The Stop TB Partnership has prioritized the development of shorter regimens as part of their global plan to eliminate TB. In pursuit of that goal, many entities have undertaken Phase II clinical trials using 2-month culture conversion as a surrogate endpoint to test the sterilizing ability of new drug regimens. However, the sequential testing of all proposed regimens is time-consuming and cost-prohibitive, so more efficient strategies for selecting regimens for testing are required. Furthermore, without prior evaluation of the costs of new therapies, there is a risk of developing a new treatment for TB that is not economically viable. Mathematical modeling can provide a solution to this problem by synthesizing data from prior human and mouse studies to generate estimates of relapse rates for new regimens that could be used in the design of clinical trials. First, a generic Markov model of TB treatment and relapse will be developed in which individuals with TB will be assigned to one of several treatment arms, then followed in monthly cycles through an interim evaluation of culture positivity at 1, 2, 3, or 4 months. They will then be assumed to complete a consolidation phase of therapy, after which they will be followed for two years for relapse. Toxicity and tolerability will be considered at each stage. We will use appropriate distributions for all relevant parameters, particularly culture conversion and relapse rates, and use probabilistic sensitivity analysis to produce point estimates of relapse rates with 95% confidence intervals that can be used to determine which regimens are worthy of further testing. This model will then be used to accomplish 3 specific aims:
Aim 1 will be to use the model to examine the potential impact of substituting moxifloxacin for isoniazid during the first two months of TB treatment on TB relapse rates, given standard and abbreviated treatment durations.
Aim 2 will be to determine the impact of high-dose rifapentine (administered during the first 2 months of TB treatment) on relapse rates and potential for reduction of the duration of TB treatment.
Aim 3 will be to model the potential effect of linezolid on the treatment of MDR-TB, paying particular attention to the tradeoff between increased effectiveness and toxicity. Costs and cost-effectiveness will be calculated in each model.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01AI083782-02
Application #
7921549
Study Section
Microbiology and Infectious Diseases B Subcommittee (MID)
Program Officer
Jacobs, Gail G
Project Start
2009-09-01
Project End
2014-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
2
Fiscal Year
2010
Total Cost
$125,368
Indirect Cost
Name
Duke University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Naggie, Susanna; Holland, David P; Sulkowski, Mark S et al. (2017) Hepatitis C Virus Postexposure Prophylaxis in the Healthcare Worker: Why Direct-Acting Antivirals Don't Change a Thing. Clin Infect Dis 64:92-99
Holland, David P; Sanders, Gillian D; Hamilton, Carol D et al. (2012) Strategies for treating latent multiple-drug resistant tuberculosis: a decision analysis. PLoS One 7:e30194
Holland, David P; Sanders, Gillian D; Hamilton, Carol D et al. (2011) Potential economic viability of two proposed rifapentine-based regimens for treatment of latent tuberculosis infection. PLoS One 6:e22276
Holland, David P; Sanders, Gillian D; Hamilton, Carol D et al. (2009) Costs and cost-effectiveness of four treatment regimens for latent tuberculosis infection. Am J Respir Crit Care Med 179:1055-60