The causal effect of switching to second-line ART in programmes without access to routine viral load monitoring

We examined the effect of switching to second-line antiretroviral therapy (ART) on mortality in patients who experienced immunological failure in ART programmes without access to routine viral load monitoring in sub-Saharan Africa.

Switching to second-line antiretroviral therapy in resource-limited settings: comparison of programmes with and without viral load monitoring

BACKGROUND: In high-income countries, viral load is routinely measured to detect failure of antiretroviral therapy (ART) and guide switching to second-line ART. Viral load monitoring is not generally available in resource-limited settings. We examined switching from nonnucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to protease inhibitor-based regimens in Africa, South America and Asia. DESIGN AND METHODS: Multicohort study of 17 ART programmes. All sites monitored CD4 cell count and had access to second-line ART and 10 sites monitored viral load. We compared times to switching, CD4 cell counts at switching and obtained adjusted hazard ratios for switching (aHRs) with 95% confidence intervals (CIs) from random-effects Weibull models. RESULTS: A total of 20 113 patients, including 6369 (31.7%) patients from 10 programmes with access to viral load monitoring, were analysed; 576 patients (2.9%) switched. Low CD4 cell counts at ART initiation were associated with switching in all programmes. Median time to switching was 16.3 months [interquartile range (IQR) 10.1-26.6] in programmes with viral load monitoring and 21.8 months (IQR 14.0-21.8) in programmes without viral load monitoring (P < 0.001). Median CD4 cell counts at switching were 161 cells/microl (IQR 77-265) in programmes with viral load monitoring and 102 cells/microl (44-181) in programmes without viral load monitoring (P < 0.001). Switching was more common in programmes with viral load monitoring during months 7-18 after starting ART (aHR 1.38; 95% CI 0.97-1.98), similar during months 19-30 (aHR 0.97; 95% CI 0.58-1.60) and less common during months 31-42 (aHR 0.29; 95% CI 0.11-0.79). CONCLUSION: In resource-limited settings, switching to second-line regimens tends to occur earlier and at higher CD4 cell counts in ART programmes with viral load monitoring compared with programmes without viral load monitoring.

Outcomes of antiretroviral treatment in programmes with and without routine viral load monitoring in Southern Africa

Objectives: To compare outcomes of antiretroviral therapy (ART) in South Africa, where viral load monitoring is routine, with those in Malawi and Zambia, where monitoring is based on CD4 cell counts. Methods: We included 18 706 adult patients starting ART in South Africa and 80 937 patients in Zambia or Malawi. We examined CD4 responses in models for repeated measures and the probability of switching to second-line regimens, mortality and loss to follow-up in multistate models, measuring time from 6 months. Results: In South Africa, 9.8% [95% confidence interval (CI) 9.1–10.5] had switched at 3 years, 1.3% (95% CI 0.9–1.6) remained on failing first-line regimens, 9.2% (95% CI 8.5–9.8) were lost to follow-up and 4.3% (95% CI 3.9–4.8) had died. In Malawi and Zambia, more patients were on a failing first-line regimen [3.7% (95% CI 3.6–3.9], fewer patients had switched [2.1% (95% CI 2.0–2.3)] and more patients were lost to follow-up [15.3% (95% CI 15.0–15.6)] or had died [6.3% (95% CI 6.0–6.5)]. Median CD4 cell counts were lower in South Africa at the start of ART (93 vs. 132 cells/μl; P < 0.001) but higher after 3 years (425 vs. 383 cells/μl; P < 0.001). The hazard ratio comparing South Africa with Malawi and Zambia after adjusting for age, sex, first-line regimen and CD4 cell count was 0.58 (0.50–0.66) for death and 0.53 (0.48–0.58) for loss to follow-up. Conclusion: Over 3 years of ART mortality was lower in South Africa than in Malawi or Zambia. The more favourable outcome in South Africa might be explained by viral load monitoring leading to earlier detection of treatment failure, adherence counselling and timelier switching to second-line ART.

Virologic failure and second-line antiretroviral therapy in children in South Africa--the IeDEA Southern Africa collaboration

Background: With expanding pediatric antiretroviral therapy (ART) access, children will begin to experience treatment failure and require second-line therapy. We evaluated the probability and determinants of virologic failure and switching in children in South Africa. Methods: Pooled analysis of routine individual data from children who initiated ART in 7 South African treatment programs with 6-monthly viral load and CD4 monitoring produced Kaplan-Meier estimates of probability of virologic failure (2 consecutive unsuppressed viral loads with the second being >1000 copies/mL, after ≥24 weeks of therapy) and switch to second-line. Cox-proportional hazards models stratified by program were used to determine predictors of these outcomes. Results: The 3-year probability of virologic failure among 5485 children was 19.3% (95% confidence interval: 17.6 to 21.1). Use of nevirapine or ritonavir alone in the initial regimen (compared with efavirenz) and exposure to prevention of mother to child transmission regimens were independently associated with failure [adjusted hazard ratios (95% confidence interval): 1.77 (1.11 to 2.83), 2.39 (1.57 to 3.64) and 1.40 (1.02 to 1.92), respectively]. Among 252 children with ≥1 year follow-up after failure, 38% were switched to second-line. Median (interquartile range) months between failure and switch was 5.7 (2.9-11.0). Conclusions: Triple ART based on nevirapine or ritonavir as a single protease inhibitor seems to be associated with a higher risk of virologic failure. A low proportion of virologically failing children were switched.

The role of targeted viral load testing in diagnosing virological failure in children on antiretroviral therapy with immunological failure

Objectives  To determine the improvement in positive predictive value of immunological failure criteria for identifying virological failure in HIV-infected children on antiretroviral therapy (ART) when a single targeted viral load measurement is performed in children identified as having immunological failure. Methods  Analysis of data from children (<16 years at ART initiation) at South African ART sites at which CD4 count/per cent and HIV-RNA monitoring are performed 6-monthly. Immunological failure was defined according to both WHO 2010 and United States Department of Health and Human Services (DHHS) 2008 criteria. Confirmed virological failure was defined as HIV-RNA >5000 copies/ml on two consecutive occasions <365 days apart in a child on ART for ≥18 months. Results  Among 2798 children on ART for ≥18 months [median (IQR) age 50 (21-84) months at ART initiation], the cumulative probability of confirmed virological failure by 42 months on ART was 6.3%. Using targeted viral load after meeting DHHS immunological failure criteria rather than DHHS immunological failure criteria alone increased positive predictive value from 28% to 82%. Targeted viral load improved the positive predictive value of WHO 2010 criteria for identifying confirmed virological failure from 49% to 82%. Conclusion  The addition of a single viral load measurement in children identified as failing immunologically will prevent most switches to second-line treatment in virologically suppressed children.

Zidovudine impairs immunological recovery on first-line antiretroviral therapy: collaborative analysis of cohort studies in southern Africa

OBJECTIVES Zidovudine (ZDV) is recommended for first-line antiretroviral therapy (ART) in resource-limited settings. ZDV may, however, lead to anemia and impaired immunological response. We compared CD4+ cell counts over 5 years between patients starting ART with and without ZDV in southern Africa. DESIGN Cohort study. METHODS Patients aged at least 16 years who started first-line ART in South Africa, Botswana, Zambia, or Lesotho were included. We used linear mixed-effect models to compare CD4+ cell count trajectories between patients on ZDV-containing regimens and patients on other regimens, censoring follow-up at first treatment change. Impaired immunological recovery, defined as a CD4+ cell count below 100 cells/μl at 1 year, was assessed in logistic regression. Analyses were adjusted for baseline CD4+ cell count and hemoglobin level, age, sex, type of regimen, viral load monitoring, and calendar year. RESULTS A total of 72,597 patients starting ART, including 19,758 (27.2%) on ZDV, were analyzed. Patients on ZDV had higher CD4+ cell counts (150 vs.128 cells/μl) and hemoglobin level (12.0 vs. 11.0 g/dl) at baseline, and were less likely to be women than those on other regimens. Adjusted differences in CD4+ cell counts between regimens containing and not containing ZDV were -16 cells/μl [95% confidence interval (CI) -18 to -14] at 1 year and -56 cells/μl (95% CI -59 to -52) at 5 years. Impaired immunological recovery was more likely with ZDV compared to other regimens (odds ratio 1.40, 95% CI 1.22-1.61). CONCLUSION In southern Africa, ZDV is associated with inferior immunological recovery compared to other backbones. Replacing ZDV with another nucleoside reverse transcriptase inhibitor could avoid unnecessary switches to second-line ART.

Cost-effectiveness of point-of-care viral load monitoring of antiretroviral therapy in resource-limited settings: mathematical modelling study

BACKGROUND Monitoring of HIV viral load in patients on combination antiretroviral therapy (ART) is not generally available in resource-limited settings. We examined the cost-effectiveness of qualitative point-of-care viral load tests (POC-VL) in sub-Saharan Africa. DESIGN Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. METHODS Cohorts of patients on ART monitored by POC-VL, CD4 cell count or clinically were simulated. Scenario A considered the more accurate detection of treatment failure with POC-VL only, and scenario B also considered the effect on HIV transmission. Scenario C further assumed that the risk of virologic failure is halved with POC-VL due to improved adherence. We estimated the change in costs per quality-adjusted life-year gained (incremental cost-effectiveness ratios, ICERs) of POC-VL compared with CD4 and clinical monitoring. RESULTS POC-VL tests with detection limits less than 1000 copies/ml increased costs due to unnecessary switches to second-line ART, without improving survival. Assuming POC-VL unit costs between US$5 and US$20 and detection limits between 1000 and 10,000 copies/ml, the ICER of POC-VL was US$4010-US$9230 compared with clinical and US$5960-US$25540 compared with CD4 cell count monitoring. In Scenario B, the corresponding ICERs were US$2450-US$5830 and US$2230-US$10380. In Scenario C, the ICER ranged between US$960 and US$2500 compared with clinical monitoring and between cost-saving and US$2460 compared with CD4 monitoring. CONCLUSION The cost-effectiveness of POC-VL for monitoring ART is improved by a higher detection limit, by taking the reduction in new HIV infections into account and assuming that failure of first-line ART is reduced due to targeted adherence counselling.

Low-frequency drug-resistant HIV-1 and risk of virological failure to first-line NNRTI-based ART: a multicohort European case-control study using centralized ultrasensitive 454 pyrosequencing.

OBJECTIVES It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. METHODS This Europe-wide case-control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%-25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. RESULTS Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35-5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76-6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12-5.18, P = 0.024). A dose-effect relationship between virological failure and mutational load was found. CONCLUSIONS Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

The brain’s pre-stimulus default state interacts with working memory in a load-dependent manner

Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

Viral load versus CD4⁺ monitoring and 5-year outcomes of antiretroviral therapy in HIV-positive children in Southern Africa: a cohort-based modelling study.

OBJECTIVES Many paediatric antiretroviral therapy (ART) programmes in Southern Africa rely on CD4⁺ to monitor ART. We assessed the benefit of replacing CD4⁺ by viral load monitoring. DESIGN A mathematical modelling study. METHODS A simulation model of HIV progression over 5 years in children on ART, parameterized by data from seven South African cohorts. We simulated treatment programmes with 6-monthly CD4⁺ or 6- or 12-monthly viral load monitoring. We compared mortality, second-line ART use, immunological failure and time spent on failing ART. In further analyses, we varied the rate of virological failure, and assumed that the rate is higher with CD4⁺ than with viral load monitoring. RESULTS About 7% of children were predicted to die within 5 years, independent of the monitoring strategy. Compared with CD4⁺ monitoring, 12-monthly viral load monitoring reduced the 5-year risk of immunological failure from 1.6 to 1.0% and the mean time spent on failing ART from 6.6 to 3.6 months; 1% of children with CD4⁺ compared with 12% with viral load monitoring switched to second-line ART. Differences became larger when assuming higher rates of virological failure. When assuming higher virological failure rates with CD4⁺ than with viral load monitoring, up to 4.2% of children with CD4⁺ compared with 1.5% with viral load monitoring experienced immunological failure; the mean time spent on failing ART was 27.3 months with CD4⁺ monitoring and 6.0 months with viral load monitoring. Conclusion: Viral load monitoring did not affect 5-year mortality, but reduced time on failing ART, improved immunological response and increased switching to second-line ART.

Monitoring and Switching of First-line Antiretroviral Therapy in sub-Saharan Africa: Collaborative Analysis of Adult Treatment Cohorts.

BACKGROUND HIV-1 viral load (VL) testing is recommended to monitor antiretroviral therapy (ART) but not universally available. We examined monitoring of first-line and switching to second-line ART in sub-Saharan Africa, 2004-2013. METHODS Adult HIV-1 infected patients starting combination ART in 16 countries were included. Switching was defined as a change from a non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based regimen to a protease inhibitor (PI)-based regimen, with a change of ≥1 NRTI. Virological and immunological failures were defined per World Health Organization criteria. We calculated cumulative probabilities of switching and hazard ratios with 95% confidence intervals (CI) comparing routine VL monitoring, targeted VL monitoring, CD4 cell monitoring and clinical monitoring, adjusted for programme and individual characteristics. FINDINGS Of 297,825 eligible patients, 10,352 patients (3·5%) switched during 782,412 person-years of follow-up. Compared to CD4 monitoring hazard ratios for switching were 3·15 (95% CI 2·92-3·40) for routine VL, 1·21 (1·13-1·30) for targeted VL and 0·49 (0·43-0·56) for clinical monitoring. Overall 58.0% of patients with confirmed virological and 19·3% of patients with confirmed immunological failure switched within 2 years. Among patients who switched the percentage with evidence of treatment failure based on a single CD4 or VL measurement ranged from 32·1% with clinical to 84.3% with targeted VL monitoring. Median CD4 counts at switching were 215 cells/µl under routine VL monitoring but lower with other monitoring (114-133 cells/µl). INTERPRETATION Overall few patients switched to second-line ART and switching occurred late in the absence of routine viral load monitoring. Switching was more common and occurred earlier with targeted or routine viral load testing.

The need for second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030: a mathematical modelling study.

BACKGROUND The number of patients in need of second-line antiretroviral drugs is increasing in sub-Saharan Africa. We aimed to project the need of second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030. METHODS We developed a simulation model for HIV and applied it to each sub-Saharan African country. We used the WHO country intelligence database to estimate the number of adult patients receiving antiretroviral therapy from 2005 to 2014. We fitted the number of adult patients receiving antiretroviral therapy to observed estimates, and predicted first-line and second-line needs between 2015 and 2030. We present results for sub-Saharan Africa, and eight selected countries. We present 18 scenarios, combining the availability of viral load monitoring, speed of antiretroviral scale-up, and rates of retention and switching to second-line. HIV transmission was not included. FINDINGS Depending on the scenario, 8·7-25·6 million people are expected to receive antiretroviral therapy in 2020, of whom 0·5-3·0 million will be receiving second-line antiretroviral therapy. The proportion of patients on treatment receiving second-line therapy was highest (15·6%) in the scenario with perfect retention and immediate switching, no further scale-up, and universal routine viral load monitoring. In 2030, the estimated range of patients receiving antiretroviral therapy will remain constant, but the number of patients receiving second-line antiretroviral therapy will increase to 0·8-4·6 million (6·6-19·6%). The need for second-line antiretroviral therapy was two to three times higher if routine viral load monitoring was implemented throughout the region, compared with a scenario of no further viral load monitoring scale-up. For each monitoring strategy, the future proportion of patients receiving second-line antiretroviral therapy differed only minimally between countries. INTERPRETATION Donors and countries in sub-Saharan Africa should prepare for a substantial increase in the need for second-line drugs during the next few years as access to viral load monitoring improves. An urgent need exists to decrease the costs of second-line drugs. FUNDING World Health Organization, Swiss National Science Foundation, National Institutes of Health.