CD4+ T-cell-guided structured treatment interruptions of antiretroviral therapy in HIV disease: projecting beyond clinical trials

Non-persistence to antiretroviral therapy among adults receiving HIV medical care in the United States

Not taking medicine over a specific period of time-non-persistence to antiretroviral therapy (ART)-may be associated with higher HIV-viral load. However, national estimates of non-persistence among U.S. HIV patients are lacking. We examined the association between non-persistence and various factors, including sustained HIV-viral suppression (VS) stratified by adherence, and assessed reasons for non-persistence using Medical Monitoring Project (MMP) data. MMP conducts clinical and behavioral surveillance among cross-sectional representative samples of adults receiving HIV care in the U.S. We analyzed weighted MMP interview and medical record abstraction data collected between 6/2011-5/2015 from 18,423 patients self-reporting ART use. We defined non-persistence as a self-initiated decision to not take ART for ≥2 consecutive days in the past 12-months, non-adherence as missing ≥1 ART dose during the past 3-days and sustained VS as all HIV-viral loads documented in medical record during the past 12-months as undetectable or <200 copies/mL. We used Rao-Scott chi-square tests to examine the association between non-persistence and sociodemographic, behavioral, clinical, and medication-related factors. We examined the association between non-persistence and sustained VS, stratified by adherence, and present prevalence ratios (PRs) with 95% confidence intervals (CIs). Reasons for non-persistence were assessed. Overall, 7% of patients reported non-persistence. Drug use, depression and medication side effects were associated with non-persistence (P < 0.01). Non-persistence was associated with the lack of sustained VS (PR: .66, CI:63-.70); this association did not differ by adherence level. However, VS was lower among the non-persistent/adherent compared with the persistent/non-adherent [51% (CI:47-54) versus 61% (CI:36-46), P < 0.01]. The most prevalent reason for non-persistence was treatment fatigue (38%). Though few persons in HIV care reported non-persistence, our findings suggest that non-persistence is associated with lack of sustained VS, regardless of adherence. Routine screening for non-persistence during clinical appointments and counseling for those at risk for non-persistence may help improve clinical outcomes.

Loss to Follow-up Trends in HIV-Positive Patients Receiving Antiretroviral Treatment in Asia From 2003 to 2013

INTRODUCTION

Over time, there has been a substantial improvement in antiretroviral treatment (ART) programs, including expansion of services and increased patient engagement. We describe time trends in, and factors associated with, loss to follow-up (LTFU) in HIV-positive patients receiving ART in Asia.

METHODS

Analysis included HIV-positive adults initiating ART in 2003-2013 at 7 ART programs in Asia. Patients LTFU had not attended the clinic for ≥180 days, had not died, or transferred to another clinic. Patients were censored at recent clinic visit, follow-up to January 2014. We used cumulative incidence to compare LTFU and mortality between years of ART initiation. Factors associated with LTFU were evaluated using a competing risks regression model, adjusted for clinical site.

RESULTS

A total of 8305 patients were included. There were 743 patients LTFU and 352 deaths over 26,217 person-years (pys), a crude LTFU, and mortality rate of 2.83 (2.64-3.05) per 100 pys and 1.34 (1.21-1.49) per 100 pys, respectively. At 24 months, the cumulative LTFU incidence increased from 4.3% (2.9%-6.1%) in 2003-05 to 8.1% (7.1%-9.2%) in 2006-09 and then decreased to 6.7% (5.9%-7.5%) in 2010-13. Concurrently, the cumulative mortality incidence decreased from 6.2% (4.5%-8.2%) in 2003-05 to 3.3% (2.8%-3.9%) in 2010-13. The risk of LTFU reduced in 2010-13 compared with 2006-09 (adjusted subhazard ratio = 0.73, 0.69-0.99).

CONCLUSIONS

LTFU rates in HIV-positive patients receiving ART in our clinical sites have varied by the year of ART initiation, with rates declining in recent years whereas mortality rates have remained stable. Further increases in site-level resources are likely to contribute to additional reductions in LTFU for patients initiating in subsequent years.

Determinants of virological response to antiretroviral therapy: socio-economic status still plays a role in the era of cART. Results from the ANRS-VESPA 2 study, France

BACKGROUND

Disparities in combined antiretroviral therapy (cART) outcomes have been consistently reported among people living with HIV (PLWHIV). The present study aims at investigating the mechanisms underlying those disparities among PLWHIV in France.

METHODS

We used data from the Vespa2 survey, a large national cross-sectional survey, representative of HIV-infected people followed at hospitals in 2011. Among participants diagnosed ≥1996, HIV treatment-naive at the time of cART initiation and on cART for at least 12 months, the frequency of sustained virological suppression (SVS; undetectable viral load [<50 copies/ml] for at least 6 months) at the time of the survey, was assessed and its social determinants were measured through logistic regression, accounting for clinical and biological determinants of response to cART.

RESULTS

Among 1,246 participants, 77.7% had achieved SVS. SVS was less frequent among those unemployed (0.6 [range 0.3-1.0]) and those with the lowest level of education (0.4 [range 0.2-0.9]). The late presenters, diagnosed at a CD4⁺ T-cell count <200/mm³ (0.5 [range 0.3-0.9]) and the late starters, diagnosed at a CD4⁺ T-cell count >200 but initiating cART at CD4⁺ T-cell count <200 (0.3 [range 0.1-0.8]) were less likely than the ideal starters (≥350 CD4⁺ T-cells/mm³ at cART initiation) to achieve SVS, as were those who reported suboptimal adherence versus those reporting optimal adherence (0.4 [range 0.2-0.7]). In bivariate analyses, material deprivation, discrimination and a weak social network were also associated with a poorer treatment response.

CONCLUSIONS

Structural social factors remain strong determinants of treatment response and should be addressed in a broad approach of care, but wider political issues should also be investigated.

Socioeconomic and clinical factors explaining the risk of unstructured antiretroviral therapy interruptions among Kenyan adult patients

A cross-sectional study was conducted to assess the extent of unstructured HIV treatment interruptions (TIs) and investigate the effects of socioeconomic, socio-demographic, HIV treatment-related and clinical factors on the magnitude and rate of the same among adult patients at a Kenyan regional referral center. Four hundred and twenty-one adult patients actively receiving antiretroviral therapy at Nyeri County Referral Hospital since 2003 were randomly selected to complete a health survey questionnaire. Electronic records were used to obtain their HIV treatment utilization history. The marginal effects of selected determinants on prevalence and rate of TI were assessed by fitting multiple Poisson log-linear regression models. In total, 392 patients participated in the study. HIV TI was prevalent with 64.5% having had at least one TI of 3 months or more during treatment. The risk of TI was significantly higher in those longer on treatment (prevalence ratio = 1.2, 95% confidence interval [CI] 1.12-1.28). Greater risk of TI was also associated with lower income (prevalence rate ratio [PRR] = 0.9, 95% CI 0.83-1.00), low medication adherence (PRR = 0.3, 95% CI 0.13-0.72), inconsistent treatment engagement (PRR = 0.4, 95% CI 0.19-0.75) and, contrarily, fewer adverse drug reactions (PRR = 0.9, 95% CI 0.90-0.97). Unstructured HIV TIs appear to be fairly common at the study site. The results suggest that efforts to minimize HIV TI could benefit from treatment-continuity monitoring strategies that target the high-risk sub-samples identified.

Could early antiretroviral therapy entail more risks than benefits in sub-Saharan African HIV-infected adults? A model-based analysis

BACKGROUND

Initiation of antiretroviral therapy (ART) in all HIV-infected adults, regardless of CD4⁺ T-cell count, is a proposed strategy for reducing HIV transmission. We investigated the conditions under which starting ART early could entail more risks than benefits for patients with high CD4⁺ T-cell counts.

METHODS

We used a simulation model to compare ART initiation upon entry to care ('immediate ART') to initiation at CD4⁺ T-cell count ≤ 350 cells/μl ('WHO 2010 ART') in African adults with CD4⁺ T-cell counts >500 cells/μl. We varied inputs to determine the combination of parameters (population characteristics, conditions of care, treatment outcomes) that would result in higher 15-year mortality with immediate ART.

RESULTS

The 15-year mortality was 56.7% for WHO 2010 ART and 51.8% for immediate ART. In one-way sensitivity analysis, lower 15-year mortality was consistently achieved with immediate ART unless the rate of fatal ART toxicity was >1.0/100 person-years, the rate of withdrawal from care was >1.2-fold higher or the rate of ART failure due to poor adherence was >4.3-fold higher on immediate than on WHO 2010 ART. In multi-way sensitivity analysis, immediate ART led to higher mortality when moderate rates of fatal ART toxicity (0.25/100 person-years) were combined with rates of withdrawal from care >1.1-fold higher and rates of treatment failure >2.1-fold higher on immediate than on WHO 2010 ART.

CONCLUSIONS

In sub-Saharan Africa, ART initiation at entry into care would improve long-term survival of patients with high CD4⁺ T-cell counts, unless it is associated with increased withdrawal from care and decreased adherence. In early ART trials, a focus on retention and adherence will be crucial.

Short-term and long-term clinical and immunological consequences of stopping antiretroviral therapy in HIV-infected patients with preserved immune function

BACKGROUND

The aim of this study was to assess the short-term and long-term consequences of stopping antiretroviral therapy (ART) in patients with preserved immune function.

METHODS

This was a randomized 144-week follow-up CD4⁺ T-cell-count-guided treatment-interruption trial. HIV-1-infected adults with plasma HIV-1 RNA<50 copies/ml, CD4⁺ T-cell count >500 cells/μl and nadir CD4⁺ T-cell count >100 cells/μl were randomized to continuous treatment (CT) or treatment interruption (TI) until CD4⁺ T-cell count decreased to <350 cells/μl. The primary end points were AIDS-defining illnesses, death, CD4⁺ T-cell count <200 cells/μl, or virological failure after restarting ART.

RESULTS

A total of 106 patients were included, 50 in the CT arm and 56 in the TI arm. A trend to a higher rate of primary end points was observed in the TI group (26.8% versus 14%, difference 12.8%, 95% CI -2.3, 27.8; P=0.105). In addition, 10 patients presented clinical events related with HIV rebound, including 8 cases of thrombocytopaenia. The CD4⁺ T-cell count significantly decreased in the TI group (even in patients with persistently high CD4⁺ T-cell counts and no clinical events) versus the CT group (median change -408 cells/μl versus -21.5 cells/μl; P<0.001), whereas a significant increase in CD8⁺ T-cell count was observed (256 cells/μl versus -59 cells/μl; P<0.001). The time to ART re-initiation was significantly associated with nadir and baseline CD4⁺ T-cell counts.

CONCLUSIONS

Discontinuation of ART in patients with preserved immune function is followed by significant immunological impairment even in those with no clinical events, and may be associated with an increased risk of HIV-related complications. Hence, patients who stop ART voluntarily should be closely monitored, regardless of their CD4⁺ T-cell count.

[Modeling of antiretroviral response from taxonomy of CD4 cells count trajectories in profound immunodeficiency setting]

Modeling of CD4 cells counts response was performed through a Non-Hierarchical-descendant process with profoundly immunocompromised symptomatic patients under nevirapine or efavirenz-based antiretroviral regimen in Abidjan. Similar CD4 cells count trajectories have been modelled in meta-trajectories linked to patients' classes. Global immunological response is similar between "nevirapine group" and "efavirenz group" but the model showed an internal variation of this response in each group. In the both groups, some variables presented a significant variation between classes: average CD4, CD4 Nadir, CD4 peak and average gain of CD4. In "nevirapine group", these following parameters vary significantly between classes: mean weight, mean haemoglobin count and mean increase in haemoglobin count and sex. It's also important to note that, all meta-trajectories began with distinctive categories of baseline CD4 cells counts. Other explanatory factors must be sought because the characteristics we have chosen to describe patients'classes, are not exhaustive.

Modelling the impact of treatment with individual antiretrovirals

PURPOSE OF REVIEW

The aim of this paper is to review the recent literature on HIV mathematical models that evaluate the effect of antiretroviral treatment on mortality, morbidity, HIV and other key outcomes. The focus of our attention is models which explicitly model specific effects of individual antiretroviral drugs.

RECENT FINDINGS

The number of studies that use mathematical models to evaluate the impact of antiretroviral drugs as a treatment or prevention strategy is increasing.Many mathematical models are deterministic compartmental models, and do not have the level of detail of specific effects of individual drugs. However, models that include specific antiretroviral drugs have been increasingly employed to assess the cost-effectiveness of prevention interventions, to evaluate benefits and harms (toxicities, side-effects, resistance development) of different regimens and different intervention timing and to predict long-term outcomes of randomized controlled trials (RCTs) that are not usually measured in the time frame of a trial.

SUMMARY

The number of models that consider specific antiretroviral drugs, with their own peculiarities, is limited. This factor is particularly the case for dynamic individual-based stochastic models. In order to address some research questions it is necessary to accurately take into consideration implications of toxicities, side-effects, and resistance acquisition, and hence to model specific drugs or at least specific drug classes.