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Comparison of guidelines for HIV viral load monitoring among pregnant and breastfeeding women in sub-Saharan Africa

Lesosky, Maiaa; Raboud, Janet M.b; Glass, Tracya; Brummel, Sean S.c; Ciaranello, Andrea L.d; Currier, Judith S.e; Essajee, Shaffiqf; Havlir, Diane V.g; Koss, Catherine A.g; Ogwu, Anthonyh; Shapiro, Roger L.i; Abrams, Elaine J.j; Myer, Landona

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doi: 10.1097/QAD.0000000000002400
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Abstract

Introduction

Lifelong antiretroviral therapy (ART) to suppress HIV viral load is the critical intervention to support the long-term health of women living with HIV while preventing both sexual and perinatal transmission. However, high levels of suboptimal ART adherence, disengagement from care and elevated viral load have been widely documented among pregnant and postpartum women living with HIV globally [1–3]. Because of the risks of both vertical and horizontal transmission associated with HIV viraemia during pregnancy and breastfeeding, raised maternal viral load during these periods requires rapid detection and intervention within ART programs. For low-income and middle-income countries, viral load monitoring has only recently entered national policies [4,5]; several policies call for viral load monitoring annually in HIV-infected adults on ART, with an additional viral load test 4–6 months after ART initiation to monitor initial adherence [5]. Although intensified viral load monitoring for pregnant and breastfeeding women has been proposed in some recommendations [5], it has not yet been evaluated systematically. To address this gap, we evaluated a selection of available viral load monitoring guidelines and estimated the percentage of women likely to be detected with raised viral load during pregnancy or breastfeeding.

Methods

We used an individual Monte Carlo simulation, based on earlier models [6,7], to describe longitudinal ART adherence, viral load and vertical transmission risk from conception until 2 years postpartum in a hypothetical cohort of 10 000 HIV-infected women. The model simulates ART use and adherence, uses this to simulate viral load and then bases in utero, intrapartum and breastfeeding transmission risks on viral load within individual women on a weekly time step, and allows for variations in the proportions of women conceiving on ART or initiating ART during pregnancy; gestational age at entry to antenatal care (and from this, duration of ART before delivery among women initiating ART in pregnancy), gestation at delivery and duration of breastfeeding.

ART use and adherence among women on ART are the primary drivers of changes in viral load in the absence of drug resistance. ART adherence is modeled using a combination of population and individual level parameters: the model allows settings for the population proportion in each of three adherence classes at entry (nonadherent, partially adherent or fully adherent), with individual adherence allowed to vary weekly depending on the class of adherence at entry, previous intraindividual adherence, gestational age or time postpartum, infant feeding practices and additional stochastic noise. Viral load values change in response to weekly ART adherence levels, with both magnitude of change and additional noise depending on current viral load levels. For example, decreasing levels of adherence will result in increasing viral load values, with (on average) larger changes as the viral load value is larger. The model was calibrated using available data from countries across sub-Saharan Africa, including MCH-ART [8,9], Mma-Bana [10], PROMISE (IMPAACT 1077BF) [11] and PROMOTE [12].

Input parameters relevant to this analysis include the distributions of: gestational age at entry into antenatal care [set at a median 22 weeks’ gestation (IQR 16–28)], gestational age at delivery (set at a median of 38 weeks (IQR 37–40)] and breastfeeding duration [set at median duration of 40 weeks (IQR 29–49)]. We assumed that 50% of women initiated ART during pregnancy [at the time of antenatal care (ANC) entry] and 50% were receiving ART prior to conception; among those on ART prior to conception, 70% had viral load less than 50 copies/ml at entry into antenatal care. For this analysis, no lost to follow-up or maternal or foetal loss was included.

Guidelines were selected for inclusion on the basis of being representative of recent guidelines used in sub-Saharan African countries and nonoverlapping in terms of monitoring strategies; US Department of Health and Human Services (DHHS) and WHO guidelines were also selected for comparison. Guidelines included in this analysis were South Africa 2015 [5], Malawi 2016 [13], Kenya 2016 [14], Zambia 2018 [15], the WHO 2016 consolidated guidelines [4] and the 2018 US DHHS guidelines [16]. The monitoring schedule in the guidelines vary from relatively low frequency (e.g. the Malawi guidelines with testing 6 months after ART initiation then every 2 years) to higher frequency (e.g. DHHS, with testing 1–3 monthly depending on viral load levels). The guidelines differ slightly if a woman is initiating ART for the first time (Table 1).

Table 1
Table 1:
Details of guidelines based monitoring.

Viral load monitoring guidelines were applied to each of 20 simulated populations of 10 000 women and the results averaged. Random seeds were specified to ensure all guidelines were applied to identical simulated data sets but seeds for each of the 20 populations were unique. The main outcome measures of interest were the percentage of women with elevated viral load at different time points, including before delivery or at any time before the end of breastfeeding; the percentage of women receiving viral load monitoring during pregnancy and/or breastfeeding; the percentage of women monitored at the time of elevated viral load; the time from elevated viral load until monitoring; and the cumulative viral load (expressed as log10 copies/year) experienced by women at the time of detection. Sensitivity analyses were used to examine the robustness of findings when varying input parameters, and subsidiary analyses were carried out with the subgroup of women who achieved viral suppression during pregnancy.

Results

The results (Table 2) show that the percentage of women who receive viral load monitoring in pregnancy and breastfeeding varied markedly by guidelines, with between 14% and 100% of women monitored antenatally and 38–98% monitored during breastfeeding. Specific recommendations for testing at either a fixed gestation (WHO, DHHS, Zambia) or a short, fixed period after ART initiation (DHHS) achieved more than 95% testing in pregnancy; other guidelines led to 59–83% antenatal testing; and with no special stipulation, only 14% of women received an antenatal test under Malawian guidelines. Guidelines calling for monitoring during breastfeeding (South Africa, Kenya, Zambia) had more than 80% coverage compared with 30–60% among guidelines that did not (WHO, Malawi).

Table 2
Table 2:
Results of simulations applying existing guidelines for viral load monitoring to populations of pregnant and breastfeeding women.

In the simulation, by 24 months postpartum, 92% of women initiating ART achieved viral load less than 50 copies/ml, and 18% of these subsequently experienced transient or extended elevations in viral load greater than 1000 copies/ml. Only a small proportion of simulated episodes of elevated viral load greater than 1000 copies/ml were successfully detected by monitoring (range 20–50%) among women who had reached viral suppression. Guidelines with more frequent testing in pregnancy and breastfeeding led to shorter delays from the onset of elevated viral load (50 copies/ml) to detection [South Africa median weeks 10 (IQR 5–16) vs. Kenya median weeks 17 (IQR 9–23)] as well as lower cumulative viral load before detection [DHHS cumulative viral load 0.34 log10 copies/ml/year (IQR 0.26, 0.41) vs. South Africa 0.54 (IQR 0.34–0.98)] (Table 2). In sensitivity analyses, higher proportions of women initiating ART during pregnancy did not alter the relative performance of guidelines appreciably (not shown). Findings across guidelines were also similar when varying other input parameters, including the median gestational age at antenatal care entry and duration of breastfeeding (not shown).

Discussion

This work provides the first systematic evaluation of existing policies for viral load monitoring in pregnant and breastfeeding women on ART. The key finding is that without guidance specific to pregnant and breastfeeding women, fewer than 30% of women would receive antenatal or postnatal viral load monitoring. However, even with specific guidance, current guidelines may lead to suboptimal detection of elevated viral load, in the form of either undetected viraemia and/or substantial delays from the onset of viraemia to its detection during routine monitoring.

Like all findings from mathematical models, these results depend on a set of underlying assumptions; however, this model has been subject to intense calibration using multiple, diverse data sources, as well as sensitivity analyses with considerable expert input. In addition, it is important to note that this analysis did not consider the delays between time of specimen collection for viral load monitoring and return of result to healthcare worker for review and potential intervention; accounting for these delays is likely to lead to further reductions in performance of viral load monitoring in real-world settings. Health systems considerations, like the delay in return of viral load results, reduction of stigma related to HIV diagnosis and retention and engagement of women in care, may have impacts that outweigh the use and timing of viral load monitoring; however, viral load monitoring is one of the few objective methods we have to assess treatment adherence and development of drug resistance, and understanding how to apply this tool optimally is important.

Although vertical transmission rates have reduced dramatically with increased coverage and access to HIV testing and rapid initiation of ART, hurdles remain to eliminate mother-to-child-transmission. In order to identify episodes of viraemia (and risk of vertical transmission), targeted strategies for viral load monitoring, and ultimately, drug resistance testing, will be needed for the elimination of mother-to-child-transmission [17]. Although further research is needed to understand the specifics of optimal viral load frequency and timing, these findings underscore the need for stronger policies to support when and how viral load monitoring during pregnancy and breastfeeding should occur in order to improve maternal and child health outcomes in the context of HIV infection.

Acknowledgements

Research reported in this publication was partially supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under award number R21HD093463. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding sources: R21 HD093463 (M.L. and L.M.), UM1AI068616 (S.B.), R01 HD079214 (A.L.C.), P01 HD059454 (D.V.H.) and K23 MH114760 (C.A.K.).

Role of authors: L.M., E.J.A. and M.L. conceptualized the study and simulation. M.L. and J.R. developed the analytic framework for the simulation. A.L.C., S.E., D.V.H., C.A.K., R.L.S., E.J.A. and L.M. provided critical input and feedback on the model framework. M.L. and T.G. wrote the simulation and analysis code. S.S.B., J.S.C., D.V.H., A.O., R.L.S., E.J.A. and L.M. contributed source data for the calibration and validation of the simulation model. All authors provided input on the draft manuscript and approved submission.

Conflicts of interest

There are no conflicts of interest.

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Keywords:

antiretroviral therapy; HIV; mathematical model; pregnancy; simulation; viral load monitoring

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