A randomized study of the utility of human immunodeficiency virus RNA measurement for the management of antiretroviral therapy

Comparison of dynamic monitoring strategies based on CD4 cell counts in virally suppressed, HIV-positive individuals on combination antiretroviral therapy in high-income countries: a prospective, observational study

BACKGROUND

Clinical guidelines vary with respect to the optimal monitoring frequency of HIV-positive individuals. We compared dynamic monitoring strategies based on time-varying CD4 cell counts in virologically suppressed HIV-positive individuals.

METHODS

In this observational study, we used data from prospective studies of HIV-positive individuals in Europe (France, Greece, the Netherlands, Spain, Switzerland, and the UK) and North and South America (Brazil, Canada, and the USA) in The HIV-CAUSAL Collaboration and The Centers for AIDS Research Network of Integrated Clinical Systems. We compared three monitoring strategies that differ in the threshold used to measure CD4 cell count and HIV RNA viral load every 3-6 months (when below the threshold) or every 9-12 months (when above the threshold). The strategies were defined by the threshold CD4 counts of 200 cells per μL, 350 cells per μL, and 500 cells per μL. Using inverse probability weighting to adjust for baseline and time-varying confounders, we estimated hazard ratios (HRs) of death and of AIDS-defining illness or death, risk ratios of virological failure, and mean differences in CD4 cell count.

FINDINGS

47 635 individuals initiated an antiretroviral therapy regimen between Jan 1, 2000, and Jan 9, 2015, and met the eligibility criteria for inclusion in our study. During follow-up, CD4 cell count was measured on average every 4·0 months and viral load every 3·8 months. 464 individuals died (107 in threshold 200 strategy, 157 in threshold 350, and 200 in threshold 500) and 1091 had AIDS-defining illnesses or died (267 in threshold 200 strategy, 365 in threshold 350, and 459 in threshold 500). Compared with threshold 500, the mortality HR was 1·05 (95% CI 0·86-1·29) for threshold 200 and 1·02 (0·91·1·14) for threshold 350. Corresponding estimates for death or AIDS-defining illness were 1·08 (0·95-1·22) for threshold 200 and 1·03 (0·96-1·12) for threshold 350. Compared with threshold 500, the 24 month risk ratios of virological failure (viral load more than 200 copies per mL) were 2·01 (1·17-3·43) for threshold 200 and 1·24 (0·89-1·73) for threshold 350, and 24 month mean CD4 cell count differences were 0·4 (-25·5 to 26·3) cells per μL for threshold 200 and -3·5 (-16·0 to 8·9) cells per μL for threshold 350.

INTERPRETATION

Decreasing monitoring to annually when CD4 count is higher than 200 cells per μL compared with higher than 500 cells per μL does not worsen the short-term clinical and immunological outcomes of virally suppressed HIV-positive individuals. However, more frequent virological monitoring might be necessary to reduce the risk of virological failure. Further follow-up studies are needed to establish the long-term safety of these strategies.

FUNDING

National Institutes of Health.

When to Monitor CD4 Cell Count and HIV RNA to Reduce Mortality and AIDS-Defining Illness in Virologically Suppressed HIV-Positive Persons on Antiretroviral Therapy in High-Income Countries: A Prospective Observational Study

OBJECTIVE

To illustrate an approach to compare CD4 cell count and HIV-RNA monitoring strategies in HIV-positive individuals on antiretroviral therapy (ART).

DESIGN

Prospective studies of HIV-positive individuals in Europe and the USA in the HIV-CAUSAL Collaboration and The Center for AIDS Research Network of Integrated Clinical Systems.

METHODS

Antiretroviral-naive individuals who initiated ART and became virologically suppressed within 12 months were followed from the date of suppression. We compared 3 CD4 cell count and HIV-RNA monitoring strategies: once every (1) 3 ± 1 months, (2) 6 ± 1 months, and (3) 9-12 ± 1 months. We used inverse-probability weighted models to compare these strategies with respect to clinical, immunologic, and virologic outcomes.

RESULTS

In 39,029 eligible individuals, there were 265 deaths and 690 AIDS-defining illnesses or deaths. Compared with the 3-month strategy, the mortality hazard ratios (95% CIs) were 0.86 (0.42 to 1.78) for the 6 months and 0.82 (0.46 to 1.47) for the 9-12 month strategy. The respective 18-month risk ratios (95% CIs) of virologic failure (RNA >200) were 0.74 (0.46 to 1.19) and 2.35 (1.56 to 3.54) and 18-month mean CD4 differences (95% CIs) were -5.3 (-18.6 to 7.9) and -31.7 (-52.0 to -11.3). The estimates for the 2-year risk of AIDS-defining illness or death were similar across strategies.

CONCLUSIONS

Our findings suggest that monitoring frequency of virologically suppressed individuals can be decreased from every 3 months to every 6, 9, or 12 months with respect to clinical outcomes. Because effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

Performance and logistical challenges of alternative HIV-1 virological monitoring options in a clinical setting of Harare, Zimbabwe

We evaluated a low-cost virological failure assay (VFA) on plasma and dried blood spot (DBS) specimens from HIV-1 infected patients attending an HIV clinic in Harare. The results were compared to the performance of the ultrasensitive heat-denatured p24 assay (p24). The COBAS AmpliPrep/COBAS TaqMan HIV-1 test, version 2.0, served as the gold standard. Using a cutoff of 5,000 copies/mL, the plasma VFA had a sensitivity of 94.5% and specificity of 92.7% and was largely superior to the VFA on DBS (sensitivity = 61.9%; specificity = 99.0%) or to the p24 (sensitivity = 54.3%; specificity = 82.3%) when tested on 302 HIV treated and untreated patients. However, among the 202 long-term ART-exposed patients, the sensitivity of the VFA decreased to 72.7% and to 35.7% using a threshold of 5,000 and 1,000 RNA copies/mL, respectively. We show that the VFA (either on plasma or on DBS) and the p24 are not reliable to monitor long-term treated, HIV-1 infected patients. Moreover, achieving acceptable assay sensitivity using DBS proved technically difficult in a less-experienced laboratory. Importantly, the high level of virological suppression (93%) indicated that quality care focused on treatment adherence limits virological failure even when PCR-based viral load monitoring is not available.

Immuno-haematologic and virologic responses and predictors of virologic failure in HIV-1 infected adults on first-line antiretroviral therapy in Cameroon

Background

Contemporary data on the immunologic, haematologic and virologic responses and predictors of virologic failure after initiation of free antiretroviral treatment in Cameroon are needed to evaluate the current treatment-monitoring algorithm and to complement efforts to scale-up and improve on the management of HIV infections.

Methods

This was a cross-sectional study conducted between October 2010 and June 2012. A total of 951 participants aged 18–74 years were recruited from selected approved HIV treatment centres of the Northwest and Southwest regions. This comprised 247 males and 704 females. Demographic, self-reported risk behaviours and socioeconomic data were obtained using a structured questionnaire. Full blood and CD4 + T-cell counts were done using standard automated techniques. Determination of viral load (VL) was done using Abbott RealTime HIV-1 m2000™ system. Data was analysed using SPSS version 17. The statistical significance level was P < 0.05.

Results

The median duration of antiretroviral therapy (ART) was 24 months. The population mean CD4 + T-cell count was 255.3 cells/μL [95% CI, 236.8 – 273.9]. Overall, 45.9%, 43.8% and 10.2% of the participants had CD4 + T-cell counts of < 200 cells/μL, 200–499 cells/μL and > 500 cells/μL respectively. Anaemia was present in 26.2% of the participants with 62.3%, 25.7% and 12% described as mild, moderate and severe anaemia respectively. Virologic failure occurred in 23.2% of the participants with 12.3% having VL > 10,000 RNA copies/mL. Meanwhile 76.8% of patients attained adequate viral suppression with 40.8% having undetectable viral load. The age group 18–29 years (p = 0.024), co-infection with tuberculosis (p = 0.014), anaemia (p = 0.028) and distance from the treatment centre (p = 0.011) independently predicted virologic failure.

Conclusion

The majority of the participants achieved adequate viral suppression after ≥ 6 months of ART. Despite these favourable immuno-haematologic and virologic outcomes, the National AIDS Control Program should step-up efforts to improve on antiretroviral drug distribution, as well as proper assessment and management of anaemia, foster early diagnosis and treatment of tuberculosis and enhance treatment adherence counselling especially in younger patients.

Evaluation of WHO immunologic criteria for treatment failure: implications for detection of virologic failure, evolution of drug resistance and choice of second-line therapy in India

Introduction

Routine HIV viral load (VL) testing is not available in India. We compared test performance characteristics of immunologic failure (IF) against the gold standard of virologic failure (VF), examined evolution of drug resistance among those who stayed on a failing regimen because they did not meet criteria for IF and assessed implications for second-line therapy.

Methods

Participants on first-line highly active antiretroviral therapy (HAART) in Bangalore, India, were monitored for 24 months at six-month intervals, with CD4 count, VL and genotype, if VL>1000 copies/ml. Standard WHO criteria were used to define IF; VF was defined as having two consecutive VL>1000 copies/ml or one VL>10,000 copies/ml. Resistance was assessed using standard International AIDS Society-USA (IAS-USA) recommendations.

Results

Of 522 participants (67.6% male, mean age of 37.5; 85.1% on nevirapine-based and 40.4% on d4T-containing regimens), 57 (10.9%) had VF, 38 (7.3%) had IF and 13 (2.5%) had both VF and IF. The sensitivity of immunologic criteria to detect VF was 22.8%, specificity was 94.6% and positive predictive value was 34.2%. Forty-four participants with VF only continued on their failing first-line regimen; by the end of the study period, 90.9% had M184V, 63.6% had thymidine analogue mutations (TAMs), 34.1% had resistance to tenofovir, and 63.6% had resistance to etravirine.

Conclusions

WHO IF criteria have low sensitivity for detecting VF, and the presence of IF poorly predicts VF. Relying on CD4 counts leads to unnecessary switches to second-line HAART and continuation of failing regimens, jeopardizing future therapeutic options. Universal access to VL monitoring would avoid costly switches to second-line HAART and preserve future treatment options.

Frequency of HIV-1 viral load monitoring of patients initially successfully treated with combination antiretroviral therapy

Background

Although considered an essential tool for monitoring the effect of combination antiretroviral treatment (CART), HIV-1 RNA (viral load, VL) testing is greatly influenced by cost and availability of resources.

Objectives

To examine whether HIV infected patients who were initially successfully treated with CART have less frequent monitoring of VL over time and whether CART failure and other HIV-disease and sociodemographic characteristics are associated with less frequent VL testing.

Methods

The study included patients who started CART in the period 1999–2004, were older than 18 years, CART naive, had two consecutive viral load measurements of <400 copies/ml after 5 months of treatment and had continuous CART during the first 15 months. The time between two consecutive visits (days) was the outcome and associated factors were assessed using linear mixed models.

Results

We analyzed a total of 128 patients with 1683 visits through December 2009. CART failure was observed in 31 (24%) patients. When adjusted for the follow-up time, the mean interval between two consecutive VL tests taken in patients before CART failure (155.2 days) was almost identical to the interval taken in patients who did not fail CART (155.3 days). On multivariable analysis, we found that the adjusted estimated time between visits was 150.9 days before 2003 and 177.6 in 2008/2009. A longer time between visits was observed in seafarers compared to non-seafarers; the mean difference was 30.7 days (95% CI, 14.0 to 47.4; p<0.001); and in individuals who lived more than 160 kilometers from the HIV treatment center (mean difference, 16 days, p = 0.010).

Conclusions

Less frequent monitoring of VL became common in recent years and was not associated with failure. We identified seafarers as a population with special needs for CART monitoring and delivery.

Optimal monitoring strategies for guiding when to switch first-line antiretroviral therapy regimens for treatment failure in adults and adolescents living with HIV in low-resource settings

BACKGROUND

One of the critical clinical decisions made in antiretroviral therapy (ART) is when to switch from an initial regimen to another due to treatment failure. This complex process requires consideration of multiple factors including: (1) what type of monitoring (e.g. clinical, immunologic, virologic) is available to guide switching; (2) establishing criteria for treatment failure (e.g. viral load >10,000 copies/mL); (3) integrating data from different types of monitoring; (4) making a decision; and, if possible, (5) follow-up and monitoring to determine patient outcomes. The initial step in this model of deciding when to switch is determining what type of monitoring for guiding when to switch is available and appropriate. This review seeks to find and summarize evidence on optimal monitoring strategies for guiding when to switch first-line regimens due to treatment failure among adults and adolescents living with HIV in low-resource settings. This review was one of a series of reviews prepared in 2009 at the request of the World Health Organization to inform the development of new guidelines on ART for adults and adolescents.

OBJECTIVES

To assess optimal monitoring strategies for guiding when to switch antiretroviral therapy regimens for first-line treatment failure among adults and adolescents living with HIV in low-resource settings.

SEARCH STRATEGY

We formulated a comprehensive and exhaustive search strategy in an attempt to identify all relevant studies regardless of language or publication status. In July 2009, we search the following electronic journal and trial databases: MEDLINE, EMBASE, CENTRAL. We also searched conference databases using NLM Gateway (for HIV/AIDS conference abstracts before 2005), abstract databases from the Conferences on Retroviruses and Opportunistic Infections, International AIDS Conferences, and International AIDS Society Conferences on HIV Pathogenesis, Treatment, and Prevention from 2005 to 2009, and the trials registers ClinicalTrials.gov, Current Controlled Trials, and Pan-African Clinical Trials Registry. We contacted researchers and relevant organizations and checked reference lists for all included studies.

SELECTION CRITERIA

We selected studies which evaluated a monitoring intervention/strategy that helps guide when to switch ART. Study types included randomized controlled trials and observational studies (cohort and case-control) which included comparators.

DATA COLLECTION AND ANALYSIS

One author performed an initial screening. Two authors performed a detailed screening. Two authors independently assessed study eligibility, extracted data, and graded methodological quality. Differences were resolved by a third reviewer. Heterogeneity was assessed, and meta-analyses were performed where appropriate.

MAIN RESULTS

Two randomized trials were identified which were in abstract form only. Two cohort studies (both published) with comparators were identified. Of the evidence available, three comparisons were studied: clinical versus immunologic and clinical monitoring; clinical versus virologic, immunologic, and clinical monitoring; and immunologic and clinical monitoring versus virologic, immunologic, and clinical monitoring. Clinical vs. Immunologic and Clinical Monitoring: Based upon two randomized trials, clinical monitoring alone results in increased mortality (low-quality evidence), increased AIDS-defining illnesses and mortality as a composite endpoint (moderate), no difference in serious adverse events (low), increased numbers of unnecessary switches (low), and no difference in switches to second-line (low) compared to immunological and clinical monitoring. Clinical vs. Virologic, Immunologic, and Clinical Monitoring: Based upon a single randomized trial, clinical monitoring alone results in a trend toward increased mortality (low), increased AIDS-defining illnesses and mortality as a composite endpoint (low), increased unnecessary switches (low), no difference in virologic treatment failures (low), and a trend toward increased switches to second-line (low) compared to virologic, immunologic, and clinical monitoring. Immunologic and Clinical vs. Virologic, Immunologic, and Clinical Monitoring: Based upon a single randomized trial, immunologic and clinical monitoring results in no difference in mortality (low), no difference in AIDS-defining illnesses and mortality as a composite endpoint (low), no difference in unnecessary switches (very low), no difference in virologic treatment failures (low), and no difference in switches to second-line (low) compared to virologic, immunologic, and clinical monitoring. Observational studies appear to demonstrate that programs with virologic, immunologic, and clinical monitoring switch therapy more frequently (very low), earlier (very low), and at higher CD4 counts (very low) compared with programs that have immunologic and clinical monitoring alone.

AUTHORS' CONCLUSIONS

A limited number of studies were available to address this topic, and, of the two randomized trials identified, both were in abstract form only. Observational studies also were limited in number and were of lesser quality. Although the quality of the evidence varied from the randomized trials, ranging from very low to moderate, there appeared to be substantial benefits for key outcomes (e.g. mortality, AIDS-defining illness and mortality as a composite endpoint, and unnecessary switches) favoring both immunologic and clinical monitoring or virologic, immunologic, and clinical monitoring versus clinical monitoring alone. Very low-quality evidence from observational studies suggested that virologic, immunologic, and clinical monitoring led to more frequent switching, earlier switching, and switching at higher CD4 counts compared with immunologic and clinical monitoring. Further information on the studies currently reported in abstract form will provide insight. Ongoing studies addressing this topic likely will provide information to further clarify optimal monitoring strategies for guiding when to switch first-line therapy. Additionally, studies looking at different virologic monitoring frequencies and/or virologic monitoring at different times after ART initiation (e.g. after 2-3 years) would be informative. Finally, cost-analysis studies will lend further insights into the applicability of these findings to low-resource settings.

Defining treatment failure in resource-rich settings

PURPOSE OF REVIEW

To define treatment failure in resource-rich settings; summarizing current guidelines, assays, the significance of detectable viremia, and definitions of treatment failure in clinical and research settings.

RECENT FINDINGS

The goal of treatment should be full viral suppression, even in highly treatment-experienced patients.

SUMMARY

Treatment failure is defined as repeated HIV RNA values above the lower limit of detection of a sensitive assay (usually 50 copies/ml). This criterion is based on evidence that the maximum clinical benefit of antiretroviral therapy is derived by keeping the viral load as low as possible. Full viral suppression should be achievable in all patients, both treatment-naïve and experienced. Transient, low-detectable viremia ('blips') may not predict virologic breakthrough. However, consecutive or higher-level transient viremia is associated with risk of treatment failure. Defining failure by a confirmed HIV RNA more than 50 copies/ml is the most conservative approach, but the use of such low limits of detection in clinical trials may lead to a high false-positive 'failure' rate, thus a definition of 200 copies/ml may be preferable. Variation in clinical trial endpoint definitions creates a challenge for comparing results between studies. For example, using a composite endpoint to define treatment failure may result in a high proportion of 'failures' that are not related to poor virologic response.

Pooled nucleic acid testing to identify antiretroviral treatment failure during HIV infection

BACKGROUND

Pooling strategies have been used to reduce the costs of polymerase chain reaction-based screening for acute HIV infection in populations in which the prevalence of acute infection is low (less than 1%). Only limited research has been done for conditions in which the prevalence of screening positivity is higher (greater than 1%).

METHODS AND RESULTS

We present data on a variety of pooling strategies that incorporate the use of polymerase chain reaction-based quantitative measures to monitor for virologic failure among HIV-infected patients receiving antiretroviral therapy. For a prevalence of virologic failure between 1% and 25%, we demonstrate relative efficiency and accuracy of various strategies. These results could be used to choose the best strategy based on the requirements of individual laboratory and clinical settings such as required turnaround time of results and availability of resources.

CONCLUSIONS

Virologic monitoring during antiretroviral therapy is not currently being performed in many resource-constrained settings largely because of costs. The presented pooling strategies may be used to significantly reduce the cost compared with individual testing, make such monitoring feasible, and limit the development and transmission of HIV drug resistance in resource-constrained settings. They may also be used to design efficient pooling strategies for other settings with quantitative screening measures.

Comparison of the COBAS TAQMAN™ HIV-1 HPS with VERSANT HIV-1 RNA 3.0 Assay (bDNA) for plasma RNA quantitation in different HIV-1 subtypes

Quantitation of HIV-1 RNA levels in plasma has an undisputed prognostic value and is extremely important for evaluating response to antiretroviral therapy. The purpose of this study was to evaluate the performance of the real-time PCR COBAS TaqMan 48 analyser, comparing it to the existing VERSANT 3.0 (bDNA) for HIV-1 RNA quantitation in plasma of individuals infected with different HIV-1 subtypes (104 blood samples). A positive linear correlation between the two tests (r2 = 0.88) was found. Quantitation by the COBAS TaqMan assay was approximately 0.32log10 higher than by bDNA. The relationship between the two assays was similar within all subtypes with a Deming regression of <1 and <0 for the Bland-Altman plots. Overall, no significant differences were found in plasma viral load quantitation in different HIV-1 subtypes between both assays; therefore these assays are suitable for viral load quantitation of highly genetically diverse HIV-1 plasma samples.

Evaluation of the clinical sensitivity for the quantification of human immunodeficiency virus type 1 RNA in plasma: Comparison of the new COBAS TaqMan HIV-1 with three current HIV-RNA assays--LCx HIV RNA quantitative, VERSANT HIV-1 RNA 3.0 (bDNA) and COBAS AMPLICOR HIV-1 Monitor v1.5

The COBAS TaqMan HIV-1 test (Roche Diagnostics) was compared with the LCx HIV RNA quantitative assay (Abbott Laboratories), the Versant HIV-1 RNA 3.0 (bDNA) assay (Bayer) and the COBAS Amplicor HIV-1 Monitor v1.5 test (Roche Diagnostics), using plasma samples of various viral load levels from HIV-1-infected individuals. In the comparison of TaqMan with LCx, TaqMan identified as positive 77.5% of the 240 samples versus 72.1% identified by LCx assay, while their overall agreement was 94.6% and the quantitative results of samples that were positive by both methods were strongly correlated (r=0.91). Similarly, in the comparison of TaqMan with bDNA 3.0, both methods identified 76.3% of the 177 samples as positive, while their overall agreement was 95.5% and the quantitative results of samples that were positive by both methods were strongly correlated (r=0.95). Finally, in the comparison of TaqMan with Monitor v1.5, TaqMan identified 79.5% of the 156 samples as positive versus 80.1% identified by Monitor v1.5, while their overall agreement was 95.5% and the quantitative results of samples that were positive by both methods were strongly correlated (r=0.96). In conclusion, the new COBAS TaqMan HIV-1 test showed excellent agreement with other widely used commercially available tests for the quantitation of HIV-1 viral load.

Optimal Frequency of Cd4 Cell Count and HIV Rna Monitoring Prior to Initiation of Antiretroviral Therapy in HIV-Infected Patients

Context

Guidelines regarding the frequency of CD4 cell count and HIV RNA monitoring in HIV-infected patients vary, with recommended strategies ranging from every 2 to every 6 months.

Objective

To determine optimal CD4 cell count and HIV RNA monitoring frequency in HIV-infected patients prior to antiretroviral therapy initiation. Design: Cost-effectiveness (CE) analysis using an HIV simulation model incorporating CD4 cell count and HIV RNA as immunological and virological predictors of clinical outcomes.

Setting

Hypothetical clinical setting.

Patients

Simulated cohort based on initial clinical presentation of HIV-infected patients in the US.

Intervention

CD4 cell count and HIV RNA monitoring at frequencies ranging from every 2 to 24 months prior to antiretroviral initiation, as well as accelerated monitoring frequencies as CD4 cell counts approach a specified treatment threshold.

Outcome measures

Life expectancy, quality-adjusted life expectancy and costs.

Results

For patients presenting with median CD4 cell count 546/mm3 and median HIV RNA 4.8 log10 copies/ml, incremental CE ratios ranged from US$37800/quality-adjusted life year (QALY) gained for a constant testing frequency of every 18 months compared with every 24 months, to US$303300/QALY gained for a constant testing frequency of every 2 months compared with every 4 months when starting treatment at a CD4 cell count of 350/mm3. Monitoring every 12 months until a warning CD4 cell count threshold of 450/mm3 followed by every 3 months until 350/mm3 had an incremental CE ratio of US$74700/QALY gained. When starting antiretroviral therapy at CD4 cell count 200/mm3, monitoring every 12 months until 300/mm3 followed by every 2 months until treatment initiation yielded an incremental CE ratio of US$52200/QALY gained compared with the next best strategy. Increasing monitoring frequency as CD4 cell counts approached a treatment threshold yielded greater incremental clinical benefit for less cost than strategies using a constant frequency.

Conclusions

Monitoring HIV-infected patients every 12 months until 100 CD4 cells/mm3 prior to a specified treatment threshold followed by more frequent monitoring every 2 or 3 months until antiretroviral therapy initiation is both more effective and cost-effective than the current standard of care.

The Correlation between Plasma Concentrations of Protease Inhibitors, Medication Adherence and Virological Outcome in HIV-Infected Patients

Background

Although adherence clearly influences response to antiretroviral therapy (ART), accurate assessment of adherence is problematic. The objective of this analysis was to assess the independent predictive value of protease inhibitor (PI) concentrations as a supplement to self-report as markers of medication adherence.

Methods

This retrospective analysis was conducted from a prospective clinical trial designed to compare the outcomes of frequent versus infrequent HIV RNA measurement used to manage antiretroviral therapy. For 131 patients, self-reported medication adherence, HIV RNA levels, CD4 counts and PI concentrations (unannounced, random samples) were measured at baseline (when patients changed to a new regimen) and every 2 months thereafter. The change in HIV RNA from baseline to month 6 (area-based measure) was used to evaluate overall response. The proportion of measured PI concentrations below the detection limit was used as an alternative marker of adherence. An undetectable concentration would be expected after missing a single dose.

Results

The mean baseline CD4 count was 125 cells/mm3 and the mean HIV RNA level was 4.7 log10 copies/ml. The mean change in log10 HIV RNA was -0.73 copies/ml. The mean percentage of self-reported adherence was 91% (range: 15–100%) and the mean proportion of undetectable PI concentrations was 27% (range: 0–100%, mean 2.5 samples/patient). The correlation between the two measures was -0.23 ( P=0.009). In a multivariate model, percentage of visits with undetectable PI concentrations ( P=0.02), percentage of medication adherence ( P=0.02), baseline HIV RNA level ( P=0.005), prior PI use ( P=0.0004), prior lamivudine (3TC) use ( P=0.0009) and randomization to the frequent HIV RNA measurement group ( P<0.0001) were all related to change in HIV RNA. After accounting for adherence, patients who always had detectable PI concentrations had an average of 0.4 log10 additional HIV RNA reduction compared with those who had no detectable concentrations.

Conclusions

Repeated, random PI concentration values are independently predictive of virological response and may add to self-report of adherence in understanding the response to ART.

Justice and HIV care in Africa--antiretrovirals in perspective

The immense burden of HIV disease in sub-Saharan Africa has focused international interest on HIV care, especially on the lack of access to antiretroviral therapy (ART). Difficulties in implementing ART in Africa include drug costs, adequate long-term funding sources, assurance of drug quality, and rapid development of the human resources and healthcare infrastructure needed to deliver ART. Important questions requiring study are the minimum level of laboratory monitoring and clinical support consistent with good treatment outcomes, the impact of antiretroviral drug resistance on treated individuals and communities, and the effect of ART on transmission at a community level. There are some concerns and risks. First, a focus on treatment could compromise the commitment of individuals to risk-reduction, and of governments to prevention. Second, health equity could be reduced, by diverting scarce public funds from basic care for the poorest, to costly disease-suppressive care for a small and probably elite group. In conclusion, while prevention must be the first priority, care is also essential. The vast prevailing economic inequity between the world's rich and poor is the fundamental determinant of inequities in health and healthcare, including care for HIV. The global community of healthcare workers must focus its substantial influence on changing political and economic policies that foster injustice and AIDS.

Structure-based phenotyping predicts HIV-1 protease inhibitor resistance

Mutations in HIV-1 drug targets lead to resistance and consequent therapeutic failure of antiretroviral drugs. Phenotypic resistance assays are time-consuming and costly, and genotypic rules-based interpretations may fail to predict the effects of multiple mutations. We have developed a computational procedure that rapidly evaluates changes in the binding energy of inhibitors to mutant HIV-1 PR variants. Models of WT complexes were produced from crystal structures. Mutant complexes were built by amino acid substitutions in the WT complexes with subsequent energy minimization of the ligand and PR binding site residues. Accuracy of the models was confirmed by comparison with available crystal structures and by prediction of known resistance-related mutations. PR variants from clinical isolates were modeled in complex with six FDA-approved PIs, and changes in the binding energy (DeltaE(bind)) of mutant versus WT complexes were correlated with the ratios of phenotypic 50% inhibitory concentration (IC(50)) values. The calculated DeltaE(bind) of five PIs showed significant correlations (R(2) = 0.7-0.8) with IC(50) ratios from the Virco Antivirogram assay, and the DeltaE(bind) of six PIs showed good correlation (R(2) = 0.76-0.85) with IC(50) ratios from the Virologic PhenoSense assay. DeltaE(bind) cutoffs corresponding to a four-fold increase in IC(50) were used to define the structure-based phenotype as susceptible, resistant, or equivocal. Blind predictions for 78 PR variants gave overall agreement of 92% (kappa = 0.756) and 86% (kappa = 0.666) with PhenoSense and Antivirogram phenotypes, respectively. The structural phenotyping predicted drug resistance of clinical HIV-1 PR variants with an accuracy approaching that of frequently used cell-based phenotypic assays.

Evaluation of the clinical sensitivities of three viral load assays with plasma samples from a pediatric population predominantly infected with human immunodeficiency virus type 1 subtype G and BG recombinant forms

The viral load assays AMPLICOR HIV-1 Monitor Test 1.5, Nuclisens HIV-1 QT, and Quantiplex HIV RNA 3.0 (bDNA) were evaluated for their abilities to quantify human immunodeficiency virus type 1 (HIV-1) RNA in 64 plasma samples from 21 children infected in Portugal. The children were infected with HIV-1 subtypes A1, B, F1, G, and BG recombinant virus. AMPLICOR v1.5 and Quantiplex v3.0 detected all samples, and there was a good correlation of results between the two kits. Thirty-eight specimens containing HIV-1 subtype B, G, or recombinant BG, could not be detected by Nuclisens HIV-1 QT. We also evaluated the new Retina HIV-1 assay on 21 samples that were HIV-1 positive; Retina HIV-1 failed to detect 5 of 11 subtype G specimens. AMPLICOR v1.5 and Quantiplex v3.0 assays may be used for HIV-1 RNA quantification in Portugal, whereas an improvement in sensitivity for subtype G and recombinant BG is required for Nuclisens HIV-1 QT and Retina HIV-1.