggested that laboratory monitoring delivers less favourable value than alternative resource allocations ,10,11. HWe have previously developed and validated a computer simulation model of HIV progression in resource-rich settings -15. Our We used a computer model to simulate alternative laboratory monitoring strategies for HIV-infected patients on cART in east Africa, and to compare the value of these strategies with alternative resource allocation options, such as earlier cART initiation. This model has been previously validated by demonstrating its ability to predict clinical data describing survival, time until cART failure, and accumulation of resistance mutations in distinct observational cohorts -15.This simulation has been revised: 1) to allow specification of a wide variety of possible monitoring strategies; (2) to allow calibration using data from resource-limited settings; and (3) to consider a specifiable number of cART regimens or a specifiable number of drugs within each cART category . The simulation is a stochastic, second-order Monte Carlo progression model that explicitly represents the two main determinates of treatment failure: accumulation of genotypic resistance and cART non-adherence and/or intolerance  of each monitoring strategy. ICERs measure the additive benefit of each strategy compared with its next best alternative, and interpret this benefit together with its additive cost. The ICER compares different choices in a systematic, quantitative manner, placing them "on a level playing field", and providing a widely used quantitative measure of value. Higher ICERs  are less favourable, corresponding to lower value. Lower ICERs  are more favourable, corresponding to higher value. ICERs are useful for informing resource allocation decisions because reallocating resources from a numerically higher (less favourable) ICER towards a numerically lower (more favourable) ICER can increase health benefits without requiring additional resources. We performed all analyses from a societal perspective using a lifetime time horizon. All costs and benefits were measured in US dollar (USD) values for 2008 and were discounted at an annual rate of 3%. In all cases, we followed recommendations of the US Panel on Cost-Effectiveness in Health . We simu3 versus 200 cells/mm3, and whether to make second- and third-line cART regimens routinely available).Considerable debate exists over acceptable value "thresholds" and their appropriate variation with resource constraints . To aid We compared the downstream effects of alternative monitoring strategies on HIV-positive patients newly started on cART. In accord with the USAID-AMPATH experience, we assumed that the first cART regimen was nevirapine in combination with two nucleoside reverse transcriptase inhibitors. Distributions of age, sex and CD4 count at cART initiation were based on characteristics of patients enrolled in USAID-AMPATH Table . We did We evaluated a matrix of different monitoring strategies: type of monitoring ; viral load threshold for switching ; and frequency of monitoring . Clinical monitoring was defined as evaluation by a health professional for signs and symptoms of AIDS . We deliBecause space limitations preclude the presentation of the numerous strategies that we evaluated, we focus on results from the subset of strategies on the efficient frontier. We first identified efficient frontiers for scenarios with two and three available cART regimens. We then identified the efficient frontier for a scenario that does not specify a fixed number of cART regimens, but rather allows the number of available cART regimens to vary.We estimated outcomes of life years, quality-adjusted life years (QALY), and costs (USD). QALYs are a preference-weighted metric that incorporate both quantity and quality of life, and reflect the idea that a year of poor-quality life is valued less than a year of high-quality life .Because some strategies may be sufficiently close to an efficient frontier that their exclusion is solely due to statistical uncertainty (from random variation in the model), we performed sensitivity analyses in which the cost and effectiveness estimates for each strategy were varied over their 95% interpercentile range. In separate sensitivity analyses, to assess the impact of biased inputs, we varied all inputs to the model across their plausible ranges, seeking to identify whether changes in model input assumptions would lead to different strategies on the efficient frontier.3, and we sought to identify strategies on the "efficient frontier" . Monitoring strategies lying outside this "efficient frontier" cannot deliver the greatest benefit regardless of willingness to pay, and therefore should not be preferred choices.We evaluated alternative monitoring strategies: first for a treatment scenario with two available cART regimens, and then a treatment scenario with three available cART regimens. In addition, we considered a scenario that does not specify a fixed number of cART regimens, but rather allows their number to vary. For all scenarios, we assumed that cART would be started at a CD4 count of 200 cells/mmWhen we explored a scenario in which two cART regimens were available Table , no labo3 rather than 350 cells/mm3, the efficient frontier was mostly comprised of monitoring strategies that were structured conditionally, in which CD4 was obtained routinely and a follow-up viral load was only obtained if the CD4 count met WHO criteria for immunologic failure. Conservative monitoring frequencies (12 or six months rather than three months) and switching thresholds  were preferred. In sensitivity analyses, only one strategy employing routine CD4 monitoring alone (every 12 months) was close to the efficient frontier.When willingness to pay remained limited to initiating cART at a CD4 count of 200 cells/mm3 rather than 200 cells/mm3, the efficient frontier continued to be mostly comprised of monitoring strategies that were structured conditionally; however, these strategies now employed less conservative monitoring frequencies and switching thresholds. Only one strategy employing routine CD4 monitoring alone (every six months) was close to the efficient frontier.As willingness to pay rose beyond initiating cART at a CD4 count of 350 cells/mmAs willingness to pay greatly exceeded the value of earlier cART initiation, the efficient frontier became comprised of monitoring strategies that used routine viral load monitoring, with progressively greater frequencies and less conservative switching thresholds.3 rather than 200 cells/mm3 (ICER $2600/QALY), the efficient frontier was comprised of monitoring strategies that were structured conditionally, where CD4 was obtained routinely and a follow-up viral load was only obtained if the CD4 count met WHO immunologic criteria. As willingness to pay greatly exceeded the value of earlier cART initiation, the efficient frontier was comprised of monitoring strategies that used routine viral load monitoring. In sensitivity analyses, no strategy employing routine CD4 monitoring alone was close to the efficient frontier.When we explored a scenario in which three cART regimens were available Table , strategWhen we considered a scenario that does not specify a fixed number of cART regimens, but rather allows the number of available cART regimens to vary Table , strategConditional strategies were no longer on the efficient frontier because the ICER of routinely offering multiple cART regimens (compared with providing one cART regimen only) was fairly high (ICER > $5000/QALY), and because the ICER of any laboratory testing strategy would only be favourable if multiple cART regimens were routinely offered. As willingness to pay exceeded the ICER of offering multiple cART regimens, they were also high enough to support the ICER of routine use of viral load testing.Sensitivity analyses suggested that efficient frontiers were robust to alternative assumptions ".Second, routine viral load testing alone is only a preferred strategy at levels of willingness to pay that far exceed those of earlier cART initiation. In other words, our results suggest that a programme routinely monitoring viral loads, but starting cART at a CD4 of 200 cells/mmThird, when monitoring includes viral load in resource-limited settings, the switching threshold conferring the greatest value is more likely to be 10,000 copies/mL than lower thresholds, and raises the question of whether the recent change in threshold advocated by WHO  is a step in the right direction, especially when the downstream cost burdens of switching first-line regimens to far more expensive, second-line regimens might make it more difficult to simultaneously adhere to other costly changes in its recommendations.Fourth, if programmes are considering alternative monitoring strategies at the same time that they are weighing how many cART regimen options to offer, our results suggest that they can save more high-quality years of life by routinely offering fewer regimens with less intense monitoring strategies, and by reallocating saved resources on earlier initiation of cART.Fifth, the bulk of expenditures from routine viral load testing did not arise from the cost of the viral load test itself, but rather originated from the downstream costs of more frequent switches to expensive second- and third-line regimens. When later cART regimens were assumed to be no more expensive than first-line cART regimens, monitoring strategies that involved routine viral load testing became more favourable. These results suggest that even if viral load tests become cheaper, they may not offer favourable value if there is no change in the relative pricing of different regimens. In contrast, if later cART regimens become less expensive relative to first-line regimens, viral load tests may offer favourable value even if the tests themselves remain expensive.Our estimates for the ICER of cART ($600/QALY) were very similar to other published analyses  ,11. LikeOur analyses have notable limitations. Our simulation is not a transmission model, and therefore does not consider how more conservative monitoring strategies might lead to: (1) delayed detection of antiretroviral resistance and its spread; and 2) higher viral loads in treated patients, which have been associated with increased transmission rates. However, this consideration is unlikely to alter inferences for decision making because the increase in resistance accumulation is likely to be modest (less than one resistance mutation over a five-year period)  because people who are treated earlier will have low viral loads for a longer portion of the time they are infected. In addition, while the simulation is sufficiently detailed to represent clinical differences among subtypes of nucleoside reverse transcriptase inhibitors , it is not sufficiently detailed to represent clinical differences among individual drugs within each subtype .A distinctive strength of our work is that we evaluated a broad matrix of monitoring options, including some strategies that are not guideline recommended at the current time, but which might seem like plausible alternatives to some decision makers . Indeed, the ability to simultaneously evaluate a broad range of monitoring options beyond those currently employed is one of the key methodological strengths of using mathematical modelling in general, and of the current report in particular.In conclusion, our computer simulation suggests that shifting resources away from routine laboratory monitoring and toward earlier initiation of cART has the potential to increase the number of lives saved with HIV treatment in a resource-constrained environment.This work is supported by National Institute of Allergy and Infectious Disease Award UO1AI069911-01 (IeDEA East Africa), US National Institutes of Health. MCB is employed by the US NIH, which provided funding for this study through a grant. The study sponsor had no role in the study design, interpretation of data, the writing of the paper, or the decision to submit the paper for publication.The authors declare that they have no competing interests.RSB designed the study concept. RSB and KN developed the model and KN programmed the model. LD, CTY, BM, SK, MCB and KWK acquired and/or interpreted the data. RSB analyzed results and wrote the manuscript. RSB, CTY, LD, MCB and KWK revised the manuscript. All authors read and approved the final manuscript.Appendix. The Appendix describes in detail the methods underlying the revision of the model and its calibration. The Appendix figures show results of model calibration and results of sensitivity analyses [analyses -29.Click here for file


When to initiate antiretroviral therapy in HIV infected patients is a diffcult clinical decision. Actually, it is still a matter of discussion whether early highly active antiretroviral therapy (HAART) during primary HIV infection may influence the dynamics of the viral rebound, in case of therapy interruption, and overall the main disease course.In this article we use a computational model and clinical data to identify the role of HAART timing on the residual capability to control HIV rebound after treatment suspension. Analyses of clinical data from three groups of patients initiating HAART respectively before seroconversion (very early), during the acute phase (early) and in the chronic phase (late), evidence differences arising from the very early events of the viral infection.The computational model allows a fine grain assessment of the impact of HAART timing on the disease outcome, from acute to chronic HIV-1 infection. Both patients' data and computer simulations reveal that HAART timing may indeed affect the HIV control capability after treatment discontinuation. In particular, we find a median time to viral rebound that is significantly longer in very early than in late patients.A timing threshold is identified, corresponding to approximately three weeks post-infection, after which the capability to control HIV replication is lost. Conversely, HAART initiation occurring within three weeks from the infection could allow to preserve a significant control capability. This time could be related to the global triggering of uncontrolled immune activation, affecting residual immune competence preservation and HIV reservoir establishment. Around the time of peak viremia, patients may become symptomatic and reservoirs of latent virus are established [The question of when antiretroviral therapy has to be initiated remains a challenging issue. Recent studies show that the early immune response to HIV-1 infection is likely to be an important factor in determining the clinical course of disease [ablished .+ T cell destruction and the establishment of viral reservoirs, seems to be a narrow but crucial period in which an antiretroviral therapy can control viral replication, prevent an extensive CD4+ T cell depletion from occurring and curb generalized immune activation. Thus, thwarting HIV replication by introducing HAART in the early phases of infection could have a substantial impact on the whole disease course. In particular, suggested factors that may contribute to the observed better viral control after treatment interruption in very early treated patients are [i) early arrest of viral escape, leaving the virus vulnerable; ii) preservation or even enhancement of the immune response resulting from the early clearing of antigen; iii) prevention of the establishment of a pool of HIV-specific memory CD4 T cells thus leaving fewer target cells available for viral infection.The "window of opportunity" between the infection and peaking of viremia, prior to massive CD4ents are : i) earlAn ideal clinical model aimed at addressing such issue should compare a number of patients treated starting on different times: from very early to very late. Besides the ethical issues, it is rather difficult to collect enough patients to significantly represent the whole spectrum of possible HAART initiation timings. As a matter of fact, a practical clinical model would compare very early to late-treated patients. While informative on the overall role of HAART timing on disease course, this approach would not allow to verify if there are events in the early infection influenced by the starting time of HAART that affect directly and decisively the course of the disease.We have already shown in -6 that ain silico model identifies a significant three-week time threshold as the "ultimate" time point beyond which the decisive HIV-induced damages already occurred, affecting the whole disease course.The aim of the present work is to verify the effect of HAART timing on subsequent events. Indeed, both a clinical model and a computational simulation show that a late initiation of treatment affects HIV-1 replication control. Interestingly, the early phase) and performed computer simulations to predict the differences in viral rebound at therapy interruption between those patients and subjects initiating therapy during the chronic phase . Our conclusion was that early initiation of therapy does not prolong the disease-free period when compared to a treatment started during the late phase. However, other studies suggest that an earlier initiation is preferable [very early patients  against late-treated patients.In a previous work , we analeferable -9. This eferable  to get aWe analyzed the results of clinical studies performed at the Clinical Department of the National Institute for Infectious Disease "L. Spallanzani" in Rome.A first group of eleven patients  were diagnosed HIV-1 positive between year 1998 and 2006. All patients initiated HAART within 14 days from diagnosis, during the very early phase of infection  enrolled in the program between year 1998 and 2005. Patients in this group underwent HAART during the early phase of HIV-1 infection. In particular, they started HAART about 20 days after treatment diagnosis . They started HAART during the chronic phase of infection defined as suggested by the guidelines . In partml; Bayer Diagnostics, Milan, Italy) from 2001 until 2008.Plasma HIV-1 RNA levels were determined by a second-generation assay based on nucleic acid sequence based amplification (NASBA), for samples collected until 2001 and by the branched-chain DNA assay  reverse transcriptase copies the viral single stranded RNA genome into a double-stranded viral DNA. The viral DNA is then integrated into the host chromosomal DNA; 3) the virus remains at rest until an event activates the transcription; 4) the replicating virus buds from the cell membrane. Fully assembled virions are then able to infect other cells to restart the life cycle. HAAR effects are modeled as follows: Reverse transcriptase inhibitors block reverse transcriptase enzymatic functions and avoid completion of synthesis of the double-stranded viral DNA thus preventing HIV-1 from replicating ; Protease inhibitors prevent viral replication by inhibiting the activity of HIV-1 protease, an enzyme used by the virus to cleave nascent proteins for final assembly of new virions . Further details and parameter settings of the simulations can be found in the Additional file The simulated life cycle of the virus is represented by the following stages: 1) the virus infects CD4in vivo: 5.8 ± 0.2 RNA copies/ml , 870 ± 50 CD4 cells/μl and 430 ± 50 CD8 cells/μl. For all simulations we applied a one-year course of HAART. Further details on the tuning of the simulation parameters can be found in the Additional file For what concerns the setting of the parameters related to the therapy, we performed computer simulations in which we fixed the immunological parameters at the time of therapy initiation on the basis of the average values measured in patients We analyze virological data from HIV patients treated during the very early, early and late phase of infection and compare them with computer simulations.In Figure In the present work we extend the simulations of  to incluFigure st) on the viral rebound. The corresponding results are shown in Figure one week after therapy interruption as a function of s tis presented. We observe that there are two regimens, one for s t< 20 days and one for s t> 30 corresponding to what clinicians call respectively best controllers (with undetectable HIV RNA levels) and rebounders .In order to provide a more precise estimate of the time "limit" beyond which the benefit of an early initiation of therapy vanishes, we use the simulation to investigate the influence of HAART initiation time  but with a greater a, a smaller d and a greater V (st) is (a + k)/2 may lead to the deceiving conclusion that there is no window of opportunity because the viral rebound is independent from st.where the parameter s t>With respect to Figure Recent analysis  of sampWith respect to the study conducted by clinical data analysis and computer simulation described so far, we identify three regimens, as highlighted in Figure These considerations are summarized in Figure A number of studies indicate that interfering with HIV replication by starting the therapy in the early phases of the infection could have a deep impact on the whole disease course. However, HAART is costly, it is onerous for both patient and health care provider, and often brings adverse effects. Its clinical benefit must therefore be weighed against its burden.in silico patients: those who initiate HAART very early and those who start it lately. We evaluated the model comparing the results to clinical data. We found that an opportunity time-window exists for the initiation of HAART , in which the therapy can control viral replication, preventing generalized immune activation and extensive CD4+ T cell depletion.In the present study, we resorted to a computer model to study the dynamics of the plasma viral load after prolonged treatment interruption in two groups of An educational version of the immune system simulator is available on our website:- Name: C-ImmSimhttp://www.iac.rm.cnr.it/~filippo/C-ImmSim.html- Home page: - Operating system(s): Linux, Unix Mac OS X, Windows- Programming language: Chttp://www.iac.rm.cnr.it/~filippo/how-to-get-cimmsim_files/LicenseAgreement.pdf- Licence: C-ImmSim is available under a LICENSE AGREEMENT that needs to be signed: The authors declare that they have no competing interests.FC and PP designed and performed research; all authors wrote the paper. FM and GDO provided the clinical data. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/11/56/prepubMathematical model details. This file lists all the interactions between cells and molecules considered in the model and an accurate description of the parameter setting.Click here for fileParameters tuning for the simulation of HIV infected virtual patients. This file reports details of the parameter setting and tuning.Click here for file


The city of Sao Paulo has the highest AIDS case rate, with nearly 60% in Brazil. Despite, several studies involving molecular epidemiology, lack of data regarding a large cohort study has not been published from this city.This study aimed to describe the HIV-1 subtypes, recombinant forms and drug resistance mutations, according to subtype, with emphasis on subtype C and BC recombinants in the city of São Paulo, Brazil.pol region sequences were used in phylogenetic analyses for subtyping and identification of drug resistance mutations. The envelope gene of subtype C and BC samples was also sequenced.RNA was extracted from the plasma samples of 302 HIV-1-seropositive subjects, of which 211 were drug-naive and 82 were exposed to ART. HIV-1 partial pol gene analyses, 239 samples (79.1%) were assigned as subtype B, 23 (7.6%) were F1, 16 (5.3%) were subtype C and 24 (8%) were mosaics (3 CRF28/CRF29-like). The subtype C and BC recombinants were mainly identified in drug-naïve patients (72.7%) and the heterosexual risk exposure category (86.3%), whereas for subtype B, these values were 69.9% and 57.3%, respectively . An increasing trend of subtype C and BC recombinants was observed (p < 0.01).From partial The HIV-1 subtype C and CRFs seem to have emerged over the last few years in the city of São Paulo, principally among the heterosexual population. These findings may have an impact on preventive measures and vaccine development in Brazil. The huge genetic variability of HIV-1 results in a complex and dynamic molecular classification of types (HIV-1 and 2), groups , and the pandemic group M could be divided into subtypes  and recombinant forms, such as circulating recombinant forms (CRF) and unique recombinant forms (URF). Such HIV-1 variation has an important impact on diagnosis, viral load measurement and the performance of HIV-1 genotyping systems . Thus, HAlthough HIV-1 subtype B is the most studied, HIV-1 C predominates globally and is responsible for approximately 50% of infections . This suThe Brazilian AIDS epidemic is mainly driven by subtypes B, F1, and BF1 recombinants; however, in the Southern region, subtype C and BC recombinants can represent up to 50% of cases, depending of the geographical studied region -27. DespThe current study was conducted to determine HIV-1 genetic diversity and PI/RTI resistance associated mutations among HIV-1 infected drug naïve and HAART patients in a cohort in the city of São Paulo. Moreover, patients classified as HIV-1 subtype C and BC recombinants were analyzed in more details.The present study aimed to describe HIV-1 subtypes, CRFs and drug resistance mutations in drug-naïve and failing HAART individuals living in the city of São Paulo, in particular attention to those classified as subtype C and BC.The study population was composed by HIV-1-infected patients who have been followed-up at the Ambulatory Service of the Department of Secondary Immunodeficiency Clinic of the Clinical Hospital, University of São Paulo Medical School (HC/FMUSP), São Paulo, SP, Brazil, one of the largest teaching and research hospitals in Brazil.+T cells and HIV-1 viral load were determined using the Brazilian Ministry of Health guidelines.According to the Brazilian Ministry of Health, HIV genotyping test should be routinely performed in patients under antiretroviral therapy who present a plasma viral load over 2000 copies/mL . FollowiHIV-1 viral RNA was isolated from plasma samples using the QIAamp® Viral RNA Mini Kit  extraction method, in accordance with the manufacturer’s protocol. Complementary DNA was performed by RT-PCR protocol with random primers and using the PR/RT PCR strategy previously described by Gonzales et al. ,35. The The chromatograms of all sequenced DNA were visually using the Sequencher program version 4.0.5 (Gene Codes) and manually edited. PR/RT sequencing was conducted to detect drug resistance mutations and HIV-1 subtypes. Major antiretroviral drug resistance mutations were classified according to Stanford University online HIV Drug Resistance Database, . The Int7 generations, with a burn-in of 4x106 generations. Convergence of parameters was assessed by calculating the effective sample size (ESS) using TRACER v1.4 (http://beast.bio.ed.ac.uk/Tracer./) excluding an initial 10% for each run. All parameter estimates for each run showed an ESS values >100. A final Bayesian majority-rule consensus tree was obtained for the data set. The SplitsTree program version 4 [Nucleotide sequences were aligned using the Clustal X program  and lateersion 4  was usedersion 4  using grersion 4  based onenv region was performed as previously described for the PR/RT region (data not shown).The envelope gene was also sequenced when subtype C and BC PR/RT sequences were identified. A fragment of 0.6 kb of the envelope region of the HIV-1 was amplified by nested-PCR primers LB1 (TAGAATGTACACATGGAATT)/, LB2 (GCCCATAGTGCTTCCTGCTGCT) as outer primers and LB3 (GCAGTCTAGCAGAAGAAGA)/, LB4 (CTTCTCCAATTGTCCCTCATA) as inner primers. The sequence analysis of the pol region: GU288708-GU288746, GU288748-GU288754, GU288756-GU288776, GU288778-GU288786, GU288788-GU288792, GU288794-GU288807, GU288809-GU288813, JN195817-JN196018 and env region: JN196019-JN196040.All the sequences generated were submitted to the GenBank database and the assigned accession numbers were: 10/mL and the CD4+T cell count was 350 cells/mm3 for naïve patients. For treated patients, 38 (46.3%) were asymptomatic, 27 (33%) were symptomatic and for 17 (20.7%), no information was obtained. The mean RNA plasma viral load was 5.0 log10/mL and the CD4+T cell count was 246 cells/mm3.A total of 302 HIV-1-infected patients were analyzed, of these, 225 (75%) were men and 77 (25%) were women, with a mean age of 36 years-old. The distribution by the exposure categories were as follows: 61% heterosexual, 23% men who have sex with men, 9% bisexual and 7% other. According to the clinical status, 153 patients (72.5%) were asymptomatic, 55 (26.1%) were symptomatic and for 3 (1.4%), no information was obtained. The mean RNA plasma viral load was 5.28 logAccording to the phylogenetic and bootscan analyses, 239 patients 79.1%) were assigned to subtype B , 23 (7.6%) were assigned to subtype F1 , 16 (5.3%) were subtype C , and 24 (8%) were recombinant forms (19 naïve and 5 treated). Among the recombinant forms, 14 were BF recombinants (11URF_BF1 and 3 CRF28/29), 1 BU, 1 FD, 2 FU and 6 BC recombinants . The Bayesian tree of the non-subtype B sequences is depicted in Figure % were asHIV-1 primary resistance mutations were detected in 42 (20%) out of 211 naive individuals, among these, 8 (3.8%) presented major PI resistance mutations, 29 (13.7%) presented NRTI resistance mutations and 27 (12.8%) presented NNRTI resistance mutations. Overall, 20% of individuals presented resistance to one antiretroviral class, 7.6% presented resistance to two classes, and 2.8% presented resistance to all three classes. HIV-1 secondary resistance mutations were investigated in 82 patients receiving HAART regimen, among these, 30 (36.6%) presented major PI resistance mutations, 51 (62.2%) NRTI resistance mutations and 42 (51.2%) NNRTI resistance mutations. Overall, 17.1% of individuals presented resistance to one antiretroviral class, 56.1% presented resistance to two classes, and 76.8% presented resistance to all three classes.Comparing the resistance levels in two distinct periods of the study, 2002–2006 and 2007–2010, the following were verified: PI resistance mutations , NRTI , NNRTI , showing an increasing trend of resistance levels, except for PI resistance mutations. Among the 82 treated patients, the following were verified: PI resistance mutations , NRTI , NNRTI , similar results to naïve patients were observed (data not shown). The major resistance mutations detected in PR and RT regions in drug naïve or HAART individuals, independent of HIV-1 subtype, were: I93L, L10I/F/V, L63P, M36I/L/V, V118I, V179D/I, as presented in Figure Secondary resistance mutations in the PR region were detected in individuals infected with subtypes B and F1 , and in the RT region . The mutations K65R, Q151M, Y115F were identified only in subtype B samples.+ T cells counts were 4.64 log10/mL and 281 cells/mm3, respectively, in naive patients, while for patients receiving HAART treatment, the means were 4.23 log10/mL and 34 cells/mm3, respectively. Among HIV-1-infected individuals in the subtype B group, 47 (19.7%) were women and 155 (64.9%) were asymptomatic . The means for viral load and CD4+ T-cells counts were 5.33 log10/mL and 349 cells/mm3, respectively, for naive patients, while for patients receiving HAART, the means were 5.02 log10/mL and 249 cells/mm3, respectively.Since very little data is available concerning subtype C individuals outside the southern region of Brazil, in the present work, this group was the focus of more specific analysis. Thus, comparisons between the 22 HIV-1 individuals classified as subtype C and BC recombinants and subtype B individuals verified that the most common transmission mode was sexual and mean age in both groups was approximately 36 years-old. Interestingly, in the subtype C and BC recombinants group, 7 (31.8%) were women and 16 (72.7%) were asymptomatic. The mean viral load and CD4An increasing trend of subtype C and BC was observed, increasing from two cases from 2003 to 2006, to 20 cases from 2007 and 2010 (p < 0.05).Sixteen out of 22 (72.7%) subtype C or BC recombinant individuals were naïve and the main mutations identified in the PR/RT region were G333A, I93L, L63P, M36I/T, V118I. Five (22.7%) were receiving treatment and the main mutations identified were I93L, L63P, M36I/T, M41L, M184V, T215F (to a lesser extent) and for 1 (4.6%) subtype C and BC individual, no information concerning treatment was available. For subtype B individuals, 167 (69.9%) were naïve patients and the main mutations identified were: D67N, K70R, G190A/S, L90M, T69A/D/N/S. Sixty six (27.6%) were receiving treatment and the main mutations identified were A98G, D30N, L74I/V, L210I/M/W, N88D, T69A/D/N/S, V90I, V106I/M, and for 6 (2.5%) individuals, no information concerning treatment was available. These mutations were verified only in the subtype B group.Only two cases (2/16) showed non-analogue nucleotide drug resistance mutation for subtype C, while four cases (4/6) showed non-analogue nucleotide drugs resistance mutation for subtype BC in naïve patients.The demographical and clinical data for subtype C and BC recombinant patients with the mutations identified in this cohort are listed in Table As expect, the HIV-1 B was the most common subtype in the cohort (79.1%) followed by subtype F1 (7.6%). A relevant presence of subtype C (5.3%) was observed and an increase in the number of mosaics (8%), of which 2% were BC recombinants. The first identified case of HIV-1 subtype C in this cohort from the city of São Paulo was from 2003, even though this cohort has been ollowed since 1989. In fact, this subtype predominates in South, where the majority of counties present the highest rates of HIV-1 infection in Brazil,  in contrThe present cohort was predominantly naive heterosexual patients for all HIV-1 subtypes. The mode of transmission for HIV-1 C was clearly associated with heterosexual contact, similar to the major source for this subtype in Africa and Asia . Thus, iRecombinations between subtypes B and C have been identified among the HIV-1 samples obtained in Southern Brazil,  and now As previously described, the prevalence of resistance associated mutations appear to differ between subtype B and others (non-B), selected mutations in codons 41, 210 and 215 are more frequent in the former, whereas mutations at codon 67, 70 and 219 are more common in subtype C . The L21The mutation V106M was previously described as occurring rapidly in subtype C virus, leading to high level of resistance,  even thoIn conclusion, the percentage of subtype C, BC and CRFs could be increasing in the city of São Paulo in recent years. Molecular epidemiological information concerning HIV-1 strains is proving to be important in elucidating the dynamics of HIV spread and the formulation of future vaccine strategies.The authors declare that there are no competing interests.RA: Drafted the manuscript, analyzed data; MLG: Statistical analysis, phylogenetic analysis, Drafted the manuscript; ADJS: Revised the drafted the manuscript; JC: Designed the study, analyzed the data and drafted the final version of the manuscript. All authors read and approved the final manuscript.