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Evaluation of 6-Month Versus Continuous Isoniazid Preventive Therapy for Mycobacterium tuberculosis in Adults Living With HIV/AIDS in Malawi

Hsieh, Yuli L. MPHa; Jahn, Andreas PhDb,c; Menzies, Nicolas A. PhDd,e; Yaesoubi, Reza PhDa; Salomon, Joshua A. PhDd,f; Girma, Belaineh MD, MPHg; Gunde, Laurence MD, MPHh; Eaton, Jeffrey W. PhDi; Auld, Andrew MD, MSch; Odo, Michael MPHc; Kiyiika, Caroline N. BPharmb,c; Kalua, Thokozani MBBS, MScc; Chiwandira, Brown MD, MPHc; Mpunga, James U. MD, MPHg; Mbendra, Kuzani MDg; Corbett, Liz MB BCh, PhDc,j; Hosseinipour, Mina C. MD, MPHk,l; Cohen, Ted DPH, MD, MPHa; Kunkel, Amber SDm

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: December 15, 2020 - Volume 85 - Issue 5 - p 643-650
doi: 10.1097/QAI.0000000000002497

Abstract

BACKGROUND

Isoniazid preventive therapy (IPT) is recommended by the WHO for people living with HIV (PLHIV), to reduce the elevated risk of tuberculosis (TB) these individuals experience.1 However, there is a lack of consensus on the optimal length of IPT among PLHIV. Although previous studies have demonstrated reduced TB incidence with IPT, the duration of protection associated with a 6-month IPT regimen has varied between settings. Randomized controlled trials conducted in Brazil and the Côte d'Ivoire found sustained protective effects after completion of a 6-month IPT in PLHIV.2,3 By contrast, trials in Botswana and South Africa, settings where the force of TB infection is higher than that in the Brazil and Côte d'Ivoire trials, found that PLHIV required longer durations of IPT to retain protection from TB.4,5 For Malawi, when this study was conducted, the National Task Force on TB Preventive Therapy recommended IPT consisting of continuous (ie, lifelong) isoniazid (INH) and pyridoxine, along with continuous cotrimoxazole preventive therapy (CPT), to all PLHIV receiving ART, for whom active TB has been ruled out.6 Although CPT coverage was high for individuals on ART,7 adoption of IPT had been slower.

Hence, when the Global Fund offered US$10.8 million to Malawi to procure isoniazid and pyridoxine in 2017 for the period 2018–2020, policymakers at the Ministry of Health (MOH) Malawi wanted to evaluate the comparative health impacts of distributing isoniazid from this procurement as (1) 6-month IPT to PLHIV on ART across districts or (2) continuous IPT to PLHIV on ART across potentially fewer districts. To address this question, we worked with representatives from the MOH Malawi to develop a calibrated transmission dynamic model and decision support framework to compare the health impacts of these 2 competing IPT allocation strategies.

METHODS

Intervention Scenarios

We defined one base scenario and 2 IPT intervention scenarios (Fig. 1). The base scenario represented no IPT intervention, reflecting the status quo in 2017 when IPT access was minimal. The first intervention scenario was defined as allocating 6-month IPT to as many districts as possible, up to the limit of IPT doses available in the 3-year budget period of 2018–2020. The alternative was to implement continuous IPT across districts up to the same limit of IPT doses, which was 1,003,423 person-years of IPT, based on the US$10.8 million budgetary limit and the commodity costs of isoniazid (300 mg) and pyridoxine (25 mg) in Malawi. The aim was to allocate the fixed number of IPT doses across districts to maximize the overall health benefit at the national level. As the model projections incorporated uncertainties in the amount of IPT required in each district over the course of time, we assumed the policymakers had a willingness to accept a 10% chance of exceeding the 2018–2020 budget.

F1
FIGURE 1.:
Modeling approach. A, The decision analytic framework with 3 IPT policy alternatives. Green square, decision node; blue circles, allocation of IPT intervention programs across 27* indivisible districts, based on the allocated budget and the expected number of IPT doses required in 2018–2020; X, implementing continuous IPT program in X number of districts; Y, implementing 6-month IPT program in Y number of districts; orange hexagons, the HIV/TB compartmental model. *Likoma was excluded from the analysis because of limited TB and HIV service and surveillance data. B, The HIV/TB compartmental model captures both the TB-related and HIV-related health states among adults (≥15 years old): N, susceptible to HIV; H, undiagnosed HIV infection; AIpre, diagnosed HIV infection on ART before having received IPT; AIon, diagnosed HIV infection on ART and IPT; AIpost, diagnosed HIV infection on ART after having received IPT (top margin); S, susceptible to TB; E, latent TB; I, untreated active TB; T, on treatment for active TB disease; C, cured from latent TB (left margin). Mortality rates are not shown in the figure.

Appendix 1, Supplemental Digital Content, https://links.lww.com/QAI/B534, describes how IPT doses were allocated across districts under each intervention scenarios in our model. Briefly, IPT was made available district-by-district, and districts with the highest TB incidence rates in 2018 were prioritized for enrolment. Each district was treated as an indivisible unit (Fig. 1, blue circles) and would only be enrolled if there were enough IPT available for all eligible patients in that district in 2018–2020. We assumed the spending rate within this 3-year budget period was flexible. No fixed costs were accounted for in our study; the MOH Malawi planned to allocate the US$10.8 million on procurement of isoniazid and pyridoxine alone. The 6-month and continuous IPT strategies were assessed as static intervention policies over a 12-year horizon, assuming funding would be available.

After the 2015 WHO recommendation on IPT for PLHIV,8 we assumed IPT eligibility would be restricted to adults (≥15 years old) living with HIV/AIDS, with an unknown or positive tuberculin skin test status, had active TB disease ruled out, and currently receiving ART. In addition, each patient was assumed to receive a single IPT course (6 months or continuous, depending on the intervention scenario) unless they developed active TB and became eligible for another IPT course (secondary IPT) after completing TB treatment. The length of treatment for secondary IPT was the same as primary IPT. There was no limit to the number of courses of secondary IPT a patient could receive.

Modeling Approach

We projected the policy outcomes in each of 27 districts in Malawi (excluding Likoma, a very small island district) under each intervention scenario over a 12-year period (2018–2030) to determine the short-term and medium-term impacts of IPT scale-up in Malawi. The model was operationalized as a set of ordinary differential equations, which were numerically integrated by the deSolve package in R version 3.5.1.9

Model Overview on TB and HIV States

We stratified the compartmental model into children (<15 years old.) and adult (≥15 years old) populations. We assumed all children were HIV-negative10 and could be TB susceptible or latently infected with TB. For adults, HIV-related states included susceptible to HIV infection, undiagnosed HIV infection, diagnosed HIV infection receiving ART but not IPT, diagnosed HIV infection receiving ART and IPT, or diagnosed HIV infection receiving ART post-IPT (top margin in Fig. 1). TB-related states included TB susceptible, latent TB infection, untreated active TB, or active TB undergoing treatment (left margin in Fig. 1). Deaths occurring among active TB cases and those receiving TB treatment were counted toward TB-related deaths in our study.

TB/HIV epidemics were modeled for each district, assuming no population mixing between districts. We estimated the district-specific TB force of infection as a function of the number of individuals with active TB in the model, assuming frequency dependent transmission and a stable population size over the simulation period. The district-level HIV force of infection was incorporated into the model as an exogenous input, based on UNAIDS national HIV incidence estimates for the period 1990–2017.11 We assumed the HIV incidence rate would continue to decrease after 2017 and would be halved by the end of 2030. Appendices 2 and 3, Supplemental Digital Content, https://links.lww.com/QAI/B534, present details of model and parameters.

Model Overview on IPT Implementation

We assumed individuals receiving IPT would experience decreased risks of TB infection, reinfection, and reactivation. We also allowed 35% of latently infected individuals completing IPT and continuing on ART to be “cured” of TB infection (no reactivation risk) and retain partial immunity to future TB infections.12 We assumed IPT had no protective effect on individuals with active TB.

For every 1000 treatment initiations in our model, we assumed IPT would cause 6 hepatic dysfunction cases, defined as serum aminotransferase levels >5 times the upper limit of normal values (grade 3/4 elevation in ALT/AST levels),13 and an excess mortality of 0.04 deaths due to INH-related hepatotoxicity.14 The modeled frequency of hepatotoxicity was dependent on the number of IPT initiators rather than the total person-time spent on IPT in each scenario because previous findings suggested most INH-associated hepatotoxicity occurs in early phases of the intervention.15

With input from local health care providers, we assumed a catch-up campaign would allow 77.5% (range, 60.0–95.0%) of eligible patients to initiate IPT in targeted districts by the end of first year. We assumed a constant retention rate of 84.25% (beta distribution, 2.5th percentile, 84.09%, 97.5th percentile, 84.41%) by the end of every 6 months of IPT in both strategies.16 That is, the median treatment duration for patients enrolled in 6-month IPT and continuous IPT was approximately 4 and 28 months, respectively.

Model Calibration

A 2-stage calibration procedure was used. In the first stage, the model was calibrated using the Nelder–Mead algorithm to national-level data, including the number of notified TB cases, the number of notified TB cases confirmed to be HIV infected, the number of patients retained on ART at mid-year, and HIV prevalence from 2008 to 2017 (TB surveillance data and Spectrum file from the MOH Malawi). We also included the expected percentage (30%) of HIV deaths from TB cases among PLHIV as a calibration target.17 The excess mortality of TB/HIV coinfection and the TB reactivation rate and the probability of having progressive primary TB for those with undiagnosed HIV were estimated through this stage of the calibration, and input as fixed parameters in the second stage of the calibration.

In the second stage, incremental mixture importance sampling18 was used to calibrate the model to district-level data on notified TB cases, notified TB cases confirmed to be HIV infected, the number of patients retained on ART in mid-year, and HIV prevalence estimates for 2008–2017 (TB surveillance data and Spectrum file from the MOH Malawi). The TB transmission parameters and the scaling factors for an HIV incidence rate were estimated and allowed to vary between districts. Previous distributions of these parameters are provided in Appendix 3 Table 2, Supplemental Digital Content, https://links.lww.com/QAI/B534. Comparisons of model outputs and observed data are in Appendix 4, Supplemental Digital Content, https://links.lww.com/QAI/B534.

Model Simulation and Outcome Comparison

We estimated future outcomes for each scenario in all 27 districts separately, and aggregated these district-level outcomes to compare the impact of IPT policy alternatives at the national level. We compared the cumulative number of active TB cases, all-cause deaths and TB-related deaths, and episodes of IPT-induced hepatotoxicity among adults at 3 and 12 years after program initiation. We also compared the efficiency of the 2 intervention programs, defined as the ratio of the total amount of IPT dispensed to cumulative TB cases averted, equivalent to the number of person-years of IPT required to avert one TB case, by year 3 and 12.

Given limited data for IPT-related parameters (see Appendix 3 Table 4, Supplemental Digital Content, https://links.lww.com/QAI/B534), uncertainty analysis with Latin hypercube sampling was performed to produce a range of plausible outcome estimates for both IPT programs. Along with the resampled parameter sets from incremental mixture importance sample, 300 simulations were obtained for each policy alternative. In addition, a one-way sensitivity analysis was conducted for the rate of INH-associated hepatotoxicity.

For each outcome, the point estimate represents the arithmetic mean of the distribution, and the uncertainty intervals represent the 95% projection intervals (PIs). All comparisons were conducted at the significance level of 0.05.

RESULTS

Baseline Epidemiological Characteristics

At the beginning of 2018, model-estimated district-specific TB prevalence ranged from 101 to 674 per 100,000 person-years, and the HIV prevalence ranged from 4.37% to 15.69%. National TB prevalence and incidence were 337 per 100,000 and 246 per 100,000 person-years, respectively. National HIV prevalence and incidence were 8.80% and 0.15% per year. The baseline TB/HIV epidemiological characteristics of each district at the start of IPT programs are shown in Appendix 5 Table 1, Supplemental Digital Content, https://links.lww.com/QAI/B534.

Allocation of IPT Intervention Programs

In each of our model simulations (n = 300), we found that the 6-month IPT program could be implemented nationwide in 2018–2020 while leaving US$7.04 million (out of 10.8 million) unused (see Appendix 5 Table 2, Supplemental Digital Content, https://links.lww.com/QAI/B534). By contrast, the continuous IPT program could only be introduced in 14 districts (see Appendix 5, Figure 1B, Supplemental Digital Content, https://links.lww.com/QAI/B534). The uncertainty to the total amount of IPT doses required annually increased with time and with the number of districts where continuous IPT was introduced (Fig. 2A, Appendix 5 Figure 1C, Supplemental Digital Content, https://links.lww.com/QAI/B534). For the analyses below, we compared the health outcomes between nationwide implementation of 6-month IPT with the implementation of continuous IPT in 14 districts. The list of targeted districts for each alternative can be found in Appendix 5 Table 2, Supplemental Digital Content, https://links.lww.com/QAI/B534.

F2
FIGURE 2.:
Person-years of IPT delivered under the 3 IPT policy alternatives. The 6-month and continuous IPT program were introduced to 28 and 14 districts with the highest TB incidence rates, respectively. The number of districts intervened over the simulation period was fixed in either intervention scenario, reflecting a static intervention policy. A, Cumulative person-years of IPT delivered. Grey dashed line (- - -), the maximum PY of IPT available in 2018–2020. B, Person-years of IPT delivered. Solid lines, arithmetic means of the distributions of resampled parameter sets; the ribbons, 95% PIs.

The consumption of IPT in both intervention scenarios was the greatest in the first 3 years of the intervention programs (Fig. 2B). The sharp increase in the first year was due to the catch-up campaign. The relatively steep decrease in the 6-month IPT curve reflects treatment completion and patient drop-out. The decrease was slower in the continuous IPT scenario and only caused by early treatment terminations. The number of patients starting IPT was minimal after the first couple of years because patients were only allowed one course of IPT treatment, most eligible patients were initiated on IPT early in the projection period, and the number of ART initiators was relatively small over time. The amount of IPT consumed in the 6-month IPT program was significantly less than the continuous program.

Health Effects of IPT Intervention Programs

Compared with the base case scenario, the 6-month IPT program reduced the national TB incidence among PLHIV by 5.05% (95% PI, 3.19–7.60%) at the end of year 3 and 7.02% (95% PI, 3.71–11.58%) at the end of year 12 (Fig. 3B). For the continuous IPT program, the estimates were 6.38% (95% PI, 3.97–8.71%) and 9.81% (95% PI, 5.28–13.37%). No rebound in TB prevalence or incidence was predicted for either program (Fig. 3), even after most patients have completed or dropped out from IPT treatment (Fig. 2B). This can be attributed to the effect of IPT on decreasing the TB force of infection in the population, relative to the base case.

F3
FIGURE 3.:
Twelve-year projection of TB burden among adults under the 3 IPT policy alternatives. A, National TB prevalence (per 100,000). B, National TB incidence (per 100,000). The 6-month IPT program was introduced nationwide, and the continuous IPT program was implemented in 14 districts with the highest estimated TB incidence rates in 2018. The number of districts intervened over the simulation period was fixed in either intervention scenario, reflecting a static intervention policy. Solid lines, arithmetic means of the distributions of resampled parameter sets; the ribbons, 95% PIs.

The mean reductions in a TB-related mortality rate among PLHIV in the 6-month IPT scenario, compared with the base case scenario, were 10.38% (95% PI, 8.28–12.15%) by the end of year 3 and 12.04% (95% PI, 9.29–15.46%) by the end of year 12, whereas the continuous IPT scenario attained a 9.33% (95% PI, 7.04-10.91%) reduction by the end of year 3 and a 12.53% (95% PI, 9.40–15.02%) reduction by the end of year 12 (Fig. 4B). The impact on all-cause mortality among PLHIV in either intervention scenario, in comparison with the base case, was <5% over the simulation period (Fig. 4C).

F4
FIGURE 4.:
Comparisons of the health impacts of IPT between policy alternatives. A, Cumulative number of TB cases averted among adults, in relation to the base case. B, Cumulative number of TB-related deaths averted among PLHIV, in relation to the base case. C, Cumulative number of all-cause deaths averted among PLHIV, in relation to the base case. Solid lines, arithmetic means of the distributions of resampled parameter sets; the ribbons, 95% PIs.

For the continuous IPT program, an estimated 3562 patients were expected to experience grade 3/4 hepatotoxicity in the first 3 years, exceeding the number of all-cause deaths averted. By the end of year 12, the number of hepatotoxicity events accumulated to 4500 but was surpassed by the number of all-cause deaths averted (Fig. 5). The 6-month IPT program displayed similar trends.

F5
FIGURE 5.:
IPT-associated adverse events. A, Expected cumulative number of patients with grade 3 or 4 INH-associated hepatotoxicity. The expected number of patients who might experience severe hepatoxicity events, assuming the rate of occurrence was 6 per 1000 IPT initiations. The uncertainty bars, 95% PIs. B, One-way sensitivity analysis on the mean number of patients with severe INH-associated hepatotoxicity, assuming the range of grade 3 or 4 INH-associated hepatotoxicity is 1–10 episodes per 1000 IPT initiations.13,32–34

Comparison Between 6-Month and Continuous IPT Intervention Scenarios

The continuous IPT strategy was predicted to avert more TB cases among adults compared with the 6-month strategy, although not statistically significant: 36 (95% PI, −489 to 524) additional cases by the end of year 3 and 2368 (95% PI, −1459 to 5023) additional cases by the end of year 12. The 6-month IPT strategy was predicted to avert more TB-related and all-cause deaths among PLHIV than the continuous strategy by year 3; the reverse was observed by year 12, although without statistical significance, either (Fig. 4). The 6-month scenario accumulated more IPT-associated hepatotoxicity than the continuous scenario (Fig. 5).

The 6-month IPT program was more efficient than the continuous scenario in terms of person-years of IPT required to prevent a TB case (see Appendix 6 Table 1, Supplemental Digital Content, https://links.lww.com/QAI/B534). The efficiency of IPT programs improved with time regardless of the choice of intervention strategy because the TB force of infection decreased and the number of IPT initiators was minimal after the first 3 years (Fig. 1B) while the population continued to benefit from the curative effect of IPT over time.

DISCUSSION

In this study, we used a decision analytic framework, in conjunction with a calibrated, district-level model of the TB/HIV epidemics in Malawi, to compare the health effects of 6-month and continuous IPT programs under budgetary constraints. Our models allowed us to understand the trade-offs between continuous IPT implemented in selected districts versus 6-month IPT available nationwide.

Under the given budgetary constraints, we found that the nationwide implementation of 6-month IPT would yield comparable health benefits to the implementation of continuous IPT in selected districts, despite significant under-spending in the 6-month IPT strategy in our model. In addition, the 6-month strategy was shown to be more efficient than the continuous IPT strategy, in terms of person-years of IPT needed to avert a TB case or TB death. Accordingly, the 6-month regimen may be more appealing under the current epidemiological context in Malawi, especially if leftover funding from IPT implementation can be reallocated to other TB interventions. We also recognize the serious ethical concerns with the continuous IPT strategy that would not be available to individuals in several districts due to anticipated budgetary constraints.

The 6-month strategy was shown to avert more TB-related deaths, but less TB cases, than the continuous strategy by the end of year 3. This is because deaths averted among those receiving active TB treatment were included in the number of TB-related deaths averted in our analysis. Because the 6-month program covered more districts, more deaths could be prevented from screening and subsequently treating more people for active TB near the start of the IPT programs.

Regardless of the strategy chosen, the population-level impact of IPT was modest in our modeled population in Malawi, and the estimated number of patients experiencing grade 3/4 hepatotoxic events was greater than the number of all-cause deaths averted in the first 3 years of program implementation. These will likely be major challenges for the scale-up of IPT programs because most health care facilities in Malawi do not currently have the laboratory capacity for routine monitoring of liver function among patients on IPT, which may preclude the opportunity for early detection and timely intervention of serious drug-related adverse events.

Results from the trial-based modeling study performed by Pho et al 19 for southern India indicated a 62% decrease in TB incidence among PLHIV from a 6-month IPT at 3-year follow-up, whereas the mean reduction in TB incidence among PLHIV in our study was 5%. The underlying assumptions in their model are similar to ours, except we assumed only PLHIV on ART could receive IPT, whereas in their study all PLHIV, with 27% receiving ART at baseline, were considered for IPT. Similarly, several studies demonstrating cost-effectiveness or cost-savings of IPT programs were performed in the pre-ART era, when the background mortality was higher.20–22 It is possible that a high ART coverage in PLHIV in our patient population conferred survival and immunological benefits and crowded out some of the potential impacts of IPT in our model, as compared to times and settings with less ART access.23–25

Furthermore, a more recent trial-based modeling study that examined the impact of delivering 12-month IPT to those receiving ART in a South African setting with a 48%–61% ART coverage predicted a 7.6% reduction in TB incidence among adults over 5 years.26 This was similar to our 6-month IPT scenario predictions where the ART coverage ranged from 68% to 89%, signifying that in settings with relatively high ART coverages among PLHIV, delivering 6–12 month IPT to those receiving ART, will produce only modest changes in TB risk in the overall PLHIV population.

An important feature of this modeling study is that we were able to capture the spatial heterogeneity in HIV and TB burden across districts by incorporating district-level demographic, epidemiological, and health service data. Another strength of this study is that the model incorporated most barriers to IPT program implemenation,27 including imperfect patient adherence, low program uptake, and the potential of clinical error in screening for active TB. Inputs from our colleagues in Malawi on local care patterns and health care capacity were highly valuable, and our findings were used by policymakers at the MOH Malawi to inform recommendations.

Our study has some limitations. One is that we did not consider drug resistance in our model. However, as suggested by previous findings from Kunkel et al, 28 the risks of spreading INH resistance may be limited given the declining TB/HIV coepidemic. Also, we assumed the population size remained constant over time, whereas Malawi has an annual population growth rate close to 3% in the past decade.29 This, however, should not have a significant impact on the volume of IPT required because its main driver is the number of people on ART, the projection of which was calibrated to available data. In addition, we assumed a 50% reduction in HIV incidence by 2030, which may be optimistic. Therefore, we analyzed a pessimistic scenario where the HIV incidence remained constant throughout 2017–2030. Instead of a steady decrease in TB burden across IPT strategies, a rebound in TB prevalence and incidence was shown for both IPT strategies, but the relative effectiveness of the 2 strategies remained the same (see Appendix 7, Supplemental Digital Content, https://links.lww.com/QAI/B534).

Another limitation is that we assumed about one-third of those completing IPT attained partial immunity against TB. If such protection wanes over time, the comparative effect of the 6-month IPT strategy, relative to the continuous alternative, would be worse than estimated. Furthermore, we assumed funding would be available for other costs incurred from IPT programs, including TB screening and patient follow-up. In practice, health care capacity is limited and different between districts, so the effectiveness of the 2 IPT programs could be lower than estimated. These costs could differ between the 2 strategies because they require different amounts of these additional costs.

It is worth noting that our model incorporated secondary IPT courses, a strength of our study because reactivation and reinfection rates have been shown to be high shortly after TB treatment in high TB burden regions.30 The WHO also recommends secondary IPT for PLHIV in resource constrained settings.31 However, to keep our model parsimonious, our model is not equipped to limit the number of secondary IPT courses an individual can receive, which may raise an issue on allocation efficiency.

Finally, it is common for patients to travel across district or country borders for routine HIV and TB care. We did not capture this health seeking behavior in our model because the population movement between districts is poorly characterized. This data limitation might affect local notification rates and complicates district-level estimation of epidemiological outcomes and resource utilization of IPT, particularly in the continuous IPT strategy, where IPT scale-up is not universal.

Overall, our results suggest that under given budgetary constraints, the nationwide implementation of 6-month IPT program could produce comparable health benefits as implementation of continuous IPT program in selected districts and would be a more efficient strategy. However, the high level of adverse events and the modest reduction in TB transmission and mortality associated with both IPT strategies suggests that a combination of different TB intervention strategies will be required to have a transformative impact on TB control in settings such as Malawi, where ART and CPT coverages are already relatively high.

ACKNOWLEDGMENTS

The authors thank the Department of HIV and AIDS, Ministry of Health and Population Malawi; the National Tuberculosis Control Program, Ministry of Health and Population Malawi; and the Center of Disease Control and Prevention (CDC Malawi), for their generosity in sharing TB and HIV surveillance and service data and for their continued support in our research endeavors.

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Keywords:

tuberculosis; preventive therapy; PLHIV; Malawi; transmission dynamic model; allocation strategies

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