A quantitative benefit-risk analysis of isoniazid for treatment of latent tuberculosis infection using incremental benefit framework

Cost-effectiveness of latent tuberculosis infection testing and treatment with 6-week regimen among key population in rural communities in China: a decision analysis study

PURPOSE

Several model studies suggested the implementation of latent tuberculosis infection (LTBI) testing and treatment could greatly reduce the incidence of tuberculosis (TB) and achieve the 2035 target of the "End TB" Strategy in China. The present study aimed to evaluate the cost-effectiveness of LTBI testing and TB preventive treatment among key population (≥ 50 years old) susceptible to TB at community level in China.

METHODS

A Markov model was developed to investigate the cost-effectiveness of LTBI testing using interferon gamma release assay (IGRA) and subsequent treatment with 6-month daily isoniazid regimen (6H) (as a standard regimen for comparison) or 6-week twice-weekly rifapentine and isoniazid regimen (6-week H2P2) in a cohort of 10,000 adults with an average initial age of 50 years.

RESULTS

In the base-case analysis, LTBI testing and treatment with 6H was dominated (i.e., more expensive with a lower quality-adjusted life year (QALY)) by LTBI testing and treatment with 6-week H2P2. LTBI testing and treatment with 6-week H2P2 was more effective than no intervention at a cost of $20,943.81 per QALY gained, which was below the willingness-to-pay (WTP) threshold of $24,211.84 per QALY gained in China. The one-way sensitivity analysis showed the change of LTBI prevalence was the parameter that most influenced the results of the incremental cost-effectiveness ratios (ICERs).

CONCLUSION

As estimated by a Markov model, LTBI testing and treatment with 6-week H2P2 was cost-saving compared with LTBI testing and treatment with 6H, and it was considered to be a cost-effective option for TB control in rural China.

Economic Evaluation of Multiple-Pharmacogenes Testing for the Prevention of Adverse Drug Reactions in People Living with HIV

Purpose

Pharmacogenetics (PGx) testing is one of the methods for determining whether individuals are at risk of adverse drug reactions (ADRs). It has been reported that multiple-PGx testing, a sequencing technology, has a higher predictive value than single-PGx testing. Therefore, this study aimed to determine the most cost-effective PGx testing strategies for preventing drug-induced serious ADRs in human immunodeficiency virus (HIV)-infected patients.

Patients and Methods

Potential strategies, including 1) single-PGx esting (ie, HLA-B*57:01 testing before prescribing abacavir, HLA-B*13:01 testing before prescribing co-trimoxazole and dapsone, and NAT2 testing before prescribing isoniazid) and 2) multiple-PGx testing as a combination of four single-gene PGx tests in one panel, were all compared to no PGx testing (current practice). To evaluate total cost in Thai baht (THB) and quality-adjusted life years (QALYs) for each strategy-based approach to a societal perspective, a hybrid decision tree and Markov model was constructed. Incremental cost-effectiveness ratios (ICERs) were estimated. Uncertainty, threshold, and scenario analyses were all performed.

Results

Before prescribing HIV therapy, providing single or multiple-PGx testing might save roughly 68 serious ADRs per year, and the number needed to screen (NNS) to avoid one serious ADR was 40. Consequently, approximately 35% and 40% of the cost of ADR treatment could be avoided by the implementation of single- and multiple-PGx testing, respectively. Compared with no PGx testing strategy, the ICERs were 146,319 THB/QALY gained for single-PGx testing and 152,014 THB/QALY gained for multiple-PGx testing. Moreover, the probability of multiple-PGx testing being cost-effective was 45% at the Thai willingness to pay threshold of 160,000 THB per QALY. Threshold analyses showed that multiple-PGx testing remained cost-effective under the range of cost, sensitivity at 0.95–1.00 and specificity at 0.98–1.00.

Conclusion

Single and multiple-PGx testing might be cost-effective options for reducing the incidence of drug-induced serious ADRs in people living with HIV.

Cost-effectiveness of a Pharmacogenomic Test for Stratified Isoniazid Dosing in Treatment of Active Tuberculosis

Background

There is marked interindividual variability in metabolism and resulting toxicity and effectiveness of drugs used for tuberculosis treatment. For isoniazid, mutations in the N-acetyltransferase 2 (NAT2) gene explain >88% of pharmacokinetic variability. However, weight-based dosing remains the norm globally. The potential clinical impact and cost-effectiveness of pharmacogenomic-guided therapy (PGT) are unknown.

Methods

We constructed a decision tree model to project lifetime costs and benefits of isoniazid PGT for drug-susceptible tuberculosis in Brazil, South Africa, and India. PGT was modeled to reduce isoniazid toxicity among slow NAT2 acetylators and reduce treatment failure among rapid acetylators. The genotyping test was assumed to cost the same as the GeneXpert test. The main outcomes were costs (2018 US dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios.

Results

In Brazil, PGT gained 19 discounted life-years (23 QALYs) and cost $11 064 per 1000 patients, a value of $476 per QALY gained. In South Africa, PGT gained 15 life-years (19 QALYs) and cost $33 182 per 1000 patients, a value of $1780 per QALY gained. In India, PGT gained 20 life-years (24 QALYs) and cost $13 195 per 1000 patients, a value of $546 per QALY gained. One-way sensitivity analyses showed the cost-effectiveness to be robust to all input parameters. Probabilistic sensitivity analyses were below per capita gross domestic product in all 3 countries in 99% of simulations.

Conclusions

Isoniazid PGT improves health outcomes and would be cost-effective in the treatment of drug-susceptible tuberculosis in Brazil, South Africa, and India.

Cost-effectiveness of 3 months of weekly rifapentine and isoniazid compared with other standard treatment regimens for latent tuberculosis infection: a decision analysis study

Background

Latent tuberculosis infection (LTBI) is a critical driver of the global burden of active TB, and therefore LTBI treatment is key for TB elimination. Treatment regimens for LTBI include self-administered daily isoniazid for 6 (6H) or 9 (9H) months, self-administered daily rifampicin plus isoniazid for 3 months (3RH), self-administered daily rifampicin for 4 months (4R) and weekly rifapentine plus isoniazid for 3 months self-administered (3HP-SAT) or administered by a healthcare worker as directly observed therapy (3HP-DOT). Data on the relative cost-effectiveness of these regimens are needed to assist policymakers and clinicians in selecting an LTBI regimen.

Objectives

To evaluate the cost-effectiveness of all regimens for treating LTBI.

Methods

We developed a Markov model to investigate the cost-effectiveness of 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H for LTBI treatment in a cohort of 10000 adults with LTBI. Cost-effectiveness was evaluated from a health system perspective over a 20 year time horizon.

Results

Compared with no preventive treatment, 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H prevented 496, 470, 442, 418, 370 and 276 additional cases of active TB per 10000 patients, respectively. All regimens reduced costs and increased QALYs compared with no preventive treatment. 3HP was more cost-effective under DOT than under SAT at a cost of US$27948 per QALY gained.

Conclusions

Three months of weekly rifapentine plus isoniazid is more cost-effective than other regimens. Greater recognition of the benefits of short-course regimens can contribute to the scale-up of prevention and achieving the 'End TB' targets.

Mathematical modelling of the impact of treating latent tuberculosis infection in the elderly in a city with intermediate tuberculosis burden

Hong Kong is a high-income city with intermediate tuberculosis (TB) burden primarily driven by endogenous reactivations. A high proportion of remote latently infected people, particularly elderly, hinders the effectiveness of current strategies focusing on passive TB detection. In this study, we developed a mathematical model to evaluate the impact of treating latent TB infection (LTBI) in the elderly in addition to current TB control strategies. The model was calibrated using the annual age-stratified TB notifications from 1965-2013 in Hong Kong. Our results showed that at present, approximately 75% of annual new notifications were from reactivations. Given the present treatment completion rate, even if only a low to moderate proportion (approximately 20% to 40%) of elderly people were screened and treated for LTBI, the overall TB incidence could be reduced by almost 50%, to reach the 2025 milestone of the global End TB Strategy. Nevertheless, due to a high risk of hepatotoxicity in elderly population, benefit-risk ratios were mostly below unity; thus, intervention programs should be carefully formulated, including prioritising LTBI treatment for high-risk elderly groups who are closely monitored for possible adverse side effects.

Benefit of treatment of latent tuberculosis infection in individual patients

We aimed to develop a decision aid that estimates whether treatment of latent tuberculosis infection (LTBI) is likely to have a net gain in quality-adjusted life-years for an individual.

A Markov model was developed which incorporated personalised estimates for risk of tuberculosis (TB) reactivation, TB death, quality-of-life impairments and treatment side-effects. The net effect of LTBI treatment was quantified in terms of quality-adjusted life-years gained or lost. Analyses were conducted for a representative set of hypothetical patients.

LTBI treatment was estimated to be beneficial when the annual risk of TB reactivation exceeded 13/100 000 to 93/100 000 for females aged 10–75 years and 15/100 000 to 119/100 000 for males aged 10–75 years; the numbers needed to treat to avoid one case of TB were 93, 77, 85 and 72, respectively, at these threshold levels.

LTBI treatment was estimated to confer a positive net benefit across a broad range of patients with characteristics typically seen in a low incidence setting for TB. Use of the decision aid has the potential to facilitate and increase confidence with LTBI treatment decisions by providing clinicians and patients with personalised estimates of likely net benefit.

Integration of PKPD relationships into benefit-risk analysis

AIM

Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents.

METHODS

A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile.

RESULTS

A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice.

CONCLUSIONS

Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials.