CD4 Cell Count Monitoring Research Articles

Prevalence, severity and associated risk factors of anemia among human immunodeficiency virus-infected adults in Sawla General Hospital, Southern Ethiopia: A facility-based cross-sectional study

Background Anemia is a significant public health problem in HIV/AIDS patients worldwide. This study is aimed to determine the prevalence of anemia and its risk factors among HIV-infected adults in Sawla General Hospital, southern Ethiopia. Methods A facility-based cross-sectional study involving HIV-infected adults was conducted in ART clinic of Sawla General Hospital from April 01 to May 31, 2019. A systematic random sampling technique was employed to recruit the study participants. Socio-demographic and clinical data were collected using a structured questionnaire and checklist. Hemoglobin concentration from venous blood was determined by HemoCue® 301 analyzer. Descriptive and inferential statistics, by Statistical Package for Social Science version 26.0, were applied; p-values ≤ 0.05 in the multivariable logistic regression analysis were considered statistically significant. Results A total of 220 HIV-infected adults participated in this study. The prevalence of anemia was 38.6%, from which 90.6, 7.1, and 2.3% are mild, moderate, and severe anemia, respectively. Anemia among HIV-infected adults was significantly associated with CD4 cell count below 200 cells/mm3 (AOR: 4.32; 95% CI: 2.10–8.86), clinical stage III or above (AOR: 4.20; 95% CI: 1.06–16.62), five or more years duration of HIV infection (AOR: 2.32; 95% CI: 1.08–4.94) and BMI below 18.5 kg/m2 (AOR: 3.82; 95% CI: 1.83–8.00). Conclusion Anemia is a moderate public health problem among the study population. Longer duration of HIV infection, advanced clinical stage, lower CD4 cell count, and BMI are risk factors for anemia. Therefore, early ART enrolment for HIV-infected adults with nutritional support and rigorous monitoring of CD4 cell count are essential to lower the prevalence.

Association between quality-of-care indicators for HIV infection and healthcare resource utilization and costs.

Multiple care quality indicators for HIV infection exist but few studies examine their impact on health outcomes. This study assessed which HIV care quality indicators were associated with healthcare resource utilization and costs. Retrospective analysis of Texas Medicaid claims data (01 January 2012 to 31 September 2016). Included patients had at least two HIV-related medical claims during the identification period (01 July 2012 to 31 August 2014) (index = date of first HIV claim), were 18-62 years at index, and were continuously enrolled in the 6-month pre-index and 1-year post-index periods. Dependent variables included emergency department (ED) visits, inpatient hospitalizations, prescription count, and all-cause healthcare costs. Independent variables included CD4 cell count monitoring, syphilis, chlamydia, gonorrhea, hepatitis B, hepatitis C, and tuberculosis screenings, influenza and pneumococcal vaccinations, retention in care, and HAART initiation. Covariates included age, chronic hepatitis C virus infection, AIDS diagnosis, sex, and baseline healthcare cost. The study objective was addressed using generalized linear modeling. CD4 cell count monitoring and HAART initiation were significantly associated with reduced emergency department visits (P < 0.0001 for each). Influenza vaccination was significantly associated with reduced inpatient hospitalization (P < 0.0001). CD4 cell count monitoring (P < 0.0001), TB screening (P = 0.0006), influenza vaccination (P < 0.0001), and HAART initiation (P < 0.0001) were significantly associated with increase prescription claims. CD4 cell count monitoring, TB screening, and HAART initiation (P < 0.0001 for each) were significantly associated with all-cause healthcare costs. HAART may reduce use of emergency care services as early as 1 year following initiation.

The Continuing Value of CD4 Cell Count Monitoring for Differential HIV Care and Surveillance.

The move toward universal provision of antiretroviral therapy and the expansion of HIV viral load monitoring call into question the ongoing value of CD4 cell count testing and monitoring. We highlight the role CD4 monitoring continues to have in guiding clinical decisions and measuring and evaluating the epidemiology of HIV. To end the HIV/AIDS epidemic, we require strategic information, which includes CD4 cell counts, to make informed clinical decisions and effectively monitor key surveillance indicators.

A superiority of viral load over CD4 cell count when predicting mortality in HIV patients on therapy

BackgroundCD4 cell count has been identified to be an essential component in monitoring HIV treatment outcome. However, CD4 cell count monitoring sometimes fails to predict virological failure resulting in unnecessary switch of treatment lines which causes drug resistance and limitations of treatment options. This study assesses the use of both viral load (HIV RNA) and CD4 cell count in the monitoring of HIV/AIDS progression.MethodsTime-homogeneous Markov models were fitted, one on CD4 cell count monitoring and the other on HIV RNA monitoring. Effects of covariates; gender, age, CD4 baseline, HIV RNA baseline and adherence to treatment were assessed for each of the fitted models. Assessment of the fitted models was done using prevalence plots and the likelihood ratio tests. The analysis was done using the “msm” package in R.ResultsResults from the analysis show that viral load monitoring predicts deaths of HIV/AIDS patients better than CD4 cell count monitoring. Assessment of the fitted models shows that viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count.ConclusionFrom this study one can conclude that although patients take more time to achieve a normal CD4 cell count and less time to achieve an undetectable viral load, once the CD4 cell count is normal, mortality risks are reduced. Therefore, both viral load monitoring and CD4 count monitoring can be used to provide useful information which can be used to improve life expectance of patients living with HIV. However, viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count and hence viral load is deemed superior.

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.

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

Safe Reduction in CD4 Cell Count Monitoring in Stable, Virally Suppressed Patients With HIV Infection or HIV/Hepatitis C Virus Coinfection.

It has been suggested that routine CD4 cell count monitoring in human immunodeficiency virus (HIV)-monoinfected patients with suppressed viral loads and CD4 cell counts >300 cell/μL could be reduced to annual. HIV/hepatitis C virus (HCV) coinfection is frequent, but evidence supporting similar reductions in CD4 cell count monitoring is lacking for this population. We determined whether CD4 cell count monitoring could be reduced in monoinfected and coinfected patients by estimating the probability of maintaining CD4 cell counts ≥200 cells/µL during continuous HIV suppression. The PISCIS Cohort study included data from 14 539 patients aged ≥16 years from 10 hospitals in Catalonia and 2 in the Balearic Islands (Spain) since January 1998. All patients who had at least one period of 6 months of continuous HIV suppression were included in this analysis. Cumulative probabilities with 95% confidence intervals were calculated using the Kaplan-Meier estimator stratified by the initial CD4 cell count at the period of continuous suppression initiation. A total of 8695 patients were included. CD4 cell counts fell to <200 cells/µL in 7.4% patients, and the proportion was lower in patients with an initial count >350 cells/µL (1.8%) and higher in those with an initial count of 200-249 cells/µL (23.1%). CD4 cell counts fell to <200 cells/µL in 5.7% of monoinfected and 11.1% of coinfected patients. Of monoinfected patients with an initial CD4 cell count of 300-349 cells/µL, 95.6% maintained counts ≥200 cells/µL. In the coinfected group with the same initial count, this rate was lower, but 97.6% of coinfected patients with initial counts >350 cells/µL maintained counts ≥200 cells/µL. From our data, it can be inferred that CD4 cell count monitoring can be safely performed annually in HIV-monoinfected patients with CD4 cell counts >300 cells/µL and HIV/HCV-coinfected patients with counts >350 cells/µL.

Effects of CD4 Cell Counts and Viral Load Testing on Mortality Rates in Patients With HIV Infection Receiving Antiretroviral Treatment: An Observational Cohort Study in Rural Southwest China.

Recent studies have suggested that CD4 cell count monitoring has little added value in patients who are virologically suppressed and immunologically stable if viral load (VL) testing is routinely available. These conclusions have not been directly assessed using mortality rate as a study end point in a real-world setting. This human immunodeficiency virus (HIV) treatment cohort study from 2008 to 2014 was conducted in Guangxi, China. We used a Cox regression model to analyze associations between the frequency of CD4 cell counts and VL testing and death. Compared with monitoring CD4 cell counts ≥3 times during the first year of antiretroviral therapy (ART) initiation, as currently suggested by the Chinese National Free Antiretroviral Treatment Program, monitoring them less than twice during the first year of ART was significantly associated with death; however, monitoring them twice in that year did not significantly increase mortality rates. Compared with testing VL at least once during the first year of ART, as currently suggested by the National Free Antiretroviral Treatment Program, performing no VL tests in the first year after ART initiation was significantly associated with higher mortality rates. Routine CD4 cell count monitoring did not have an impact on mortality rates among HIV-infected patients with VLs <1000 copies/mL or CD4 cell counts ≥350/μL beyond 12 months after ART initiation. Our study suggests that CD4 cell counts can be reduced to twice during the first year of ART and be reduced or stopped for patients who have achieved virologic suppression or immunologic stability after 12 months of treatment.

No differences in clinical outcomes with the addition of viral load testing to CD4 cell count monitoring among HIV infected participants receiving ART in rural Uganda: Long-term results from the Home Based AIDS Care Project.

BackgroundWe compared clinical outcomes among HIV-infected participants receiving ART who were randomized to viral load (VL) and CD4 cell count monitoring in comparison to CD4 cell count monitoring alone in Tororo, Uganda.MethodsBeginning in May 2003, participants with CD4 cell counts <250 cells/μL or WHO stage 3 or 4 disease were randomized to clinical monitoring alone, clinical monitoring plus quarterly CD4 cell counts (CD4-only); or clinical monitoring, quarterly CD4 cell counts and quarterly VL testing (CD4-VL). In 2007, individuals in clinical monitoring arm were re-randomized to the other two arms and all participants were followed until March 31, 2009. We used Cox Proportional Hazard models to determine if study arm was independently associated with the development of opportunistic infections (OIs) or death.ResultsWe randomized 1211 participants to the three original study arms and 331 surviving participants in the clinical monitoring arm were re-randomized to the CD4-VL and CD4 only arms. At enrolment the median age was 38 years and the median CD4 cell count was 134 cells/μL. Over a median of 5.2 years of follow-up, 37 deaths and 35 new OIs occurred in the VL-CD4 arm patients, 39 deaths and 42 new OIs occurred in CD4-only patients. We did not observe an association between monitoring arm and new OIs or death (AHR =1.19 for CD4-only vs. CD4-VL; 95 % CI 0.82–1.73).ConclusionWe found no differences in clinical outcomes associated with the addition of quarterly VL monitoring to quarterly CD4 cell count monitoring.

The Impact of Different CD4 Cell-Count Monitoring and Switching Strategies on Mortality in HIV-Infected African Adults on Antiretroviral Therapy: An Application of Dynamic Marginal Structural Models.

In Africa, antiretroviral therapy (ART) is delivered with limited laboratory monitoring, often none. In 2003–2004, investigators in the Development of Antiretroviral Therapy in Africa (DART) Trial randomized persons initiating ART in Uganda and Zimbabwe to either laboratory and clinical monitoring (LCM) or clinically driven monitoring (CDM). CD4 cell counts were measured every 12 weeks in both groups but were only returned to treating clinicians for management in the LCM group. Follow-up continued through 2008. In observational analyses, dynamic marginal structural models on pooled randomized groups were used to estimate survival under different monitoring-frequency and clinical/immunological switching strategies. Assumptions included no direct effect of randomized group on mortality or confounders and no unmeasured confounders which influenced treatment switch and mortality or treatment switch and time-dependent covariates. After 48 weeks of first-line ART, 2,946 individuals contributed 11,351 person-years of follow-up, 625 switches, and 179 deaths. The estimated survival probability after a further 240 weeks for post-48-week switch at the first CD4 cell count less than 100 cells/mm3 or non-Candida World Health Organization stage 4 event (with CD4 count <250) was 0.96 (95% confidence interval (CI): 0.94, 0.97) with 12-weekly CD4 testing, 0.96 (95% CI: 0.95, 0.97) with 24-weekly CD4 testing, 0.95 (95% CI: 0.93, 0.96) with a single CD4 test at 48 weeks (baseline), and 0.92 (95% CI: 0.91, 0.94) with no CD4 testing. Comparing randomized groups by 48-week CD4 count, the mortality risk associated with CDM versus LCM was greater in persons with CD4 counts of <100 (hazard ratio = 2.4, 95% CI: 1.3, 4.3) than in those with CD4 counts of ≥100 (hazard ratio = 1.1, 95% CI: 0.8, 1.7; interaction P = 0.04). These findings support a benefit from identifying patients immunologically failing first-line ART at 48 weeks.

Prevalence, incidence and predictors of peripheral neuropathy in African adults with HIV infection within the DART trial.

We investigated the prevalence, incidence and predictors of new peripheral neuropathy episodes in previously untreated, symptomatic HIV-infected Ugandan/Zimbabwean adults initiating zidovudine-based antiretroviral therapy (ART). An open-label, multicentre, randomized trial. Peripheral neuropathy was self-reported at 12-weekly clinic visits. Cox regression models (excluding participants reporting preexisting peripheral neuropathy at ART initiation), considered sex; pre-ART WHO stage, age and CD4(+) cell count; CD4(+) cell count versus no CD4(+) cell count monitoring; and time-updated CD4(+) cell count, weight and use of stavudine, isoniazid and didanosine. Four hundred and twenty-one out of 3316(13%) patients reported preexisting peripheral neuropathy at ART initiation. Median (interquartile range, IQR) follow-up in 2895 participants without preexisting peripheral neuropathy was 4.9 (4.7-5.4) years. Three hundred and fifty-four (12%) took stavudine as first-line substitution and 518 (18%) took isoniazid during follow-up. Two hundred and ninety (11%) participants developed a new peripheral neuropathy episode, an incidence of 2.12 per 100 person-years. Eighteen (0.1%) had a grade 3/4 episode. Independent predictors of peripheral neuropathy were current stavudine use [adjusted hazard ratio (a)HR 4.16 (95% confidence interval, 95% CI 3.06-5.66], current isoniazid use [aHR 1.59 (95% CI 1.02-2.47)] and current didanosine use [aHR 1.60 (95% CI 1.19-2.14)]. Higher risks were independently associated with higher pre-ART weight [aHR (per+5 kg) 1.07 (95% CI 1.01-1.13)] and older age aHR (per 10 years older) 1.29 (95% CI 1.12-1.49), but there was no significant effect of sex (P = 0.13), pre-ART CD4(+) cell count (P = 0.91) or CD4(+) cell count monitoring (P = 0.73). Current stavudine, didanosine or isoniazid use continue to increase peripheral neuropathy risks, as does older age and weight at ART initiation; however, we found no evidence of increased risk in women in contrast to previous studies. The incidence of peripheral neuropathy may now be lower in ART programmes, as stavudine and didanosine are no longer recommended. All patients receiving isoniazid, either as part of antituberculosis (TB) chemotherapy or TB-preventive therapy, should receive pyridoxine as recommended in national guidelines.

Routine CD4 cell count monitoring seldom contributes to clinical decision-making on antiretroviral therapy in virologically suppressed HIV-infected patients.

In Australia, CD4 cell count is monitored approximately every 6 months in HIV-infected patients during antiretroviral therapy (ART). The aim of this study was to determine if routine CD4 monitoring contributed to decisions on changes to ART, and to estimate how reduced CD4 monitoring could contribute to cost savings in Australia. We conducted a retrospective cohort analysis investigating all HIV-infected patients who attended the Melbourne Sexual Health Centre (MSHC) in Australia from 1 April 2011 to 1 October 2013. We reviewed the electronic medical records of all patients who changed or stopped antiretroviral regimens during this time period to determine whether CD4 cell count could have contributed to this clinical decision. Among 1004 patients with HIV infection on ART, none [95% confidence interval (CI) 0-2.3%] of the 162 clinical decisions to change or stop treatment were influenced by CD4 cell counts. Reducing the current biannual CD4 monitoring strategy to annually could potentially save ∼AU$ 1.5 million (US$ 1.4 million) each year in Australia [i.e. ∼AU$ 74 700 (US$ 67 700) could be saved per 1000 HIV-infected patients during ART]. Routine CD4 monitoring in HIV-infected patients during ART could be reduced from biannually to annually, as it rarely influences clinical decisions in patients' management. Not only could this avoid patients being unnecessarily anxious about normal fluctuations in their CD4 counts but it would also result in cost savings.

Relationship between CD4 cell count and serious long-term complications among HIV-positive individuals

To summarize recent findings on the relationship between CD4 cell count metrics and selected serious clinical outcomes, and to deduce implications for CD4 cell count monitoring in treated HIV infection and the timing of combination antiretroviral therapy initiation. In treated HIV infection, a higher latest CD4 cell count is associated with a lower short-term risk of serious non-AIDS events (often composite endpoints) even in CD4 cell count strata more than 350/μl. Knowledge of alternate CD4 cell count metrics, such as CD4 cell count slope, nadir level and time spent under specific CD4 cell count thresholds, does not seem to confer additional prognostic information beyond that achieved by current CD4 cell count. Latest CD4 cell count is strongly associated with a short-term risk of infection-related non-AIDS malignancies, and serious hepatic events; however, the evidence is inconsistent for cardiovascular outcomes. Studies vary significantly in definitions of composite endpoints as well as the rigorousness of outcome ascertainment, which could explain the heterogeneity in results. Current CD4 cell count, but not other metrics, could be an important clinical tool to predict the short-term risk of serious non-AIDS events in treated HIV-positive individuals. An earlier initiation of therapy at CD4 cell count more than 350/μl or above 500/μl is likely to improve long-term CD4 cell count metrics. Whether it provides net individual clinical benefit requires a randomized trial.

Cost-effectiveness of different strategies to monitor adults on antiretroviral treatment: a combined analysis of three mathematical models.

WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6-12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per μL, and then at a CD4 cell count lower than 500 cells per μL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. Bill & Melinda Gates Foundation, WHO.

Cost-effectiveness of point-of-care viral load monitoring of antiretroviral therapy in resource-limited settings

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. Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. 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. 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. 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.

Monitoring of HIV viral load, CD4 cell count, and clinical assessment versus clinical monitoring alone for antiretroviral therapy in low-resource settings (Stratall ANRS 12110/ESTHER): a cost-effectiveness analysis

In low-income countries, the use of laboratory monitoring of patients taking antiretroviral therapy (ART) remains controversial in view of persistent resource constraints. The Stratall trial did not show that clinical monitoring alone was non-inferior to laboratory and clinical monitoring in terms of immunological recovery. We aimed to evaluate the costs and cost-effectiveness of the ART monitoring approaches assessed in the Stratall trial. The randomised, controlled, non-inferiority Stratall trial was done in a decentralised setting in Cameroon. Between May 23, 2006, and Jan 31, 2008, ART-naive adults were randomly assigned (1:1) to clinical monitoring (CLIN) or viral load and CD4 cell count plus clinical monitoring (LAB) and followed up for 24 months. We calculated costs, number of life-years saved (LYS), and incremental cost-effectiveness ratios (ICERs) with data from patients who had been followed up for at least 6 months. We considered two cost scenarios in which viral load plus CD4 cell count tests cost either US$95 (scenario 1; Abbott RealTime HIV-1 assay) or $63 (scenario 2; generic assay). We compared ICERs with a WHO-recommended threshold of three times the per-person gross domestic product (GDP) for Cameroon ($3670-3800) and an alternative lower threshold of $2385 to determine cost-effectiveness. We assessed uncertainty with one-way sensitivity analyses and cost-effectiveness acceptability curves. 188 participants who underwent LAB and 197 who underwent CLIN were followed up for at least 6 months. In scenario 1, LAB increased costs by a mean of $489 (SD 430) per patient and saved 0·103 life-years compared with CLIN (ICER of $4768 [95% CI 3926-5613] per LYS). In scenario 2, the incremental mean cost of LAB was $343 (SD 425) -ie, an ICER of $3339 (2507-4173) per LYS. A combined strategy in which LAB would only be used in patients starting ART with a CD4 count of 200 cells per μL or fewer suggests that 0·120 life-years would be saved at an additional cost of $259 per patient in scenario 1 (ICER of $2167 [95% CI 1314-3020] per LYS) and $181 in scenario 2 (ICER of $1510 [692-2329] per LYS) when compared with CLIN. Laboratory monitoring was not cost effective in 2006-10 compared with clinical monitoring when the Abbott RealTime HIV-1 assay was used according to the $3670 cost-effectiveness threshold (three times per-person GDP in Cameroon), but it might be cost effective if a generic in-house assay is used. French National Agency for Research on AIDS and Viral Hepatitis (ANRS) and Ensemble pour une Solidarité Thérapeutique Hospitalière En Réseau (ESTHER).

Monitoring of Antiretroviral Therapy and Mortality in HIV Programmes in Malawi, South Africa and Zambia: Mathematical Modelling Study

ObjectivesMortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference.Design:Mathematical modelling study based on data from ART programmes.MethodsWe used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained.ResultsRRs comparing VL with CD4 cell count monitoring were 0.94 (0.74–1.03) in scenario A, 0.94 (0.77–1.02) with delayed switching (scenario B) and 0.80 (0.44–1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality.ConclusionsVL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.

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Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa

In low-income settings, treatment failure is often identified using CD4 cell count monitoring. Consequently, patients remain on a failing regimen, resulting in a higher risk of transmission. We investigated the benefit of routine viral load monitoring for reducing HIV transmission. Mathematical model. We developed a stochastic mathematical model representing the course of individual viral load, immunological response and survival in a cohort of 1000 HIV-infected patients receiving antiretroviral therapy (ART) in southern Africa. We calculated cohort viral load (CVL; sum of individual viral loads) and used a mathematical relationship between individual viral load values and transmission probability to estimate the number of new HIV infections. Our model was parameterized with data from the International epidemiologic Databases to Evaluate AIDS Southern African collaboration. Sensitivity analyses were performed to assess the validity of the results in a universal 'test and treat' scenario, wherein patients start ART earlier after HIV infection. If CD4 cell count alone was regularly monitored, the CVL was 2.6 × 10 copies/ml and the treated patients transmitted on average 6.3 infections each year. With routine viral load monitoring, both CVL and transmissions were reduced by 31% to 1.7 × 10 copies/ml and 4.3 transmissions, respectively. The relative reduction of 31% between monitoring strategies remained similar for different scenarios. Although routine viral load monitoring enhances the preventive effect of ART, the provision of ART to everyone in need should remain the highest priority.

CD4 cell count and viral load monitoring in patients undergoing antiretroviral therapy in Uganda: cost effectiveness study

Objective To examine the cost and cost effectiveness of quarterly CD4 cell count and viral load monitoring among patients taking antiretroviral therapy (ART).Design Cost effectiveness study.Setting A randomised trial in...

Development and Validation of Decision Rules to Guide Frequency of Monitoring CD4 Cell Count in HIV-1 Infection before Starting Antiretroviral Therapy

BackgroundAlthough CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study.Methodology/Principal FindingsWe built up two prediction rules (“Snap-shot rule” for a single sample and “Track-shot rule” for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or <5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200×106/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold.Conclusions/SignificanceFrequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count >650 for a threshold of 200, >900 for 350, or >1150 for 500×106/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.