Point-of-care CD4 testing to inform selection of antiretroviral medications in South African antenatal clinics: A cost-effectiveness analysis

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Study Justification:
The study aims to evaluate the cost-effectiveness of implementing point-of-care (POC) CD4 testing in South African antenatal clinics for the selection of antiretroviral medications in pregnant women with HIV. Currently, many prevention of mother-to-child HIV transmission (PMTCT) programs prioritize antiretroviral therapy (ART) for women with advanced HIV. POC CD4 testing may expedite the selection of three-drug ART instead of zidovudine, but it is costlier than traditional laboratory assays. This study seeks to determine if the higher initial cost of POC CD4 testing is offset by cost-savings from preventing pediatric HIV infection.
Highlights:
– The study used validated models of HIV infection to simulate pregnant, HIV-infected women and their infants in a South African antenatal clinic.
– Two strategies for CD4 testing were examined: laboratory testing and POC testing.
– The outcomes measured included the risk of mother-to-child HIV transmission, life expectancy for both mothers and infants, and healthcare costs.
– In the base case, POC testing led to lower projected mother-to-child HIV transmission risk, greater pediatric life expectancy, and lower lifetime costs compared to laboratory testing.
– POC testing improved clinical outcomes and reduced healthcare costs compared to laboratory testing.
Recommendations:
Based on the study findings, the following recommendations can be made:
– Antenatal clinics implementing Option A should consider implementing POC CD4 testing for the selection of antiretroviral medications.
– The higher initial cost of POC CD4 testing will be offset by cost-savings from preventing pediatric HIV infection.
Key Role Players:
To address the recommendations, the following key role players are needed:
– Antenatal clinic staff: to implement POC CD4 testing and ensure proper selection of antiretroviral medications.
– Laboratory technicians: to perform laboratory-based CD4 testing if POC testing is not available.
– Healthcare administrators: to allocate resources and budget for the implementation of POC CD4 testing.
Cost Items for Planning Recommendations:
When planning the implementation of POC CD4 testing, the following cost items should be considered (not actual cost but budget items):
– Cost of POC CD4 assays: estimated at $26 per test.
– Cost of laboratory-based CD4 assays: estimated at $14 per test.
– Training costs for healthcare workers on POC CD4 testing.
– Additional healthcare worker time for processing CD4 specimens, training, and quality control activities.
– Possible reduction in staff capacity to perform other patient-related activities.
– ANC costs, pediatric costs, and total costs over a 5-year horizon.
Please note that these cost items are estimates and may vary depending on the specific context and resources available.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on validated models of HIV infection and includes data from a pilot study. However, to improve the evidence, the abstract could provide more information on the sample size and demographics of the study population, as well as the statistical methods used to analyze the data.

Background Many prevention of mother-to-child HIV transmission (PMTCT) programs currently prioritize antiretroviral therapy (ART) for women with advanced HIV. Point-of-care (POC) CD4 assays may expedite the selection of three-drug ART instead of zidovudine, but are costlier than traditional laboratory assays. Methods We used validated models of HIV infection to simulate pregnant, HIV-infected women (mean age 26 years, gestational age 26 weeks) in a general antenatal clinic in South Africa, and their infants. We examined two strategies for CD4 testing after HIV diagnosis: laboratory (test rate: 96%, result-return rate: 87%, cost: $14) and POC (test rate: 99%, result-return rate: 95%, cost: $26). We modeled South African PMTCT guidelines during the study period (WHO “Option A”): antenatal zidovudine (CD4 ≤350/μL) or ART (CD4>350/μL). Outcomes included MTCT risk at weaning (age 6 months), maternal and pediatric life expectancy (LE), maternal and pediatric lifetime healthcare costs (2013 USD), and cost-effectiveness ($/lifeyear saved). Results In the base case, laboratory led to projected MTCT risks of 5.7%, undiscounted pediatric LE of 53.2 years, and undiscounted PMTCT plus pediatric lifetime costs of $1,070/infant. POC led to lower modeled MTCT risk (5.3%), greater pediatric LE (53.4 years) and lower PMTCT plus pediatric lifetime costs ($1,040/infant). Maternal outcomes following laboratory were similar to POC (LE: 21.2 years; lifetime costs: $23,860/person). Compared to laboratory, POC improved clinical outcomes and reduced healthcare costs. Conclusions In antenatal clinics implementing Option A, the higher initial cost of a one-time POC CD4 assay will be offset by cost-savings from prevention of pediatric HIV infection.

This work was approved by the Partners Healthcare Human Subjects Committee, Boston, MA, USA and the University of Cape Town IRB, Cape Town, South Africa. Participants at the study site in South Africa provided written informed consent for this work. In 2012, a point-of-care CD4 assay was introduced and evaluated in the Gugulethu Midwife Obstetric Unit (MOU), an antenatal clinic near Cape Town, South Africa (Appendix) [15]. We used data from this evaluation, with published clinical and cost data, to simulate a cohort of pregnant women identified as HIV-infected in antenatal care and their infants [13,14,21–24]. We linked three validated computer models: 1) a decision analytic model simulating a cohort of women through a single pregnancy and delivery (the “MTCT model”) [25–27]; 2) a Monte Carlo model of HIV disease among postpartum women (the Cost-effectiveness of Preventing AIDS Complications-International or “CEPAC-Adult model”) [28,29]; and 3) a Monte Carlo model of perinatal and postpartum HIV infection among HIV-exposed infants (the “CEPAC-Pediatric model”) [26,30]. Together, these three models simulate each mother-infant pair from the time of presentation to antenatal care (ANC) through the lifetimes of both mother and infant. We projected short- and long-term clinical and economic impacts for two CD4 testing strategies: flow cytometry performed in a central laboratory (“laboratory”), and point-of-care testing performed in the antenatal clinic (“POC”). Clinical outcomes included MTCT risk at birth and weaning, pediatric life expectancy from birth, maternal life expectancy from presentation to care, and combined (maternal+pediatric) life expectancy. Economic outcomes, from the healthcare system perspective, included ANC costs, lifetime maternal HIV-related healthcare costs, lifetime pediatric healthcare costs, and 1–5-year maternal and pediatric health care costs (2013 USD). We calculated incremental cost-effectiveness ratios (ICERs) in $/life-year (LY): difference in combined healthcare costs (antenatal+maternal+pediatric costs) between the two strategies divided by difference in combined projected life expectancy (maternal+pediatric life expectancy). For ICERs, all outcomes were discounted at 3%/year [31]. We considered a strategy to be “very cost-effective,” compared to the alternative strategy, if its ICER was <1x South African per-capita gross domestic product (GDP: $6,600 in 2013)/LY, “cost-effective” if the ICER was 350/μL when true CD4 is >350/μL). To be conservative with regard to the benefit of POC, we assumed in the base case that laboratory CD4 had 100% sensitivity and specificity to detect true CD4 ≤350/μL. b. In the base-case analysis, 13 weeks of antentatal AZT for non-ART eligible women are assumed in both strategies, based on median gestational age at booking in South Africa of 26 weeks. For ART-eligible women, 13 weeks of ART are assumed in the POC strategy and 3 weeks of AZT and 10 weeks of ART are assumed in the laboratory strategy. c. Please see S1 Table for description of assumptions of outpatient healthcare resource utilization. We simulated South African PMTCT guidelines at the time of the study, which reflected WHO Option A (lifelong maternal three-drug ART if CD4 ≤350/μL or WHO Stage 3–4 disease; maternal zidovudine (AZT) in pregnancy, then daily infant nevirapine (NVP) throughout breastfeeding if CD4 >350/μL; Fig. 1) [3,5]. In the antenatal period, we therefore modeled provision of AZT to women who were awaiting CD4 results (laboratory), who never received CD4 results (either strategy), or who received results indicating CD4>350/μL (either strategy). We modeled provision of antenatal three-drug ART to women who received results indicating CD4 ≤350/μL or who had evidence of WHO Stage 3–4 disease (either strategy). As a result, the model permits women with CD4 350/μL) based on 2010 WHO guidelines. The sensitivity and specificity of the CD4 assays are reflected in assigned probabilities that the CD4 test will indicate women to be eligible or non-eligible for ART. The observed CD4 results then determine whether women receive AZT or ART for PMTCT. Transmission probabilities and maternal outcomes depend on true CD4 count and PMTCT regimen received. Abbreviations: ANC: antenatal care; POC: point-of-care testing; ART: three-drug antiretroviral therapy; AZT: zidovudine. In the absence of data on infant feeding practices under recent South African guidelines, we modeled six months of breastfeeding for all infants [6]. After delivery, modeled women in both strategies linked to postnatal care, including routine laboratory-based CD4 monitoring. Women with initial or current CD4 ≤350/μL continued lifelong ART, and those with initial and current CD4 >350/μL stopped maternal AZT and provided daily nevirapine syrup to their infants until weaning [3,5]. To isolate the impact of the CD4 testing strategies, in the base case, we varied only CD4 testing rates, CD4 result-return rates, and CD4 assay costs. We otherwise assumed guideline-concordant care based on receipt of CD4 results: all women were accurately identified as HIV-infected, all mothers and infants adhered to prescribed PMTCT regimens, and all mothers and infants linked to postnatal HIV-related care, received ART if eligible after delivery, and were retained in care. To be conservative with regard to the benefit of POC, we assumed in the base case that laboratory CD4 had 100% sensitivity and specificity to detect true CD4 ≤350/μL, and that POC had 93% sensitivity and 86% specificity to detect true CD4 ≤350/μL (Table 1) [18]. We varied all of these assumptions in sensitivity analyses. We linked three computer models to simulate mother-infant pairs through pregnancy, breastfeeding, and the lifetimes of both mothers and infants (S1 Appendix; S1–S2 Figs.) [25–29,34]. At the time of presentation to ANC, mother-infant pairs enter the MTCT model, in which they face probabilities of key clinical events during pregnancy and delivery. MTCT model outcomes are assessed after delivery, and include maternal and infant vital status, infant HIV infection, and costs accrued during pregnancy and delivery. From delivery through death, clinical and economic outcomes are simulated for mothers in the CEPAC-Adult model and for infants in the CEPAC-Pediatric model. In these models, individuals are subject to monthly risks of clinical events, including opportunistic infections, response to ART, medication toxicities, and mortality, and the costs associated with these events (Appendix). We simulated the cohort of women seeking care at the Gugulethu MOU, with median age of 26 years and median gestational age at first visit of 26 weeks (Table 1, S1 Table) [13]. Monthly risks for opportunistic infections (OIs) and HIV-related death in the absence of ART were from Cape Town (adults) and from the International Epidemiologic Database for the Evaluation of AIDS (IeDEA; children) [30,35,36]. First-line ART was tenofovir/emtricitabine/efavirenz (TDF/FTC/EFV) for women and abacavir/lamivudine/lopinavir/ritonavir (ABC/3TC/LPV/r) for HIV-infected children [3,37–39]. Further details of ART initiation, CD4 and RNA responses to ART, and switching to second-line ART regimens are provided in the Appendix [40–44]. Modeled MTCT risks during pregnancy and breastfeeding, which substantially impact projected pediatric life expectancy, were the average values from published clinical studies in African breastfeeding populations, stratified by maternal CD4 count and ARV regimen received (Table 1, S1 Table, S1 Appendix) [26]. In sensitivity analyses, we also examined the impact of the highest and lowest published transmission risks for each regimen and CD4 stratum (S1 Appendix). We defined two key parameters for each CD4 testing strategy: the proportion of HIV-infected women undergoing CD4 testing, and the proportion of CD4-tested women receiving CD4 results and initiating three-drug ART if CD4 ≤350/μL (result-return, Table 1; result-return rates below 100% reflect the proportion of women lost to follow-up before receiving CD4 results). For the laboratory strategy, data for testing (96%) and result-return (87%) were from the Cape Town MOU [45]. For the POC testing strategy, data for testing (99%) and result-return (95%) were from the pilot study of POC CD4 measurement at the MOU [45]. Based on MOU data, we modeled a 3-week interval between CD4 testing and CD4 result-return for the laboratory strategy [14]. POC CD4 assay costs (base case: $26) were derived according to Larson et al., substituting healthcare worker time observations from the MOU and local salary data in place of the Larson estimates (Table 1, S1 Table) [21]. Laboratory-based CD4 assay costs (base case: $14) were from published data [22]. During pregnancy, we included the costs of routine antenatal care and delivery (Appendix). After delivery, we included maternal and pediatric costs for routine HIV-related healthcare, acute care for opportunistic infections, ART, laboratory monitoring, and care in the final month of life (Appendix) [22,35,46,47]. All costs were in 2013 US dollars. In previous work, we validated model-projected MTCT risk, pediatric survival, pediatric HIV-free survival, and maternal postpartum OI rates against published data, and we reported extensive sensitivity analyses on clinical, cost, and access-to-care parameters [25–28]. For this analysis, we examined additional variations in test sensitivity, specificity, testing rates, and result-return rates for the POC strategy, as well as antenatal and postnatal loss to follow-up (LTFU) rates, breastfeeding duration, healthcare and medication costs, MTCT risks, and the discount rate for both POC and laboratory strategies (S1 Table). We also examined both decreased POC CD4 costs, reflecting new POC assays in development, and increased POC CD4 costs, to incorporate possible costs not captured in the base-case estimate, for example: additional healthcare worker time to process CD4 specimens, undergo training, or conduct quality control activities; or reduction in staff capacity to perform other patient-related activities [21,48–50]. Finally, we conducted multiway sensitivity analyses, varying POC assay cost, sensitivity, testing rates, and result return rates simultaneously. In many settings, access to laboratory-based CD4 testing is more limited than in Cape Town, an urban area close to central laboratory facilities. We therefore examined a second, “low laboratory access scenario,” in which POC CD4 testing was introduced into a setting with a laboratory test rate (30%) and result-return rate (50%) based on UNAIDS data for low/middle-income countries [51]. To inform short-term budgets, we projected not only lifetime outcomes, but also outcomes over a 5-year horizon. Outcomes included ANC costs, pediatric costs, total costs, and yearly pediatric survival rates for both laboratory and POC strategies. Because variations in access to laboratory-based CD4 testing had the greatest impact on lifetime cost projections, we repeated the budget impact analysis in the “low laboratory access” scenario.

One innovation to improve access to maternal health is the use of point-of-care CD4 testing in antenatal clinics. This innovation allows for faster selection of antiretroviral medications for pregnant women with HIV, compared to traditional laboratory testing. The cost-effectiveness analysis showed that point-of-care CD4 testing led to lower mother-to-child HIV transmission risk, greater pediatric life expectancy, and lower overall healthcare costs compared to laboratory testing. This innovation can help improve access to maternal health by providing timely and accurate information for the selection of antiretroviral medications, ultimately preventing pediatric HIV infection.
AI Innovations Description
The recommendation to improve access to maternal health is to implement point-of-care CD4 testing in antenatal clinics. This recommendation is based on a cost-effectiveness analysis conducted in South African antenatal clinics. The analysis compared two strategies for CD4 testing after HIV diagnosis: laboratory testing and point-of-care testing.

The study found that point-of-care CD4 testing led to lower mother-to-child HIV transmission risk, greater pediatric life expectancy, and lower overall costs compared to laboratory testing. The point-of-care testing strategy had a higher initial cost, but the cost-savings from preventing pediatric HIV infection offset this cost.

The recommendation is to introduce point-of-care CD4 testing in antenatal clinics implementing Option A, which is the current PMTCT guideline in South Africa. This guideline prioritizes antiretroviral therapy for women with advanced HIV. Point-of-care CD4 testing can expedite the selection of three-drug antiretroviral therapy instead of zidovudine.

The study was approved by the Partners Healthcare Human Subjects Committee in Boston, MA, USA and the University of Cape Town IRB in Cape Town, South Africa. Participants at the study site in South Africa provided written informed consent. The study used data from a point-of-care CD4 assay evaluation conducted in an antenatal clinic near Cape Town.

The analysis used validated computer models to simulate a cohort of pregnant, HIV-infected women and their infants. The models projected short- and long-term clinical and economic impacts for the two CD4 testing strategies. Clinical outcomes included mother-to-child HIV transmission risk, pediatric life expectancy, and maternal life expectancy. Economic outcomes included antenatal care costs, lifetime maternal HIV-related healthcare costs, and lifetime pediatric healthcare costs.

The analysis calculated incremental cost-effectiveness ratios to determine the cost-effectiveness of the point-of-care CD4 testing strategy compared to the laboratory testing strategy. The strategy was considered “very cost-effective” if its incremental cost-effectiveness ratio was less than 1x South African per-capita gross domestic product (GDP) per life-year saved.

The study projected outcomes for a cohort of HIV-infected, ART-naive pregnant women and their infants in South Africa. It considered various assumptions and conducted sensitivity analyses to assess the robustness of the findings.

In summary, implementing point-of-care CD4 testing in antenatal clinics can improve access to maternal health by expediting the selection of appropriate antiretroviral therapy for pregnant women with HIV. This innovation can reduce mother-to-child HIV transmission risk, improve pediatric and maternal outcomes, and lead to cost-savings in the healthcare system.
AI Innovations Methodology
The study described in the provided text is a cost-effectiveness analysis of implementing point-of-care (POC) CD4 testing in South African antenatal clinics to improve access to antiretroviral medications for pregnant women with HIV. The aim of the study was to compare the clinical and economic outcomes of using POC CD4 testing versus traditional laboratory-based CD4 testing.

The methodology used in the study involved the simulation of a cohort of pregnant, HIV-infected women and their infants using validated computer models. Three computer models were linked together to simulate the progression of HIV infection and the impact of different CD4 testing strategies on maternal and pediatric outcomes. The models included a decision analytic model for simulating pregnancy and delivery, a Monte Carlo model for simulating HIV disease among postpartum women, and a Monte Carlo model for simulating perinatal and postpartum HIV infection among infants.

The study compared two CD4 testing strategies: laboratory-based testing and POC testing. The outcomes assessed included the risk of mother-to-child HIV transmission, maternal and pediatric life expectancy, lifetime healthcare costs, and cost-effectiveness.

The results of the study showed that implementing POC CD4 testing led to lower projected mother-to-child HIV transmission risk, greater pediatric life expectancy, and lower lifetime healthcare costs compared to laboratory-based testing. The study concluded that the higher initial cost of POC CD4 testing would be offset by cost-savings from the prevention of pediatric HIV infection.

In summary, the methodology used in the study involved the simulation of a cohort of pregnant, HIV-infected women and their infants using computer models. The study compared the clinical and economic outcomes of implementing POC CD4 testing versus laboratory-based testing in South African antenatal clinics. The results showed that POC testing was more cost-effective and led to better clinical outcomes compared to laboratory testing.

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