Dynamic modelling of improved diagnostic testing for drug-resistant tuberculosis in high burden settings
摘要
Limited diagnostic testing for drug-resistant TB (DR-TB) may lead to high rates of misdiagnosis and undertreatment. Current diagnostic tests focus only on detection of rifampicin-resistant TB (RR-TB). This study aims to determine the impact of improved diagnostic testing for a wider range of drug resistance on DR-TB outcomes in high-burden TB settings, using the Philippines and Thailand as case studies.
MethodsA dynamic compartmental model was designed to simulate population level TB transmission, accounting for acquired drug resistance from treatment failure of drug susceptible TB. Three scenarios were analyzed: (1) Use of GeneXpert MTB/RIF on all presumptive TB cases (Status Quo); (2) GeneXpert MTB/RIF + GeneXpert XDR, (3) GeneXpert MTB/RIF + targeted Next Generation Sequencing (tNGS). Scenarios were modelled over a 10-year period, from 2025 to 2034.
ResultsCompared to the status quo, Scenario 2 results in a fourfold increase in annual DR-TB cases diagnosed in the Philippines and a fivefold increase in Thailand. DR-TB treatment failure decreases by 20% in the Philippines and 23% in Thailand. Scenario 3 further increases DR-TB case detection, reducing DR-TB treatment failure by 26% in the Philippines and 29% in Thailand. Reductions in DR-TB incidence and mortality ranged from 3 to 6%.
ConclusionThe use of GeneXpert XDR or tNGS as an additional diagnostic test for DR-TB significantly improves DR-TB case detection and reduces treatment failure, supporting their consideration for use in high burden settings. These findings highlight the importance of detecting a wider range of TB resistance in addition to RR-TB, the potential impact these improved diagnostic tests can have on DR-TB outcomes, and the need for additional research on cost-effectiveness of these interventions.