Xpert MTB/RIF is cost-effective, but less so than expected

In this issue of The Lancet Global Health, Anil Pooran and colleagues1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar present a previously announced economic evaluation of the TB-NEAT trial2Theron G Zijenah L Chanda D et al.Feasibility, accuracy, and clinical effect of point-of-care Xpert MTB/RIF testing for tuberculosis in primary-care settings in Africa: a multicentre, randomised, controlled trial.Lancet. 2014; 383: 424-435Summary Full Text Full Text PDF PubMed Scopus (338) Google Scholar in southern Africa. This evaluation adds important additional aspects to the economic evaluation of the previously published XTEND trial,3Vassall A Siapka M Foster N et al.Cost-effectiveness of Xpert MTB/RIF for tuberculosis diagnosis in South Africa: a real-world cost analysis and economic evaluation.Lancet Glob Health. 2017; 5: e710-e719Summary Full Text Full Text PDF PubMed Scopus (49) Google Scholar which did not show improved cost-effectiveness of tuberculosis diagnosis. Pooran and colleagues1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar report on the outcomes of a cost-effectiveness analysis using clinical endpoints, with an assessment of the empirically collected costs and derived effectiveness measures from the clinical outcome data of Xpert MTB/RIF (Xpert) implementation versus standard smear microscopy. In the TB-NEAT trial,2Theron G Zijenah L Chanda D et al.Feasibility, accuracy, and clinical effect of point-of-care Xpert MTB/RIF testing for tuberculosis in primary-care settings in Africa: a multicentre, randomised, controlled trial.Lancet. 2014; 383: 424-435Summary Full Text Full Text PDF PubMed Scopus (338) Google Scholar these authors previously showed that Xpert roll-out did not improve tuberculosis morbidity measured with the TBscore4Wejse C Gustafson P Nielsen J Gomes VF Aaby P Andersen PL Sodemann M TBscore: signs and symptoms from tuberculosis patients in a low-resource setting have predictive value and may be used to assess clinical course.Scand J Infect Dis. 2008; 40: 111-120Crossref PubMed Scopus (116) Google Scholar despite showing several benefits (not all significant), including more patients starting same-day treatment, more culture-positive patients starting therapy, and a shorter time to treatment. They have now collected an impressive amount of cost data to show the effect of roll-out on costs,1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar which is a highly relevant research matter since Xpert is now endorsed by WHO for front-line diagnosis. Xpert is a somewhat expensive test in terms of the equipment and kits needed, hence costs are expected to exceed previous costs of standard care. The major contribution of the present study1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar is that the incremental costs per treatment completion has been laid out, which is important information for policy makers. The authors must therefore be commended for their ability to gather cost data as a major new intervention was rolled-out to peripheral clinics. This study should serve as an example for other major global health interventions, which are often implemented based on data generated far from the primary care facilities where they are put to use. The authors should also be congratulated for making such a considerable effort to collect cost data while doing a clinical trial; there is much to learn from this report with regard to determination of cost-effectiveness of major global health interventions, which is a major contribution to the literature. In fact, the report is also an important corrigendum to the extensive modelling of effect and cost-effectiveness of interventions, such as new vaccines or changes in the vaccination programme. What has been learned from this analysis? Certainly an important take-home message from the cost-effective analysis of the TB-NEAT trial1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar is that, as previously anticipated, Xpert is quite a bit more expensive than smear microscopy, in particular if delivered at point of care.5Wejse C Point-of-care diagnostics for tuberculosis elimination?.Lancet. 2014; 383: 388-390Summary Full Text Full Text PDF PubMed Scopus (10) Google Scholar However, the investment might lead to an increase in suitable patients starting treatment on the same day as diagnosis and more patients completing treatment, all with incremental costs between US$1680 and $9450 per patient. But was the roll-out of Xpert cost-effective? The answer depends on the willingness to pay; however, missing tuberculosis cases surely also come at a cost—at the individual and societal levels. Therefore, although Xpert is cost-effective from the perspective of starting more patients early on treatment, the somewhat limited incremental cost-effectiveness adds to the notion that the Xpert roll-out is not likely to be a major game-changer for tuberculosis elimination; a point that is also underlined by the fact that another cost-effective analysis3Vassall A Siapka M Foster N et al.Cost-effectiveness of Xpert MTB/RIF for tuberculosis diagnosis in South Africa: a real-world cost analysis and economic evaluation.Lancet Glob Health. 2017; 5: e710-e719Summary Full Text Full Text PDF PubMed Scopus (49) Google Scholar was not able to document cost-effectiveness of Xpert roll-out in South Africa. Another important question answered by Pooran and colleagues1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar was whether the roll-out was as cost-effective as previously stipulated in the many attempts to model what the effect of Xpert roll-out would be. The short answer is no. A considerable amount of mathematical modelling evidence supports the cost-effectiveness of Xpert;6Menzies NA Cohen T Lin HH et al.Population health impact and cost-effectiveness of tuberculosis diagnosis with Xpert MTB/RIF: a dynamic simulation and economic evaluation.PLoS Med. 2012; 9: e1001347Crossref PubMed Scopus (155) Google Scholar, 7Langley I Lin HH Egwaga S et al.Assessment of the patient, health system, and population effects of Xpert MTB/RIF and alternative diagnostics for tuberculosis in Tanzania: an integrated modelling approach.Lancet Glob Health. 2014; 2: e581-e591Summary Full Text Full Text PDF PubMed Scopus (50) Google Scholar, 8Menzies NA Gomez GB Bozzani F et al.Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models.Lancet Glob Health. 2016; 4: e816-e826Summary Full Text Full Text PDF PubMed Scopus (59) Google Scholar however, the actual cost data gathered here has shown that the assumptions behind previous modelling studies were wrong and it is important to learn from these mistakes in future modelling studies. Pooran and colleagues highlight that the effect of empirical treatment was not taken into account in the previous models, and empirical treatment is indeed an underestimated asset in smear microscopy-based facilities. Would a similar investment to the one needed for global Xpert roll-out—spent on training of staff, good clinic facilities, and increased empirical treatment based on good algorithms9Rudolf F Haraldsdottir TL Mendes MS et al.Can case-finding among pulmonary tuberculosis suspects be improved? Oberservations from Bissau.Int J TB Lung Dis. 2014; 18: 277-285Crossref PubMed Scopus (23) Google Scholar— lead to some of the same outcomes, perhaps even at a lesser cost per patient diagnosed, treated, and completed? This question will probably remain unanswered; the roll-out is sensibly well underway and contributes important clinical knowledge regarding drug-resistance. Yet, it is important to learn from this kind of evaluation based on real-life data before the next roll-out of a new diagnostic tool or vaccine, and these evaluations should be used to guide the further scale-up, as described by Pooran and colleagues,1Pooran A Theron G Zijenah L et al.Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluation.Lancet Glob Health. 2019; 7: e798-e807Summary Full Text Full Text PDF PubMed Scopus (27) Google Scholar with a focus on tuberculosis hotspots, difficult transportation access, low rate of empirical treatment, and high rates of resistance. These are obvious areas in which Xpert will be more cost-effectiveness in the continued drive to end the tuberculosis epidemic with limited funds. I declare no competing interests. Point of care Xpert MTB/RIF versus smear microscopy for tuberculosis diagnosis in southern African primary care clinics: a multicentre economic evaluationIn southern Africa, although point-of-care Xpert unit cost is higher than Lab Xpert, it is likely to offer good value for money relative to smear microscopy. With the current availability of point-of-care nucleic acid amplification platforms (eg, Xpert Edge), these data inform much needed investment and resource allocation strategies in tuberculosis endemic settings. Full-Text PDF Open Access