Objective To evaluate the cost-effectiveness of three LTBI screening strategies: the tuberculin skin test (TST), the T-SPOT.TB and the combination of TST and T-SPOT (TST+T.SPOT), to provide economic evidence for T.SPOT application in China. Methods A decision analysis model evaluated three strategies among a cohort of 1000 tuberculosis (TB) close contacts, using incremental cost-effectiveness of prevention a active TB patient (1 year post contact). Meta analyses were conducted to calculate the key parameters of T.SPOT and TST. The official data or literature was searched and the unaccessible data was to specify other parameters, such as cost, LTBI prevalence, etc. The one-way sensitivity analysis was performed, varying key parameters over a wide range of reasonable values to evaluate the impact of data uncertainties and to determine the robustness of our overall conclusion. Results a) As for the total cost, the TST+T.SPOT strategy (?212 213.81 per 1 000 contacts) cost the least, while the single T.SPOT strategy cost the most; b) Subsequently, the TST+T.SPOT strategy required less contacts to be treated to prevent an active case of TB (8.31) than the single TST strategy (25.67); c) the TST+T.SPOT strategy shared the most cost-effectiveness (?3 063.50 per active TB case prevented) than the single TST or T.SPOT strategy; and d) The results of one-way sensitivity analyses showed that cost-effectiveness values were sensitive to changes in LTBI prevalence (gt;60%), Sen and Spn of TST test (gt;70%), with the single TST being superior to the single T.SPOT. Conclusion The Single T.SPOT strategy enjoys the most cases prevented from active TB, while the TST+S.SPOT strategy is the most cost-effective. The conclusion is sensitive to a few parameters, such as LTBI prevalence, but the TST+T.SPOT strategy is always the best.
Tuberculosis risk prediction and drug intervention for latent tuberculosis infection (LTBI) patients plays an important role in achieving the goal of eliminating tuberculosis. At present, the diagnostic methods of LTBI still have some defects and cannot predict the risk of LTBI progression to active tuberculosis. In this paper, studies of LTBI advancing into tuberculosis in genomics, transcriptomics, proteomics and metabonomics have been comprehensively summarized, and the further development of markers for risk prediction is prospected.