Rapid diagnosis of tuberculosis with the Xpert MTB/RIF assay in high burden countries: A cost-effectiveness analysis

Background: xpert mtb/rif (xpert) is a promising new rapid diagnostic technology for tuberculosis (tb) that has characteristics that suggest large-scale roll-out. however,because the test is expensive,there are concerns among tb program managers and policy makers regarding its affordability for low- and middle-income settings. methods and findings: we estimate the impact of the introduction of xpert on the costs and cost-effectiveness of tb care using decision analytic modelling,comparing the introduction of xpert to a base case of smear microscopy and clinical diagnosis in india,south africa,and uganda. the introduction of xpert increases tb case finding in all three settings; from 72%-85% to 95%-99% of the cohort of individuals with suspected tb,compared to the base case. diagnostic costs (including the costs of testing all individuals with suspected tb) also increase: from us$28-us$49 to us$133-us$146 and us$137-us$151 per tb case detected when xpert is used in addition to and as a replacement of smear microscopy,respectively. the incremental cost effectiveness ratios (icers) for using xpert in addition to smear microscopy,compared to the base case,range from us$41-$110 per disability adjusted life year (daly) averted. likewise the icers for using xpert as a replacement of smear microscopy range from us$52-$138 per daly averted. these icers are below the world health organization (who) willingness to pay threshold. conclusions: our results suggest that xpert is a cost-effective method of tb diagnosis,compared to a base case of smear microscopy and clinical diagnosis of smear-negative tb in low- and middle-income settings where,with its ability to substantially increase case finding,it has important potential for improving tb diagnosis and control. the extent of cost-effectiveness gain to tb programmes from deploying xpert is primarily dependent on current tb diagnostic practices. further work is required during scale-up to validate these findings. © 2011 vassall et al.