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Cost-effectiveness of treating multidrug-resistant tuberculosis.

Resch SC, Salomon JA, Murray M, Weinstein MC - PLoS Med. (2006)

Bottom Line: Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths annually worldwide.We found that strategies incorporating the use of second-line drug regimens following first-line treatment failure were highly cost-effective compared to strategies using first-line drugs only.In other settings, the attractiveness of strategies using second-line drugs will depend on TB incidence, MDR burden, and the available budget, but simulation results suggest that individualized regimens would be cost-effective in a wide range of situations.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Policy and Management, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America. resch@fas.harvard.edu

ABSTRACT

Background: Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths annually worldwide. Effective treatment is complicated by multidrug-resistant TB (MDR TB) strains that respond only to second-line drugs. We projected the health benefits and cost-effectiveness of using drug susceptibility testing and second-line drugs in a lower-middle-income setting with high levels of MDR TB.

Methods and findings: We developed a dynamic state-transition model of TB. In a base case analysis, the model was calibrated to approximate the TB epidemic in Peru, a setting with a smear-positive TB incidence of 120 per 100,000 and 4.5% MDR TB among prevalent cases. Secondary analyses considered other settings. The following strategies were evaluated: first-line drugs administered under directly observed therapy (DOTS), locally standardized second-line drugs for previously treated cases (STR1), locally standardized second-line drugs for previously treated cases with test-confirmed MDR TB (STR2), comprehensive drug susceptibility testing and individualized treatment for previously treated cases (ITR1), and comprehensive drug susceptibility testing and individualized treatment for all cases (ITR2). Outcomes were costs per TB death averted and costs per quality-adjusted life year (QALY) gained. We found that strategies incorporating the use of second-line drug regimens following first-line treatment failure were highly cost-effective compared to strategies using first-line drugs only. In our base case, standardized second-line treatment for confirmed MDR TB cases (STR2) had an incremental cost-effectiveness ratio of 720 dollars per QALY (8,700 dollars per averted death) compared to DOTS. Individualized second-line drug treatment for MDR TB following first-line failure (ITR1) provided more benefit at an incremental cost of 990 dollars per QALY (12,000 dollars per averted death) compared to STR2. A more aggressive version of the individualized treatment strategy (ITR2), in which both new and previously treated cases are tested for MDR TB, had an incremental cost-effectiveness ratio of 11,000 dollars per QALY (160,000 dollars per averted death) compared to ITR1. The STR2 and ITR1 strategies remained cost-effective under a wide range of alternative assumptions about treatment costs, effectiveness, MDR TB prevalence, and transmission.

Conclusions: Treatment of MDR TB using second-line drugs is highly cost-effective in Peru. In other settings, the attractiveness of strategies using second-line drugs will depend on TB incidence, MDR burden, and the available budget, but simulation results suggest that individualized regimens would be cost-effective in a wide range of situations.

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Structure of the TB Treatment ModelBoxes represent health states, arrows represent population flow between health states, red arrows represent infection and re-infection. λd is the force of non-MDR infection, λm is the force of MDR TB infection,q is the proportion of new infections that break down rapidly,v is the immunity factor, γ is the rate of delayed progression from latent to active disease, ϕi is the case detection rate, δi is the treatment dropout rate, τ is the treatment failure rate, anda is the fraction of uncured patients acquiring MDR. Death can occur from any state (not shown). Cure can occur from any diseased state. Cured patients transition to the latent infection health state (not shown).
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pmed-0030241-g001: Structure of the TB Treatment ModelBoxes represent health states, arrows represent population flow between health states, red arrows represent infection and re-infection. λd is the force of non-MDR infection, λm is the force of MDR TB infection,q is the proportion of new infections that break down rapidly,v is the immunity factor, γ is the rate of delayed progression from latent to active disease, ϕi is the case detection rate, δi is the treatment dropout rate, τ is the treatment failure rate, anda is the fraction of uncured patients acquiring MDR. Death can occur from any state (not shown). Cure can occur from any diseased state. Cured patients transition to the latent infection health state (not shown).

Mentions: The model (Figure 1) begins with a population of 100,000 people, distributed across health states to distinguish uninfected from infected persons, latent infection from active disease, non-MDR from MDR infection, and various treatment histories (seeText S1 andTables S1–S3 for technical details). In each monthly cycle persons may transition from one state to another, reflecting the processes of infection, progression, treatment initiation and completion, and mortality. Active disease is limited to smear-positive pulmonary cases, since they are the primary target of DOTS-based TB control strategies.


Cost-effectiveness of treating multidrug-resistant tuberculosis.

Resch SC, Salomon JA, Murray M, Weinstein MC - PLoS Med. (2006)

Structure of the TB Treatment ModelBoxes represent health states, arrows represent population flow between health states, red arrows represent infection and re-infection. λd is the force of non-MDR infection, λm is the force of MDR TB infection,q is the proportion of new infections that break down rapidly,v is the immunity factor, γ is the rate of delayed progression from latent to active disease, ϕi is the case detection rate, δi is the treatment dropout rate, τ is the treatment failure rate, anda is the fraction of uncured patients acquiring MDR. Death can occur from any state (not shown). Cure can occur from any diseased state. Cured patients transition to the latent infection health state (not shown).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1483913&req=5

pmed-0030241-g001: Structure of the TB Treatment ModelBoxes represent health states, arrows represent population flow between health states, red arrows represent infection and re-infection. λd is the force of non-MDR infection, λm is the force of MDR TB infection,q is the proportion of new infections that break down rapidly,v is the immunity factor, γ is the rate of delayed progression from latent to active disease, ϕi is the case detection rate, δi is the treatment dropout rate, τ is the treatment failure rate, anda is the fraction of uncured patients acquiring MDR. Death can occur from any state (not shown). Cure can occur from any diseased state. Cured patients transition to the latent infection health state (not shown).
Mentions: The model (Figure 1) begins with a population of 100,000 people, distributed across health states to distinguish uninfected from infected persons, latent infection from active disease, non-MDR from MDR infection, and various treatment histories (seeText S1 andTables S1–S3 for technical details). In each monthly cycle persons may transition from one state to another, reflecting the processes of infection, progression, treatment initiation and completion, and mortality. Active disease is limited to smear-positive pulmonary cases, since they are the primary target of DOTS-based TB control strategies.

Bottom Line: Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths annually worldwide.We found that strategies incorporating the use of second-line drug regimens following first-line treatment failure were highly cost-effective compared to strategies using first-line drugs only.In other settings, the attractiveness of strategies using second-line drugs will depend on TB incidence, MDR burden, and the available budget, but simulation results suggest that individualized regimens would be cost-effective in a wide range of situations.

View Article: PubMed Central - PubMed

Affiliation: Department of Health Policy and Management, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America. resch@fas.harvard.edu

ABSTRACT

Background: Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths annually worldwide. Effective treatment is complicated by multidrug-resistant TB (MDR TB) strains that respond only to second-line drugs. We projected the health benefits and cost-effectiveness of using drug susceptibility testing and second-line drugs in a lower-middle-income setting with high levels of MDR TB.

Methods and findings: We developed a dynamic state-transition model of TB. In a base case analysis, the model was calibrated to approximate the TB epidemic in Peru, a setting with a smear-positive TB incidence of 120 per 100,000 and 4.5% MDR TB among prevalent cases. Secondary analyses considered other settings. The following strategies were evaluated: first-line drugs administered under directly observed therapy (DOTS), locally standardized second-line drugs for previously treated cases (STR1), locally standardized second-line drugs for previously treated cases with test-confirmed MDR TB (STR2), comprehensive drug susceptibility testing and individualized treatment for previously treated cases (ITR1), and comprehensive drug susceptibility testing and individualized treatment for all cases (ITR2). Outcomes were costs per TB death averted and costs per quality-adjusted life year (QALY) gained. We found that strategies incorporating the use of second-line drug regimens following first-line treatment failure were highly cost-effective compared to strategies using first-line drugs only. In our base case, standardized second-line treatment for confirmed MDR TB cases (STR2) had an incremental cost-effectiveness ratio of 720 dollars per QALY (8,700 dollars per averted death) compared to DOTS. Individualized second-line drug treatment for MDR TB following first-line failure (ITR1) provided more benefit at an incremental cost of 990 dollars per QALY (12,000 dollars per averted death) compared to STR2. A more aggressive version of the individualized treatment strategy (ITR2), in which both new and previously treated cases are tested for MDR TB, had an incremental cost-effectiveness ratio of 11,000 dollars per QALY (160,000 dollars per averted death) compared to ITR1. The STR2 and ITR1 strategies remained cost-effective under a wide range of alternative assumptions about treatment costs, effectiveness, MDR TB prevalence, and transmission.

Conclusions: Treatment of MDR TB using second-line drugs is highly cost-effective in Peru. In other settings, the attractiveness of strategies using second-line drugs will depend on TB incidence, MDR burden, and the available budget, but simulation results suggest that individualized regimens would be cost-effective in a wide range of situations.

Show MeSH
Related in: MedlinePlus