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      Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation

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          Abstract

          Nicolas Menzies and colleagues investigate the potential impact and cost-effectiveness of implementing Xpert MTB/RIF for diagnosing tuberculosis in five southern African countries.

          Abstract

          Background

          The Xpert MTB/RIF test enables rapid detection of tuberculosis (TB) and rifampicin resistance. The World Health Organization recommends Xpert for initial diagnosis in individuals suspected of having multidrug-resistant TB (MDR-TB) or HIV-associated TB, and many countries are moving quickly toward adopting Xpert. As roll-out proceeds, it is essential to understand the potential health impact and cost-effectiveness of diagnostic strategies based on Xpert.

          Methods and Findings

          We evaluated potential health and economic consequences of implementing Xpert in five southern African countries—Botswana, Lesotho, Namibia, South Africa, and Swaziland—where drug resistance and TB-HIV coinfection are prevalent. Using a calibrated, dynamic mathematical model, we compared the status quo diagnostic algorithm, emphasizing sputum smear, against an algorithm incorporating Xpert for initial diagnosis. Results were projected over 10- and 20-y time periods starting from 2012. Compared to status quo, implementation of Xpert would avert 132,000 (95% CI: 55,000–284,000) TB cases and 182,000 (97,000–302,000) TB deaths in southern Africa over the 10 y following introduction, and would reduce prevalence by 28% (14%–40%) by 2022, with more modest reductions in incidence. Health system costs are projected to increase substantially with Xpert, by US$460 million (294–699 million) over 10 y. Antiretroviral therapy for HIV represents a substantial fraction of these additional costs, because of improved survival in TB/HIV-infected populations through better TB case-finding and treatment. Costs for treating MDR-TB are also expected to rise significantly with Xpert scale-up. Relative to status quo, Xpert has an estimated cost-effectiveness of US$959 (633–1,485) per disability-adjusted life-year averted over 10 y. Across countries, cost-effectiveness ratios ranged from US$792 (482–1,785) in Swaziland to US$1,257 (767–2,276) in Botswana. Assessing outcomes over a 10-y period focuses on the near-term consequences of Xpert adoption, but the cost-effectiveness results are conservative, with cost-effectiveness ratios assessed over a 20-y time horizon approximately 20% lower than the 10-y values.

          Conclusions

          Introduction of Xpert could substantially change TB morbidity and mortality through improved case-finding and treatment, with more limited impact on long-term transmission dynamics. Despite extant uncertainty about TB natural history and intervention impact in southern Africa, adoption of Xpert evidently offers reasonable value for its cost, based on conventional benchmarks for cost-effectiveness. However, the additional financial burden would be substantial, including significant increases in costs for treating HIV and MDR-TB. Given the fundamental influence of HIV on TB dynamics and intervention costs, care should be taken when interpreting the results of this analysis outside of settings with high HIV prevalence.

          Please see later in the article for the Editors' Summary

          Editors' Summary

          Background

          In 2010, about 9 million people developed tuberculosis (TB)—a contagious bacterial disease that usually infects the lungs—and about 1.5 million people died from the disease. Most of these deaths were in low- and middle-income countries, and a quarter were in HIV-positive individuals, who are particularly susceptible to TB. Mycobacterium tuberculosis, the bacterium that causes TB, is spread in airborne droplets when people with active disease cough or sneeze. The characteristic symptoms of TB are a persistent cough, weight loss, fever, and night sweats. Diagnostic tests for TB include sputum smear analysis (microscopic examination of mucus coughed up from the lungs for the presence of M. tuberculosis) and mycobacterial liquid culture (growth of M. tuberculosis from sputum and determination of its drug sensitivity). TB can be cured by taking several antibiotics daily for at least six months, although the recent emergence of multidrug-resistant TB (MDR-TB) is making the disease increasingly hard to treat.

          Why Was This Study Done?

          To reduce the global TB burden, active disease must be diagnosed quickly and accurately. In most high-burden settings, however, TB diagnosis relies on sputum smear analysis, which fails to identify some people (especially HIV-infected individuals) who have TB. Mycobacterial culture correctly identifies more infected people but is slow and costly, and many high-burden settings lack the infrastructure for high-volume culture diagnosis of TB. Faced with these diagnostic inadequacies, the World Health Organization (WHO) recently recommended the use of Xpert MTB/RIF for initial diagnosis in patients suspected of having MDR-TB or HIV-associated TB. This new, automated DNA test detects M. tuberculosis and DNA differences that make the bacteria resistant to the drug rifampicin (an indicator of MDR-TB) within two hours. Many countries are moving toward adopting Xpert for TB diagnosis, so it is essential to understand the population health impact and cost-effectiveness of diagnostic strategies based on this test. Here, the researchers use a calibrated, dynamic mathematical model of TB to investigate the consequences of Xpert MTB/RIF implementation in five southern African countries where both TB-HIV coinfection and MDR-TB are common.

          What Did the Researchers Do and Find?

          The researchers used their mathematical model, which simulates the movement of individuals through different stages of TB infection, to investigate the potential health and economic consequences of implementing Xpert for initial TB diagnosis in Botswana, Lesotho, Namibia, South Africa, and Swaziland. In the modeled scenarios, compared to an diagnostic approach based on sputum smear (the “status quo”), implementation of Xpert averted an estimated 132,000 TB cases and 182,000 TB deaths in southern Africa over the ten years following its introduction, reduced the proportion of the population with TB by 28%, and increased health service costs by US$460 million. Much of this cost increase reflected increased antiretroviral therapy costs for TB/HIV-infected individuals who survived TB infection because of better case-finding and treatment. Finally, relative to the status quo, over ten years, Xpert implementation in southern Africa cost US$959 for every DALY (disability-adjusted life-year) averted. Cost-effectiveness ratios in individual countries ranged from US$792 per DALY averted in Swaziland to US$1,257 per DALY averted in Botswana.

          What Do These Findings Mean?

          These findings suggest that Xpert implementation in southern Africa could substantially reduce TB illness and death through improved case-finding and treatment, but that the impact of Xpert on long-term transmission dynamics may be more limited. Although the additional financial burden associated with Xpert roll-out is likely to be substantial, these findings suggest that using Xpert for TB diagnosis offers reasonable value given its cost. WHO considers any intervention with a cost-effectiveness ratio less than the per-capita gross domestic product (GDP) highly cost-effective—in 2010, the per-capita GDP ranged from US$7,000 in South Africa and Botswana to US$982 in Lesotho.

          These findings may not be generalizable to regions with different HIV infection rates, and their accuracy is likely to be affected by the quality of the data fed into the mathematical model and by the structure of the model. Thus, it is essential that the impact of Xpert-based TB diagnosis be carefully evaluated as the approach is rolled out, and that the information generated by these evaluations be used to improve the accuracy of model-based estimates of the long-term effects of this new strategy for TB diagnosis.

          Additional Information

          Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001347.

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          Most cited references67

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          Recommendations of the Panel on Cost-effectiveness in Health and Medicine.

          To develop consensus-based recommendations for the conduct of cost-effectiveness analysis (CEA). This article, the second in a 3-part series, describes the basis for recommendations constituting the reference case analysis, the set of practices developed to guide CEAs that inform societal resource allocation decisions, and the content of these recommendations. The Panel on Cost-Effectiveness in Health and Medicine, a nonfederal panel with expertise in CEA, clinical medicine, ethics, and health outcomes measurement, was convened by the US Public Health Service (PHS). The panel reviewed the theoretical foundations of CEA, current practices, and alternative methods used in analyses. Recommendations were developed on the basis of theory where possible, but tempered by ethical and pragmatic considerations, as well as the needs of users. The panel developed recommendations through 2 1/2 years of discussions. Comments on preliminary drafts prepared by panel working groups were solicited from federal government methodologists, health agency officials, and academic methodologists. The panel's methodological recommendations address (1) components belonging in the numerator and denominator of a cost-effectiveness (C/E) ratio; (2) measuring resource use in the numerator of a C/E ratio; (3) valuing health consequences in the denominator of a C/E ratio; (4) estimating effectiveness of interventions; (5) incorporating time preference and discounting; and (6) handling uncertainty. Recommendations are subject to the ¿rule of reason,¿ balancing the burden engendered by a practice with its importance to a study. If researchers follow a standard set of methods in CEA, the quality and comparability of studies, and their ultimate utility, can be much improved.
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            Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities.

            With an estimated 9.4 million new cases globally, tuberculosis (TB) continues to be a major public health concern. Eighty percent of all cases worldwide occur in 22 high-burden, mainly resource-poor settings. This devastating impact of tuberculosis on vulnerable populations is also driven by its deadly synergy with HIV. Therefore, building capacity and enhancing universal access to rapid and accurate laboratory diagnostics are necessary to control TB and HIV-TB coinfections in resource-limited countries. The present review describes several new and established methods as well as the issues and challenges associated with implementing quality tuberculosis laboratory services in such countries. Recently, the WHO has endorsed some of these novel methods, and they have been made available at discounted prices for procurement by the public health sector of high-burden countries. In addition, international and national laboratory partners and donors are currently evaluating other new diagnostics that will allow further and more rapid testing in point-of-care settings. While some techniques are simple, others have complex requirements, and therefore, it is important to carefully determine how to link these new tests and incorporate them within a country's national diagnostic algorithm. Finally, the successful implementation of these methods is dependent on key partnerships in the international laboratory community and ensuring that adequate quality assurance programs are inherent in each country's laboratory network.
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              Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies.

              Insufficient data are available from single cohort studies to allow estimation of the prognosis of HIV-1 infected, treatment-naive patients who start highly active antiretroviral therapy (HAART). The ART Cohort Collaboration, which includes 13 cohort studies from Europe and North America, was established to fill this knowledge gap. We analysed data on 12,574 adult patients starting HAART with a combination of at least three drugs. Data were analysed by intention-to-continue-treatment, ignoring treatment changes and interruptions. We considered progression to a combined endpoint of a new AIDS-defining disease or death, and to death alone. The prognostic model that generalised best was a Weibull model, stratified by baseline CD4 cell count and transmission group. FINDINGS During 24,310 person-years of follow up, 1094 patients developed AIDS or died and 344 patients died. Baseline CD4 cell count was strongly associated with the probability of progression to AIDS or death: compared with patients starting HAART with less than 50 CD4 cells/microL, adjusted hazard ratios were 0.74 (95% CI 0.62-0.89) for 50-99 cells/microL, 0.52 (0.44-0.63) for 100-199 cells/microL, 0.24 (0.20-0.30) for 200-349 cells/microL, and 0.18 (0.14-0.22) for 350 or more CD4 cells/microL. Baseline HIV-1 viral load was associated with a higher probability of progression only if 100,000 copies/microL or above. Other independent predictors of poorer outcome were advanced age, infection through injection-drug use, and a previous diagnosis of AIDS. The probability of progression to AIDS or death at 3 years ranged from 3.4% (2.8-4.1) in patients in the lowest-risk stratum for each prognostic variable, to 50% (43-58) in patients in the highest-risk strata. The CD4 cell count at initiation was the dominant prognostic factor in patients starting HAART. Our findings have important implications for clinical management and should be taken into account in future treatment guidelines.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                November 2012
                November 2012
                20 November 2012
                : 9
                : 11
                : e1001347
                Affiliations
                [1 ]Center for Health Decision Sciences, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [2 ]Institute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, United States of America
                [3 ]Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [4 ]Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
                [5 ]Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
                [6 ]Department of Global Health and Population, Harvard School of Public Health, Boston, Massachusetts, United States of America
                Boston University, United States of America
                Author notes

                JAS and MM are members of the PLOS Medicine editorial board. The authors declare that no other competing interests exist.

                Analyzed the data: NAM. Wrote the first draft of the manuscript: NAM. Contributed to the writing of the manuscript: TC HHL MM JAS. ICMJE criteria for authorship read and met: NAM TC HHL MM JAS. Agree with manuscript results and conclusions: NAM TC HHL MM JAS. Conceived and designed the study: NAM TC MM JAS. Contributed to model design and parameterization: NAM TC HHL MM JAS.

                Article
                PMEDICINE-D-11-02547
                10.1371/journal.pmed.1001347
                3502465
                23185139
                06fd646c-83b3-4c4d-8e93-f09554cb0cad
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 October 2011
                : 12 October 2012
                Page count
                Pages: 17
                Funding
                NAM and JAS were supported in part by funding from UNITAID. NAM was also supported by a training grant from the Massachusetts General Hospital's Program in Cancer Outcomes and Training (NIH Grant No. R25 CA092203). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
                Categories
                Research Article
                Medicine
                Epidemiology
                Infectious Disease Epidemiology
                Global Health
                Infectious Diseases
                Bacterial Diseases
                Tuberculosis
                Multi-Drug-Resistant Tuberculosis
                Sexually Transmitted Diseases
                AIDS
                Infectious Disease Control
                Infectious Disease Modeling
                Non-Clinical Medicine
                Health Economics
                Cost Effectiveness

                Medicine
                Medicine

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