Pretreatment CD4 Cell Slope and Progression to AIDS or Death in HIV-Infected Patients Initiating Antiretroviral Therapy—The CASCADE Collaboration: A Collaboration of 23 Cohort Studies

Background

CD4 cell count is a strong predictor of the subsequent risk of AIDS or death in HIV-infected patients initiating combination antiretroviral therapy (cART). It is not known whether the rate of CD4 cell decline prior to therapy is related to prognosis and should, therefore, influence the decision on when to initiate cART.

Methods and Findings

We carried out survival analyses of patients from the 23 cohorts of the CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) collaboration with a known date of HIV seroconversion and with at least two CD4 measurements prior to initiating cART. For each patient, a pre-cART CD4 slope was estimated using a linear mixed effects model. Our primary outcome was time from initiating cART to a first new AIDS event or death. We included 2,820 treatment-naïve patients initiating cART with a median (interquartile range) pre-cART CD4 cell decline of 61 (46–81) cells/µl per year; 255 patients subsequently experienced a new AIDS event or death and 125 patients died. In an analysis adjusted for established risk factors, the hazard ratio for AIDS or death was 1.01 (95% confidence interval 0.97–1.04) for each 10 cells/µl per year reduction in pre-cART CD4 cell decline. There was also no association between pre-cART CD4 cell slope and survival. Alternative estimates of CD4 cell slope gave similar results. In 1,731 AIDS-free patients with >350 CD4 cells/µl from the pre-cART era, the rate of CD4 cell decline was also not significantly associated with progression to AIDS or death (hazard ratio 0.99, 95% confidence interval 0.94–1.03, for each 10 cells/µl per year reduction in CD4 cell decline).

Conclusions

The CD4 cell slope does not improve the prediction of clinical outcome in patients with a CD4 cell count above 350 cells/µl. Knowledge of the current CD4 cell count is sufficient when deciding whether to initiate cART in asymptomatic patients. Please see later in the article for the Editors'' Summary     

Long-Term Survival in HIV Positive Patients with up to 15 Years of Antiretroviral Therapy

Background

Life expectancy has increased for newly diagnosed HIV patients since the inception of combination antiretroviral treatment (cART), but there remains a need to better understand the characteristics of long-term survival in HIV-positive patients. We examined long-term survival in HIV-positive patients receiving cART in the Australian HIV Observational Database (AHOD), to describe changes in mortality compared to the general population and to develop longer-term survival models.

Methods

Data were examined from 2,675 HIV-positive participants in AHOD who started cART. Standardised mortality ratios (SMR) were calculated by age, sex and calendar year across prognostic characteristics using Australian Bureau of Statistics national data as reference. SMRs were examined by years of duration of cART by CD4 and similarly by viral load. Survival was analysed using Cox-proportional hazards and parametric survival models.

Results

The overall SMR for all-cause mortality was 3.5 (95% CI: 3.0–4.0). SMRs by CD4 count were 8.6 (95% CI: 7.2–10.2) for CD4<350 cells/µl; 2.1 (95% CI: 1.5–2.9) for CD4 = 350–499 cells/µl; and 1.5 (95% CI: 1.1–2.0) for CD4≥500 cells/µl. SMRs for patients with CD4 counts <350 cells/µL were much higher than for patients with higher CD4 counts across all durations of cART. SMRs for patients with viral loads greater than 400 copies/ml were much higher across all durations of cART. Multivariate models demonstrated improved survival associated with increased recent CD4, reduced recent viral load, younger patients, absence of HBVsAg-positive ever, year of HIV diagnosis and incidence of ADI. Parametric models showed a fairly constant mortality risk by year of cART up to 15 years of treatment.

Conclusion

Observed mortality remained fairly constant by duration of cART and was modelled accurately by accepted prognostic factors. These rates did not vary much by duration of treatment. Changes in mortality with age were similar to those in the Australian general population.     

Risk of all-cause mortality in HIV infected patients is associated with clinical, immunologic predictors and the CCR5 Δ32 deletion

Objective

Investigation of the interplay between the CCR5 Δ32/wt genotype and demographic, epidemiological, clinical and immunological factors associated with mortality in the cART era.

Design

Longitudinal data from 507 HIV-infected patients following the Δ32 allele detection were analyzed.

Methods

Cumulative 15 years mortality was calculated using Kaplan-Meyer methodology. Hazard ratios were estimated using univariate Cox models. Basing on Akakie information criteria and statistical significance multivariate Cox model was constructed and effect plots presenting adjusted hazard ratio time-dependency were drawn. Analysis of the association of all-cause mortality and CCR5 Δ32/wt genotype prior to the antiretroviral treatment (cART) initiation (n = 507) and on the therapy (n = 422) was also performed.

Results

A mortality rate of 2.66 (CI 2.57–3.19) per 100 person-years was observed. Univariate analysis factors modifying the risk of death included the CCR5 genotype, gender, history of cART, AIDS diagnosis and also CD4 lymphocyte nadir, zenith, the latest CD4 count and stable levels >500 cells/µl. For multivariate analysis the following predictors were selected: CCR5 genotype (HR for wt/wt 2.53, CI 1.16–5.53, p = 0.02), gender (HR for males 1.91, 95%CI 1.1–3.36, p = 0.023), introduction of combined antiretroviral treatment (HR 4.85, CI 3.0–7.89, if untreated or treated <1 month, p<0.0001) CD4 count of 500 cells/µl for six months or more (HR 4.16, CI 1.95–8.88 if not achieved, p = 0.028), the latest CD4 count (HR 5.44, CI 3.39–8.74 for <100 cells/µl, p<0.0001) and history of AIDS (HR 1.69, CI 1.03–2.79, p = 0.039). Among untreated individuals the Δ32/wt genotype was associated with notably better survival (p = 0.026), while among cART treated individuals the Δ32 mutation did not correlate significantly with higher survival rates (p = 0.23).

Conclusions

The Δ32 CCR5 allele is associated with a reduction of the risk of all-cause mortality in HIV (+) patients alongside clinical and immunologic predictors such as AIDS, history of cART, lymphocyte CD4 cell count and gender.     

Immuno-Virological Discordance and the Risk of Non-AIDS and AIDS Events in a Large Observational Cohort of HIV-Patients in Europe

Background

The impact of immunosuppression despite virological suppression (immuno-virological discordance, ID) on the risk of developing fatal and non-fatal AIDS/non-AIDS events is unclear and remains to be elucidated.

Methods

Patients in EuroSIDA starting at least 1 new antiretroviral drug with CD4<350 cells/µl and viral load (VL)>500 copies/mL were followed-up from the first day of VL< = 50 copies/ml until a new fatal/non-fatal non-AIDS/AIDS event. Considered non-AIDS events included non-AIDS malignancies, pancreatitis, severe liver disease with hepatic encephalopathy (>grade 3), cardio- and cerebrovascular events, and end-stage renal disease. Patients were classified over time according to whether current CD4 count was above (non-ID) or below (ID) baseline level. Relative rates (RR) of events were calculated for ID vs. non-ID using adjusted Poisson regression models.

Results

2,913 patients contributed 11,491 person-years for the analysis of non-AIDS. 241 pre-specified non-AIDS events (including 84 deaths) and 89 AIDS events (including 10 deaths) occurred. The RR of developing pre-specified non-AIDS events for ID vs. non-ID was 1.96 (95% CI 1.37–2.81, p<0.001) in unadjusted analysis and 1.43 (0.94–2.17, p = 0.095) after controlling for current CD4 count. ID was not associated with the risk of AIDS events (aRR 0.76, 95% CI 0.41–1.38, p = 0.361).

Conclusion

Compared to CD4 responders, patients with immuno-virological discordance may be at increased risk of developing non-AIDS events. Further studies are warranted to establish whether in patients with ID, strategies to directly modify CD4 count response may be needed besides the use of ART.     

Population-Based CD4 Counts in a Rural Area in South Africa with High HIV Prevalence and High Antiretroviral Treatment Coverage

Background

Little is known about the variability of CD4 counts in the general population of sub-Saharan Africa countries affected by the HIV epidemic. We investigated factors associated with CD4 counts in a rural area in South Africa with high HIV prevalence and high antiretroviral treatment (ART) coverage.

Methods

CD4 counts, health status, body mass index (BMI), demographic characteristics and HIV status were assessed in 4990 adult resident participants of a demographic surveillance in rural KwaZulu-Natal in South Africa; antiretroviral treatment duration was obtained from a linked clinical database. Multivariable regression analysis, overall and stratified by HIV status, was performed with CD4 count levels as outcome.

Results

Median CD4 counts were significantly higher in women than in men overall (714 vs. 630 cells/µl, p<0.0001), both in HIV-uninfected (833 vs. 683 cells/µl, p<0.0001) and HIV-infected adults (384.5 vs. 333 cells/µl, p<0.0001). In multivariable regression analysis, women had 19.4% (95% confidence interval (CI) 16.1–22.9) higher CD4 counts than men, controlling for age, HIV status, urban/rural residence, household wealth, education, BMI, self-reported tuberculosis, high blood pressure, other chronic illnesses and sample processing delay. At ART initiation, HIV-infected adults had 21.7% (95% CI 14.6–28.2) lower CD4 counts than treatment-naive individuals; CD4 counts were estimated to increase by 9.2% (95% CI 6.2–12.4) per year of treatment.

Conclusions

CD4 counts are primarily determined by sex in HIV-uninfected adults, and by sex, age and duration of antiretroviral treatment in HIV-infected adults. Lower CD4 counts at ART initiation in men could be a consequence of lower CD4 cell counts before HIV acquisition.     

Among Patients with Sustained Viral Suppression in a Resource-Limited Setting,CD4 Gains Are Continuous Although Gender-Based Differences Occur

Introduction

There is conflicting data on long-term CD4 immune recovery after combination antiretroviral therapy (ART) in resource-limited settings. Virologic suppression is rarely documented in cohorts from sub-Saharan Africa so objective evidence of adherence is biologically unsubstantiated. We sought to investigate long-term patterns of immune recovery in Ugandan patients on ART with sustained viral suppression.

Methods

A prospective cohort of patients starting ART between April, 2004 and April, 2005 at the Infectious Diseases Institute with sustained viral suppression (viral load ≤400 copies/ml at month 6 and 12) while on first-line ART. Propensity scores were used to adjust for treatment allocation (nevirapine or efavirenz) at ART initiation. Data were analyzed using Kaplan Meier methods and cross-sectional time series regression.

Results

Three hundred and fifty-six patients were included in the analysis.71.6% were female, 87% in WHO stage 3 or 4, median age was 37 years, (IQR:32–43), and median CD4 count was 108 cells/µL, (IQR:35–174) at ART start. At multivariable analysis, lower immune recovery (measured by change in CD4 from ART start at each time interval) was associated with male-gender (-59, 95% CI: 90, -28, P<0.001), baseline CD4 count of 101–200 cells/µL (-35, 95% CI: 62, -9, P=0.009) and >200 (-64, 95% CI: 101, -26, P=0.001), and use of AZT at baseline (-47, 95% CI: -74, -20, P=0.001). Median time to reach >400 cells/µL was longer in males (197.4 weeks, IQR:119.9–312.0), compared to females (144.7 weeks, IQR:96.6–219.7, P<0.001). The cumulative probability of attaining CD4 >400 cells/µL over 7 years was higher in females compared to males (P<0.001).

Conclusions

There was long-term, continuous, immunologic recovery up to 7 years after ART initiation in an urban Ugandan cohort. Virologically suppressed women had better sustained immune recovery than men. Men take longer to immune reconstitute and have a lower probability of reaching a CD4 cell count >400 cells/µL. The biologic mechanisms of these gender differences need further exploration.     

Treatment Initiation,Program Attrition and Patient Treatment Outcomes Associated with Scale-Up and Decentralization of HIV Care in Rural Malawi

Objective

To describe patient antiretroviral therapy (cART) outcomes associated with intensive decentralization of services in a rural HIV program in Malawi.

Methods

Longitudinal analysis of data from HIV-infected patients starting cART between August 2001 and December 2008 and of a cross-sectional immunovirological assessment conducted 12 (±2) months after therapy start. One-year mortality, lost to follow-up, and attrition (deaths and lost to follow-up) rates were estimated with exact Poisson 95% confidence intervals (CI) by type of care delivery and year of initiation. Association of virological suppression (<50 copies/mL) and immunological success (CD4 gain ≥100 cells/µL), with type of care was investigated using multiple logistic regression.

Results

During the study period, 4322 cART patients received centralized care and 11,090 decentralized care. At therapy start, patients treated in decentralized health facilities had higher median CD4 count levels (167 vs. 130 cell/µL, P<0.0001) than other patients. Two years after cART start, program attrition was lower in decentralized than centralized facilities (9.9 per 100 person-years, 95% CI: 9.5–10.4 vs. 20.8 per 100 person-years, 95% CI: 19.7–22.0). One year after treatment start, differences in immunological success (adjusted OR = 1.23, 95% CI: 0.83–1.83), and viral suppression (adjusted OR = 0.80, 95% CI: 0.56–1.14) between patients followed at centralized and decentralized facilities were not statistically significant.

Conclusions

In rural Malawi, 1- and 2-year program attrition was lower in decentralized than in centralized health facilities and no statistically significant differences in one-year immunovirological outcomes were observed between the two health care levels. Longer follow-up is needed to confirm these results.     

Morbidity and Mortality According to Latest CD4+ Cell Count among HIV Positive Individuals in South Africa Who Enrolled in Project Phidisa

Background

Short-term morbidity and mortality rates for HIV positive soldiers in the South African National Defence Force (SANDF) would inform decisions about deployment and HIV disease management. Risks were determined according to the latest CD4+ cell count and use of antiretroviral therapy (ART) for HIV positive individuals in the SANDF and their dependents.

Methods and Findings

A total of 7,114 participants were enrolled and followed for mortality over a median of 4.7 years (IQR: 1.9, 7.1 years). For a planned subset (5,976), progression of disease (POD) and grade 4, potentially life-threatening events were also ascertained. CD4+ count and viral load were measured every 3 to 6 months. Poisson regression was used to compare event rates by latest CD4+ count (<50, 50–99, 100–199, 200–349, 350–499, 500+) with a focus on upper three strata, and to estimate relative risks (RRs) (ART/no ART). Median entry CD4+ was 207 cells/mm³. During follow-up over 70% were prescribed ART. Over follow-up 1,226 participants died; rates ranged from 57.6 (< 50 cells) to 0.8 (500+ cells) per 100 person years (py). Compared to those with latest CD4+ 200–349 (2.2/100py), death rates were significantly lower (p<0.001), as expected, for those with 350–499 (0.9/100py) and with 500+ cells (0.8/100py). The composite outcome of death, POD or grade 4 events occurred in 2,302 participants (4,045 events); rates were similar in higher CD4+ count strata (9.4 for 350–499 and 7.9 for 500+ cells) and lower than those with counts 200–349 cells (13.5) (p<0.001). For those with latest CD4+ 350+ cells, 63% of the composite outcomes (680 of 1,074) were grade 4 events.

Conclusion

Rates of morbidity and mortality are lowest among those with CD4+ count of 350 or higher and rates do not differ for those with counts of 350–499 versus 500+ cells. Grade 4 events are the predominant morbidity for participants with CD4+ counts of 350+ cells.     

Causes of Death among AIDS Patients after Introduction of Free Combination Antiretroviral Therapy (cART) in Three Chinese Provinces, 2010–2011

Introduction

Although AIDS-related deaths have had significant economic and social impact following an increased disease burden internationally, few studies have evaluated the cause of AIDS-related deaths among patients with AIDS on combination anti-retroviral therapy (cART) in China. This study examines the causes of death among AIDS-patients in China and uses a methodology to increase data accuracy compared to the previous studies on AIDS-related mortality in China, that have taken the reported cause of death in the National HIV Registry at face-value.

Methods

Death certificates/medical records were examined and a cross-sectional survey was conducted in three provinces to verify the causes of death among AIDS patients who died between January 1, 2010 and June 30, 2011. Chi-square analysis was conducted to examine the categorical variables by causes of death and by ART status. Univariate and multivariate logistic regression were used to evaluate factors associated with AIDS-related death versus non-AIDS related death.

Results

This study used a sample of 1,109 subjects. The average age at death was 44.5 years. AIDS-related deaths were significantly higher than non-AIDS and injury-related deaths. In the sample, 41.9% (465/1109) were deceased within a year of HIV diagnosis and 52.7% (584/1109) of the deceased AIDS patients were not on cART. For AIDS-related deaths (n = 798), statistically significant factors included CD4 count <200 cells/mm³ at the time of cART initiation (AOR 1.94, 95%CI 1.24–3.05), ART naïve (AOR 1.69, 95%CI 1.09–2.61; p = 0.019) and age <39 years (AOR 2.96, 95%CI 1.77–4.96).

Conclusion

For the AIDS patients that were deceased, only those who initiated cART while at a CD4 count ≥200 cells/mm3 were less likely to die from AIDS-related causes compared to those who didn’t initiate ART at all.     

Delay in cART Initiation Results in Persistent Immune Dysregulation and Poor Recovery of T-Cell Phenotype Despite a Decade of Successful HIV Suppression

Background

Successful combination antiretroviral therapy (cART) increases levels of CD4+ T-cells, however this increase may not accurately reflect long-term immune recovery since T-cell dysregulation and loss of T-cell homeostasis often persist. We therefore assessed the impact of a decade of effective cART on immune regulation, T-cell homeostasis, and overall T-cell phenotype.

Methods

We conducted a retrospective study of 288 HIV+ cART-naïve patients initiating therapy. We identified 86 individuals who received cART for at least a decade, of which 44 consistently maintained undetectable plasma HIV-RNA levels throughout therapy. At baseline, participants were classified into three groups according to pre-treatment CD4+ T-cell counts: Group I (CD4<200 cells/mm³); Group II (CD4: 200–350 cells/mm³); Group III (CD4>350 cells/mm³). Outcomes of interest were: (1) CD4+ T-cell count restoration (CD4>532 cells/mm³); (2) normalization of CD4:CD8 T-cell ratio (1.2–3.3); (3) maintenance of CD3+ T-cell homeostasis (CD3: 65%–85% of peripheral lymphocytes); (4) normalization of the complete T-cell phenotype (TCP).

Results

Despite a decade of sustained successful cART, complete T-cell phenotype normalization only occurred in 16% of patients, most of whom had initiated therapy at high CD4+ T-cell counts (>350 cells/mm³). The TCP parameter that was the least restored among patients was the CD4:CD8 T-cell ratio.

Conclusions

Failure to normalize the complete T-cell phenotype was most apparent in patients who initiated cART with a CD4+ T-cell count <200 cells/mm³. The impact of this impaired T-cell phenotype on life-long immune function and potential comorbidities remains to be elucidated.     

Blunted Response to Combination Antiretroviral Therapy in HIV Elite Controllers: An International HIV Controller Collaboration

Objective

HIV “elite controllers” (ECs) spontaneously control viral load, but some eventually require combination antiretroviral treatment (cART), due to a loss of viral control or a decline in CD4 T-cell counts. Here we studied the CD4 T-cell count dynamics after cART initiation among 34 ECs followed in U.S. and European cohorts, by comparison with chronically viremic patients (VIRs).

Methods

ECs were defined as patients with at least ≥5 viral load (VL) measurements below 400 copies/mL during at least a 5-year period despite never receiving ART and were selected from the French ANRS CO18 cohort, the U.S. SCOPE cohort, the International HIV Controllers study and the European CASCADE collaboration. VIRs were selected from the ANRS COPANA cohort of recently-diagnosed (<1 year) ART-naïve HIV-1-infected adults. CD4 T-cell count dynamics after cART initiation in both groups were modelled with piecewise mixed linear models.

Results

After cART initiation, CD4 T-cell counts showed a biphasic rise in VIRs with: an initial rapid increase during the first 3 months (+0.63/month), followed by +0.19/month. This first rapid phase was not observed in ECs, in whom the CD4Tc count increased steadily, at a rate similar to that of the second phase observed in VIRs. After cART initiation at a CD4 T-cell count of 300/mm³, the estimated mean CD4 T-cell gain during the first 12 months was 139/mm³ in VIRs and 80/mm³ in ECs (p = 0.048).

Conclusions

cART increases CD4 T-cell counts in elite controllers, albeit less markedly than in other patients.     

Using Plasma Viral Load to Guide Antiretroviral Therapy Initiation to Prevent HIV-1 Transmission

Background

Current WHO guidelines recommend antiretroviral therapy (ART) initiation at CD4 counts ≤350 cells/µL. Increasing this threshold has been proposed, with a primary goal of reducing HIV-1 infectiousness. Because the quantity of HIV-1 in plasma is the primary predictor of HIV-1 transmission, consideration of plasma viral load in ART initiation guidelines is warranted.

Methods

Using per-sex-act infectivity estimates and cross-sectional sexual behavior data from 2,484 HIV-1 infected persons with CD4 counts >350 enrolled in a study of African heterosexual HIV-1 serodiscordant couples, we calculated the number of transmissions expected and the number potentially averted under selected scenarios for ART initiation: i) CD4 count <500 cells/µL, ii) viral load ≥10,000 or ≥50,000 copies/mL and iii) universal treatment. For each scenario, we estimated the proportion of expected infections that could be averted, the proportion of infected persons initiating treatment, and the ratio of these proportions.

Results

Initiating treatment at viral load ≥50,000 copies/mL would require treating 19.8% of infected persons with CD4 counts >350 while averting 40.5% of expected transmissions (ratio 2.0); treating at viral load ≥10,0000 copies/mL had a ratio of 1.5. In contrast, initiation at CD4 count <500 would require treating 41.8%, while averting 48.4% (ratio 1.1).

Conclusion

Inclusion of viral load in ART initiation guidelines could permit targeting ART resources to HIV-1 infected persons who have a higher risk of transmitting HIV-1. Further work is needed to estimate costs and feasibility.     

CD4 Cell Count Trends after Commencement of Antiretroviral Therapy among HIV-Infected Patients in Tigray,Northern Ethiopia: A Retrospective Cross-Sectional Study

Background

The rate and extent of CD4 cell recovery varies widely among HIV-infected patients with different baseline CD4 cell count strata. The objective of the study was to assess trends in CD4 cell counts in HIV-infected patients after initiation of antiretroviral therapy in Tigray, Northern Ethiopia.

Methods

A retrospective cross-sectional study was conducted by reviewing medical records of HIV patients who received antiretroviral treatment at twenty health centers in Tigray region during 2008–2012. Multi-stage cluster sampling technique was employed to collect data, and the data were analyzed using SPSS version 20.0 software.

Results

The median change from baseline to the most recent CD4 cell count was +292 cells/μl. By 5 years, the overall median (inter-quartile range, IQR) CD4 cell count was 444(263-557) cells/μl while the median (IQR) CD4 cell count was 342(246-580) cells/μl among patients with baseline CD4 cell counts ≤200 cells/μl, 500(241-557) cells/μl among those with baseline CD4 cell counts of 201–350 cells/μl, and 652(537-767) cells/μl among those with baseline CD4 cell counts >350 cells/μl. Higher baseline CD4 cell counts and being male were independently associated with the risk of immunological non-response at 12 months. Furthermore, it was also investigated that these factors were significant predictors of subsequent CD4 cell recovery.

Conclusions

Patients with higher baseline CD4 cell stratum returned to normal CD4 Cell counts though they had an increased risk of immunological non-response at 12 months compared to those with the least baseline CD4 cell stratum. The findings suggest that consideration be given to initiation of HAART at a CD4 cell count >350 cells/μl to achieve better immune recovery, and to HIV-infected male patients to improve their health seeking behavior.     

Treatment Adherence and Health Outcomes in MSM with HIV/AIDS: Patients Enrolled in “One-Stop” and Standard Care Clinics in Wuhan China

Background

Conducted in Wuhan China, this study examined follow-up and health markers in HIV patients receiving care in two treatment settings. Participants, all men who have sex with men, were followed for18–24 months.

Method

Patients in a “one-stop” service (ACC; N = 89) vs those in standard care clinics (CDC; N = 243) were compared on HIV treatment and retention in care outcomes.

Results

Among patients with CD4 cell count ≦350 cells/µL, the proportion receiving cART did not differ across clinic groups. The ACC was favored across five other indicators: proportion receiving tests for CD4 cell count at the six-month interval (98.2% vs. 79.4%, 95% CI 13.3–24.3, p = 0.000), proportion with HIV suppression for patients receiving cART for 6 months (86.5% vs. 57.1%, 95% CI 14.1–44.7, p = 0.000), proportion with CD4 cell recovery for patients receiving cART for 12 months (55.8% vs. 22.2%, 95% CI 18.5–48.6, p = 0.000), median time from HIV confirmation to first test for CD4 cell count (7 days, 95% CI 4–8 vs. 10 days, 95% CI 9–12, log-rank p = 0.000) and median time from first CD4 cell count ≦350 cells/µL to cART initiation (26 days, 95% CI 16–37 vs. 41.5 days, 95% CI 35–46, log-rank p = 0.031). Clinic groups did not differ on any biomedical indicator at baseline, and no baseline biomedical or demographic variables remained significant in the multivariate analysis. Nonetheless, post-hoc analyses suggest the possibility of self-selection bias.

Conclusions

Study findings lend preliminary support to a one-stop patient-centered care model that may be useful across various HIV care settings.     

Clinical Prognostic Value of RNA Viral Load and CD4 Cell Counts during Untreated HIV-1 Infection—A Quantitative Review

Background

The prognostic value of CD4 counts and RNA viral load for identifying treatment need in HIV-infected individuals depends on (a) variation within and among individuals, and (b) relative risks of clinical progression per unit CD4 or RNA difference.

Methodology/Principal Findings

We reviewed these measurements across (a) 30 studies, and (b) 16 cohorts of untreated seropositive adults. Median within-population interquartile ranges were 74,000 copies/mL for RNA with no significant change during the course of infection; and 330 cells/µL for CD4, with a slight proportional increase over infection. Applying measurement and physiological fluctuations observed on chronically infected patients, we estimate that 45% of population-level variation in RNA, and 25% of variation in CD4, were due to within-patient fluctuations. Comparing a patient with RNA at upper 75^th centile with a patient at median RNA, 5-year relative risks were 1.4 (95% CI 1.2–1.7) for AIDS and 1.5 (1.3–1.9) for death, without change over the course of infection. In contrast, for a patient with CD4 count at the lower 75^th centile, relative risks increased from 1.0 at seroconversion to maxima of 6.3 (4.4–8.9) for AIDS and 5.5 (2.7–10.1) for death by year 6, when the population median had fallen to 300 cells/µL. Below 300 cells/µL, prognostic power did not increase, due to a narrower CD4 range.

Conclusions

Findings support the current WHO recommendation (used with clinical criteria) to start antiretroviral treatment in low-income settings at CD4 thresholds of 200–350 cells/µL, without pre-treatment RNA monitoring – while not precluding earlier treatment based on clinical, socio-demographic or public health criteria.     

Randomized trial of time-limited interruptions of protease inhibitor-based antiretroviral therapy (ART) vs. continuous therapy for HIV-1 infection

Background

The clinical outcomes of short interruptions of PI-based ART regimens remains undefined.

Methods

A 2-arm non-inferiority trial was conducted on 53 HIV-1 infected South African participants with viral load <50 copies/ml and CD4 T cell count >450 cells/µl on stavudine (or zidovudine), lamivudine and lopinavir/ritonavir. Subjects were randomized to a) sequential 2, 4 and 8-week ART interruptions or b) continuous ART (cART). Primary analysis was based on the proportion of CD4 count >350 cells(c)/ml over 72 weeks. Adherence, HIV-1 drug resistance, and CD4 count rise over time were analyzed as secondary endpoints.

Results

The proportions of CD4 counts >350 cells/µl were 82.12% for the intermittent arm and 93.73 for the cART arm; the difference of 11.95% was above the defined 10% threshold for non-inferiority (upper limit of 97.5% CI, 24.1%; 2-sided CI: −0.16, 23.1). No clinically significant differences in opportunistic infections, adverse events, adherence or viral resistance were noted; after randomization, long-term CD4 rise was observed only in the cART arm.

Conclusion

We are unable to conclude that short PI-based ART interruptions are non-inferior to cART in retention of immune reconstitution; however, short interruptions did not lead to a greater rate of resistance mutations or adverse events than cART suggesting that this regimen may be more forgiving than NNRTIs if interruptions in therapy occur.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00100646","term_id":"NCT00100646"}}NCT00100646     

Cost of Treatment in a US Commercially Insured,HIV-1–Infected Population

Objective

Recent treatment patterns and cost data associated with HIV in the United States are limited. This study assessed first-line persistence and healthcare costs of HIV-1 in patients by treatment line and CD4 cell count.

Methods

MarketScan Commercial Claims and Encounters Database (2007–2011) and Lab Database (2007–2010) were used to construct two HIV-1 cohorts: 1) newly treated HIV-1–infected patients with ≥6 months'' continuous enrollment prior to first third-agent drug claim (Newly Treated Cohort) and 2) CD4 cell count test results (CD4 Measurements Cohort). All patients were ≥18 years old and without hepatitis co-infection. The Kaplan-Meier method was used to measure treatment switch rates. Generalized linear models (gamma distribution, log link) were used to compare healthcare costs by treatment line and CD4 cell count controlling for potential confounders.

Results

Newly treated patients (n = 8,617) had mean age of 41, 82% were male, and 20% had experienced AIDS-defining events at baseline. Over 20% of newly treated patients switched initial treatment regimen within 2 years. Average unadjusted (and covariate-adjusted) total healthcare cost/year was $33,674 ($28,861) for first-line, $39,191 ($35,805) for second-line, and $39,882 ($40,804) for third-line treatment. Covariate-adjusted costs of care on second- and third-line treatments were significantly more expensive than first-line treatment (24% [p<0.001] and 41% [p = 0.006] higher, respectively). The CD4 Measurements Cohort included 803 CD4 measurements (mean age 49, 76% male, 8% experienced an AIDS-defining event). Costs associated with CD4 measurements <100 cells/µL were 92% higher than those with >350 cells/µL (p<0.001). For higher CD4 cell counts, the majority of expenditures were for antiretrovirals (64% of total for CD4 >350 cells/µL).

Conclusions

Despite modern advances in antiretroviral therapy and medical care, direct medical costs of HIV-1–infected patients increase after treatment switch and with lower CD4 counts, consistent with previous costing studies.     

No Association of Cryptococcal Antigenemia with Poor Outcomes among Antiretroviral Therapy-Experienced HIV-Infected Patients in Addis Ababa,Ethiopia

Introduction

There are limited data on clinical outcomes of ART-experienced patients with cryptococcal antigenemia. We assessed clinical outcomes of a predominantly asymptomatic, ART-experienced cohort of HIV+ patients previously found to have a high (8.4%) prevalence of cryptococcal antigenemia.

Methods

The study took place at All Africa Leprosy, Tuberculosis and Rehabilitative Training Centre and Black Lion Hospital HIV Clinics in Addis Ababa, Ethiopia. A retrospective study design was used to perform 12-month follow-up of 367 mostly asymptomatic HIV-infected patients (CD4<200 cells/µl) with high levels of antiretroviral therapy use (74%) who were previously screened for cryptococcal antigenemia. Medical chart abstraction was performed approximately one year after initial screening to obtain data on clinic visit history, ART use, CD4 count, opportunistic infections, and patient outcome. We evaluated the association of cryptococcal antigenemia and a composite poor outcome of death and loss to follow-up using logistic regression.

Results

Overall, 323 (88%) patients were alive, 8 (2%) dead, and 36 (10%) lost to follow-up. Among the 31 patients with a positive cryptococcal antigen test (titers ≥1∶8) at baseline, 28 were alive (all titers ≤1∶512), 1 dead and 2 lost to follow-up (titers ≥1∶1024). In multivariate analysis, cryptococcal antigenemia was not predictive of a poor outcome (aOR = 1.3, 95% CI 0.3–4.8). A baseline CD4 count <100 cells/µl was associated with an increased risk of a poor outcome (aOR 3.0, 95% CI 1.4–6.7) while an increasing CD4 count (aOR 0.1, 95% CI 0.1–0.3) and receiving antiretroviral therapy at last follow-up visit (aOR 0.1, 95% CI 0.02–0.2) were associated with a reduced risk of a poor outcome.

Conclusions

Unlike prior ART-naïve cohorts, we found that among persons receiving ART and with CD4 counts <200 cells/µl, asymptomatic cryptococcal antigenemia was not predictive of a poor outcome.     

Different Plasma Markers of Inflammation Are Influenced by Immune Recovery and cART Composition or Intensification in Treated HIV Infected Individuals

Background

HIV-1 infection increases plasma levels of inflammatory markers. Combination antiretroviral therapy (cART) does not restore inflammatory markers to normal levels. Since intensification of cART with raltegravir reduced CD8 T-cell activation in the Discor-Ral and IntegRal studies, we have evaluated the effect of raltegravir intensification on several soluble inflammation markers in these studies.

Methods

Longitudinal plasma samples (0–48 weeks) from the IntegRal (n = 67, 22 control and 45 intensified individuals) and the Discor-Ral studies (44 individuals with CD4 T-cell counts<350 cells/µl, 14 control and 30 intensified) were assayed for 25 markers. Mann-Whitney, Wilcoxon, Spearman test and linear mixed models were used for analysis.

Results

At baseline, different inflammatory markers were strongly associated with HCV co-infection, lower CD4 counts and with cART regimens (being higher in PI-treated individuals), but poorly correlated with detection of markers of residual viral replication. Although raltegravir intensification reduced inflammation in individuals with lower CD4 T-cell counts, no effect of intensification was observed on plasma markers of inflammation in a global analysis. An association was found, however, between reductions in immune activation and plasma levels of the coagulation marker D-dimer, which exclusively decreased in intensified patients on protease inhibitor (PI)-based cART regimens (P = 0.040).

Conclusions

The inflammatory profile in treated HIV-infected individuals showed a complex association with HCV co-infection, the levels of CD4 T cells and the cART regimen. Raltegravir intensification specifically reduced D-dimer levels in PI-treated patients, highlighting the link between cART composition and residual viral replication; however, raltegravir had little effect on other inflammatory markers.