Testing and treatment decision rules.

BackgroundHost-response-based transcriptional signatures (HrTS) have been developed to identify “incipient tuberculosis (TB)”. No study has reported the cost-effectiveness of HrTS for post-arrival migrant screening programs in low-incidence countries. The aim of this study was to assess the potential health impact and cost-effectiveness of HrTS for post-arrival TB infection screening among new migrants in the United States.Methods and findingsWe used a discrete-event simulation model to compare four strategies: (1) no screening for TB infection or incipient TB; (2) ‘IGRA-only’, screen all with interferon-gamma release assay (IGRA), provide TB preventive treatment for IGRA-positives; (3) ‘IGRA-HrTS’, screen all with IGRA followed by HrTS for IGRA-positives, provide incipient TB treatment for individuals testing positive with both tests; and (4) ‘HrTS-only’, screen all with HrTS, provide incipient TB treatment for HrTS-positives. We assessed outcomes over the lifetime of migrants entering the United Stataes (U.S.) in 2019, assuming HrTS met WHO Target Product Profile (TPP) optimal criteria. We conducted sensitivity analyses to evaluate the robustness of results. Our findings show that at a willingness-to-pay threshold of $150,000 per quality-adjusted life-year (QALY) gained, the IGRA-only strategy was the optimal strategy under both healthcare sector and societal perspectives, with an incremental cost-effectiveness ratio (ICER) of $104,138 and $143,103 per QALY gained, respectively. At a willingness-to-pay of $100,000 per QALY gained the IGRA-HrTS strategy appeared optimal. When the cohort was stratified by TB incidence in the country-of-origin, the IGRA-only strategy was optimal for country-of-origin incidence 100 per 100,000, and the no-screening strategy was optimal for country-of-origin incidence ConclusionsAn HrTS test meeting WHO TPP optimal criteria would be potentially cost-effective for post-arrival screening among a subset of U.S. migrants, but this result was sensitive to multiple factors.