
Drug susceptibility testing (DST) against second-line tuberculosis drugs (SLDs) is essential for improving outcomes among multidrug-resistant (MDR-) and extensively drug-resistant tuberculosis (XDR-TB) cases.To evaluate the potential cost-effectiveness of rapid DST for SLDs.We constructed a decision analysis model of Xpert MTB/RIF-based TB diagnosis in East and South-East Asia to compare culture-based DST vs. a hypothetical rapid SLD DST system for specimens resistant to rifampin. Our primary outcomes were the effectiveness and incremental cost-effectiveness of a rapid SLD DST assay relative to culture-based DST.For rapid SLD DST to be more effective than culture-based DST, treating individuals with pre-XDR/XDR-TB with a standardized MDR-TB regimen while awaiting culture-based DST must incur at least 30% excess XDR-TB mortality (100% = treatment with first-line drugs); rapid SLD DST should attain an aggregate sensitivity and specificity for all pre-XDR/XDR mutations of 88% and 96%, respectively. The unit cost of the rapid SLD DST assay must approach that of culture to achieve common thresholds for cost-effectiveness in low-income countries.Rapid SLD DST has the potential to be cost-effective, but must meet stringent criteria for accuracy and costs, and requires that standardized second-line treatment for pre-XDR/XDR-TB incur substantial excess mortality before the return of culture results.
Asia, Cost-Benefit Analysis, Extensively Drug-Resistant Tuberculosis, Decision Trees, Antitubercular Agents, Health Care Costs, Microbial Sensitivity Tests, Drug Costs, Decision Support Techniques, Models, Economic, Treatment Outcome, Predictive Value of Tests, Drug Resistance, Multiple, Bacterial, Tuberculosis, Multidrug-Resistant, Humans, Algorithms
Asia, Cost-Benefit Analysis, Extensively Drug-Resistant Tuberculosis, Decision Trees, Antitubercular Agents, Health Care Costs, Microbial Sensitivity Tests, Drug Costs, Decision Support Techniques, Models, Economic, Treatment Outcome, Predictive Value of Tests, Drug Resistance, Multiple, Bacterial, Tuberculosis, Multidrug-Resistant, Humans, Algorithms
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