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Monday, 18 October 2004

This presentation is part of: Poster Session - CEA: Methods and Applications; Health Services Research

DECISION ANALYSIS FOR TUBERCULOSIS CONTROL USING A DYNAMIC EPIDEMIC MODEL

Stephen Resch, MPH, Harvard University, Health Policy, Boston, MA, Joshua Salomon, PhD, Harvard School of Public Health, Population and International Health, Cambridge, MA, Megan Murray, MD, DPH, Harvard School of Public Health, Epidemiology, Boston, MA, and Milton C. Weinstein, PhD, Harvard School of Public Health, Harvard Center for Risk Analysis, Boston, MA.

Purpose: The optimal control strategy for tuberculosis (TB) in countries with prevalent or increasing multidrug-resistant disease (MDR-TB) is controversial when resources are substantially constrained. Directly-observed treatment (short-course) with first-line drugs (DOTS) has been shown to be cost-effective but is not adequate for treating MDR-TB. Second-line drugs can cure MDR-TB and also prevent its transmission to others, but they are more expensive and require longer treatment duration. We developed a decision model to inform policymakers in deciding whether to allocate limited TB control resources to treating MDR-TB.

Methods: A deterministic dynamic compartmental model of a population of 100,000 was constructed to describe the transmission dynamics of DOTS-susceptible- and MDR-TB, capturing both the acquisition of drug resistance by ineffectively-treated cases and the impact of effective TB treatment on reducing transmission. Four treatment strategies that differed by drug regimen type and case identification method were evaluated: (1) DOTS only, (2) DOTS for new cases and standardized second-line regimen for first-line treatment failures, (3) DOTS for new cases, drug-susceptibility testing (DST) for first-line treatment failures and individualized second-line regimen for identified MDR-TB cases, (4) DST for all new patients with DOTS for susceptible cases, and individualized regimens for MDR-TB cases. Model parameters were dynamically calibrated to reflect epidemiological indices for Peru where annual TB incidence is 120 per 100,000 with 3% MDR-TB.

Results: Over the 40-year time horizon (discount rate 3%), the baseline DOTS strategy resulted in 524 TB deaths and $238,000 of TB-related costs. Performing DST on first-line failures and treating MDR-TB with an individualized second-line regimen had an incremental cost per death averted (ICDA) of $900. Use of a standardized second-line regimen was dominated. The strategy where DST is performed on all new TB cases had an ICDA of $4400. When treatment’s transmission externality is ignored, the ICDA for strategies (3) and (4) increase from $900 to $12,800, and $4400 to $20,500 per death averted, respectively.

Conclusions: Treating MDR-TB after first-line failure improves health outcomes at an affordable cost (less than $100 per QALY gained) even in low-income countries. Ignoring the effect of treatment on reducing transmission overestimates the total burden of disease and cost, and also makes the cost-effectiveness ratio of treating MDR-TB with second-line drugs appear several times less favorable.


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