Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation 

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Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation  Anil Pooran, PhD, Grant Theron, PhD, Lynn Zijenah, PhD, Duncan Chanda, MD, Petra Clowes, MD, Lawrence Mwenge, MSc, Farirai Mutenherwa, MSc, Paul Lecesse, MD, John Metcalfe, MD, Hojoon Sohn, PhD, Michael Hoelscher, MD, Alex Pym, PhD, Jonny Peter, PhD, David Dowdy, PhD, Keertan Dheda, PhD  The Lancet Global Health  Volume 7, Issue 6, Pages e798-e807 (June 2019) DOI: 10.1016/S2214-109X(19)30164-0 Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

Figure 1 Estimated unit cost per Xpert test Costs (US$, 2014) estimated according to annual test volume either at the clinic (point-of-care Xpert; dashed lines) or central laboratory (Xpert Lab; solid lines) for each individual study site. The overall weighted average of all sites is shown by the grey lines. The cost per Xpert test on the y-axis is expressed on a logarithmic scale. The observed annual number of Xpert tests done at the laboratory (circles) and at the clinic (diamond) in each of the four study sites are indicated. The Xpert Lab is not presented for South Africa as no empirical cost data were collected for this site. For individual and all sites, the observed annual testing frequency was greater at the laboratory compared with the clinic, resulting in a lower Xpert Lab unit cost. However, if the annual number of Xperts performed annually were the same for a given site, the unit cost of point-of-care Xpert would be less than Xpert Lab. Xpert=Xpert MTB/RIF. The Lancet Global Health 2019 7, e798-e807DOI: (10.1016/S2214-109X(19)30164-0) Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

Figure 2 Differences in clinical outcomes comparing point-of-care Xpert to smear microscopy in culture-positive patients and symptomatic patients Error bars indicate 95% CIs. All outcomes and costs are normalised to 1000 patients in each study group. (A) The estimated incremental outcomes for patients ultimately found to have culture-confirmed tuberculosis. (B) Corresponding outcomes in all patients. (C) The estimated incremental costs (US$, 2014); estimates are shown under the assumption that the unit cost of Xpert at all sites can be doubled or halved. Xpert=Xpert MTB/RIF. The Lancet Global Health 2019 7, e798-e807DOI: (10.1016/S2214-109X(19)30164-0) Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

Figure 3 Univariate sensitivity analysis Tornado diagrams showing the effect of changing individual cost parameters on the cost (US$, 2014) per Xpert assay performed at the point of care (A), the incremental cost per treatment initiation (B), and the incremental cost per treatment completion among culture-positive patients across all sites (C). Low and high estimates of each input parameter are shown in parentheses on the left side of each figure. ELY=expected life years. LTF=lost to follow up. Xpert=Xpert MTB/RIF. The Lancet Global Health 2019 7, e798-e807DOI: (10.1016/S2214-109X(19)30164-0) Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

Figure 4 Cost-effectiveness acceptability curves for selected incremental cost-effectiveness ratios The probability of point-of-care Xpert, relative to smear microscopy, being cost-effective was plotted as a function of willingness to pay per culture-positive patient diagnosed by the index test (A), starting treatment (B), starting treatment on same day as diagnosis (C), completing treatment (D), and experiencing improved morbidity for all sites combined (E). The arrow indicates the willingness-to-pay threshold, at which the probability of cost-effectiveness is 90%. Xpert=Xpert MTB/RIF. The Lancet Global Health 2019 7, e798-e807DOI: (10.1016/S2214-109X(19)30164-0) Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions