Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation
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
Vyšlo v časopise:
Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation. PLoS Med 9(11): e32767. doi:10.1371/journal.pmed.1001347
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1001347
Souhrn
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
Zdroje
1. World Health Organization (2011) Global tuberculosis control: WHO report 2011. Geneva: World Health Organization.
2. ObermeyerZ, Abbott-KlafterJ, MurrayCJ (2008) Has the DOTS strategy improved case finding or treatment success? An empirical assessment. PLoS ONE 3: e1721 doi:10.1371/journal.pone.0001721.
3. DenkingerCM, PaiM (2011) Point-of-care tuberculosis diagnosis: are we there yet? Lancet Infect Dis 12: 169–170.
4. CorbettEL, WattCJ, WalkerN, MaherD, WilliamsBG, et al. (2003) The growing burden of tuberculosis: global trends and interactions with the HIV epidemic. Arch Intern Med 163: 1009–1021.
5. ElliottAM, HalwiindiB, HayesRJ, LuoN, TemboG, et al. (1993) The impact of human immunodeficiency virus on presentation and diagnosis of tuberculosis in a cohort study in Zambia. J Trop Med Hyg 96: 1–11.
6. GetahunH, HarringtonM, O'BrienR, NunnP (2007) Diagnosis of smear-negative pulmonary tuberculosis in people with HIV infection or AIDS in resource-constrained settings: informing urgent policy changes. Lancet 369: 2042–2049.
7. Acuna-VillaordunaC, VassallA, HenostrozaG, SeasC, GuerraH, et al. (2008) Cost-effectiveness analysis of introduction of rapid, alternative methods to identify multidrug-resistant tuberculosis in middle-income countries. Clin Infect Dis 47: 487–495.
8. Van DeunA, MartinA, PalominoJC (2010) Diagnosis of drug-resistant tuberculosis: reliability and rapidity of detection. Int J Tuberc Lung Dis 14: 131–140.
9. ParsonsLM, SomoskoviA, GutierrezC, LeeE, ParamasivanCN, et al. (2011) Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities. Clin Microbiol Rev 24: 314–350.
10. Tuberculosis Division (2005) Tuberculosis bacteriology—priorities and indications in high prevalence countries: position of the technical staff of the Tuberculosis Division of the International Union Against Tuberculosis and Lung Disease. Int J Tuberc Lung Dis 9: 355–361.
11. FarmerP, BayonaJ, BecerraM, FurinJ, HenryC, et al. (1998) The dilemma of MDR-TB in the global era. Int J Tuberc Lung Dis 2: 869–876.
12. MeintjesG, SchoemanH, MorroniC, WilsonD, MaartensG (2008) Patient and provider delay in tuberculosis suspects from communities with a high HIV prevalence in South Africa: a cross-sectional study. BMC Infect Dis 8: 72.
13. Van RieA, EnarsonD (2006) XDR tuberculosis: an indicator of public-health negligence. Lancet 368: 1554–1556.
14. BoehmeCC, NabetaP, HillemannD, NicolMP, ShenaiS, et al. (2010) Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med 363: 1005–1015.
15. BoehmeCC, NicolMP, NabetaP, MichaelJS, GotuzzoE, et al. (2011) Feasibility, diagnostic accuracy, and effectiveness of decentralised use of the Xpert MTB/RIF test for diagnosis of tuberculosis and multidrug resistance: a multicentre implementation study. Lancet 377: 1495–1505.
16. HelbD, JonesM, StoryE, BoehmeC, WallaceE, et al. (2010) Rapid detection of Mycobacterium tuberculosis and rifampin resistance by use of on-demand, near-patient technology. J Clin Microbiol 48: 229–237.
17. TheronG, PeterJ, van Zyl-SmitR, MishraH, StreicherE, et al. (2011) Evaluation of the Xpert MTB/RIF assay for the diagnosis of pulmonary tuberculosis in a high HIV prevalence setting. Am J Respir Crit Care Med 184: 132–140.
18. RachowA, ZumlaA, HeinrichN, Rojas-PonceG, MtafyaB, et al. (2011) Rapid and accurate detection of Mycobacterium tuberculosis in sputum samples by Cepheid Xpert MTB/RIF assay—a clinical validation study. PLoS ONE 6: e20458 doi:10.1371/journal.pone.0020458.
19. Selibas K, Hanrahan C, Deery C, Dansey H, Clouse K, et al.. (2012) TB suspects with negative initial Xpert [abstract]. 3rd South African Tuberculosis Conference; 12–15 June 2012; Durban, South Africa.
20. World Health Organization (2010) Roadmap for rolling out Xpert MTB/RIF for rapid diagnosis of TB and MDR-TB. Geneva: World Health Organization.
21. World Health Organization (2012) WHO monitoring of Xpert MTB/RIF roll-out: orders of GeneXperts and Xpert MTB/RIF cartridges [database]. Available: http://www.stoptb.org/wg/gli/assets/documents/map/1/atlas.html. Accessed 4 September 2012. Geneva: World Health Organization.
22. Mirzayev F (2012) Current dynamics in the Xpert MTB/RIF assay pricing mechanisms [abstract]. Xpert MTB/RIF Early Implementers Meeting; 18–19 April 2012; Annecy, France. Geneva: World Health Organization.
23. Cepheid Pharmaceuticals (2012 Aug 6) Cepheid announces first phase of Xpert MTB/RIF buy-down for high burden developing countries. Sunnyvale (California): Cepheid Pharmaceuticals.
24. DowdyDW, CattamanchiA, SteingartKR, PaiM (2011) Is scale-up worth it? Challenges in economic analysis of diagnostic tests for tuberculosis. PLoS Med 8: e1001063 doi:10.1371/journal.pmed.1001063.
25. EvansCA (2011) GeneXpert—a game-changer for tuberculosis control? PLoS Med 8: e1001064 doi:10.1371/journal.pmed.1001064.
26. KirwanDE, CardenasMK, GilmanRH (2012) Rapid implementation of new tb diagnostic tests: is it too soon for a global roll-out of Xpert MTB/RIF? Am J Trop Med Hyg 87: 197–201.
27. LawnSD, BrooksSV, KranzerK, NicolMP, WhitelawA, et al. (2011) Screening for HIV-associated tuberculosis and rifampicin resistance before antiretroviral therapy using the Xpert MTB/RIF assay: a prospective study. PLoS Med 8: e1001067 doi:10.1371/journal.pmed.1001067.
28. ScottLE, McCarthyK, GousN, NdunaM, Van RieA, et al. (2011) Comparison of Xpert MTB/RIF with other nucleic acid technologies for diagnosing pulmonary tuberculosis in a high HIV prevalence setting: a prospective study. PLoS Med 8: e1001061 doi:10.1371/journal.pmed.1001061.
29. TrebucqA, EnarsonDA, ChiangCY, Van DeunA, HarriesAD, et al. (2011) Xpert(R) MTB/RIF for national tuberculosis programmes in low-income countries: when, where and how? Int J Tuberc Lung Dis 15: 1567–1572.
30. Van RieA, MelletK, JohnMA, ScottL, Page-ShippL, et al. (2012) False-positive rifampicin resistance on Xpert(R) MTB/RIF: case report and clinical implications. Int J Tuberc Lung Dis 16: 206–208.
31. RamsayA, SteingartKR, PaiM (2010) Assessing the impact of new diagnostics on tuberculosis control. Int J Tuberc Lung Dis 14: 1506–1507.
32. TheronG, PooranA, PeterJ, van Zyl-SmitR, Kumar MishraH, et al. (2012) Do adjunct tuberculosis tests, when combined with Xpert MTB/RIF, improve accuracy and the cost of diagnosis in a resource-poor setting? Eur Respir J 40: 161–168.
33. World Health Organization (2011) Rapid implementation of the Xpert MTB/RIF diagnostic test: technical and operational ‘how-to’. Geneva: World Health Organization.
34. PeltzerK, MatsekeG, MzoloT, MajajaM (2009) Determinants of knowledge of HIV status in South Africa: results from a population-based HIV survey. BMC Public Health 9: 174.
35. BaltussenR, FloydK, DyeC (2005) Cost effectiveness analysis of strategies for tuberculosis control in developing countries. BMJ 331: 1364.
36. CohenT, LipsitchM, WalenskyRP, MurrayM (2006) Beneficial and perverse effects of isoniazid preventive therapy for latent tuberculosis infection in HIV-tuberculosis coinfected populations. Proc Natl Acad Sci U S A 103: 7042–7047.
37. DowdyDW, ChaissonRE (2009) The persistence of tuberculosis in the age of DOTS: reassessing the effect of case detection. Bull World Health Organ 87: 296–304.
38. DyeC, GarnettGP, SleemanK, WilliamsBG (1998) Prospects for worldwide tuberculosis control under the WHO DOTS strategy. Directly observed short-course therapy. Lancet 352: 1886–1891.
39. DyeC, WilliamsBG (2000) Criteria for the control of drug-resistant tuberculosis. Proc Natl Acad Sci U S A 97: 8180–8185.
40. MurrayCJ, SalomonJA (1998) Modeling the impact of global tuberculosis control strategies. Proc Natl Acad Sci U S A 95: 13881–13886.
41. SalomonJA, Lloyd-SmithJO, GetzWM, ReschS, SanchezMS, et al. (2006) Prospects for advancing tuberculosis control efforts through novel therapies. PLoS Med 3: e273 doi:10.1371/journal.pmed.0030273.
42. DaleyCL, SmallPM, SchecterGF, SchoolnikGK, McAdamRA, et al. (1992) An outbreak of tuberculosis with accelerated progression among persons infected with the human immunodeficiency virus. An analysis using restriction-fragment-length polymorphisms. N Engl J Med 326: 231–235.
43. ShaferRW, SinghSP, LarkinC, SmallPM (1995) Exogenous reinfection with multidrug-resistant Mycobacterium tuberculosis in an immunocompetent patient. Tuber Lung Dis 76: 575–577.
44. BucherHC, GriffithLE, GuyattGH, SudreP, NaefM, et al. (1999) Isoniazid prophylaxis for tuberculosis in HIV infection: a meta-analysis of randomized controlled trials. AIDS 13: 501–507.
45. ManosuthiW, TantanathipP, ChimsuntornS, EampokarapB, ThongyenS, et al. (2010) Treatment outcomes of patients co-infected with HIV and tuberculosis who received a nevirapine-based antiretroviral regimen: a four-year prospective study. Int J Infect Dis 14: e1013–e1017.
46. van der SandeMA, Schim van der LoeffMF, BennettRC, DowlingM, AveikaAA, et al. (2004) Incidence of tuberculosis and survival after its diagnosis in patients infected with HIV-1 and HIV-2. AIDS 18: 1933–1941.
47. AdamMA, JohnsonLF (2009) Estimation of adult antiretroviral treatment coverage in South Africa. S Afr Med J 99: 661–667.
48. GranichRM, GilksCF, DyeC, De CockKM, WilliamsBG (2009) Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet 373: 48–57.
49. StoverJ, BollingerL, AvilaC (2011) Estimating the impact and cost of the WHO 2010 recommendations for antiretroviral therapy. AIDS Res Treat 2011: 738271.
50. UNAIDS Reference Group on Estimates, Modelling and Projections (2011) Technical meeting to review Spectrum 2011 and considering potential bias in DHS and ANC data. Geneva: Joint United Nations Programme on HIV/AIDS.
51. DowdyDW, O'BrienMA, BishaiD (2008) Cost-effectiveness of novel diagnostic tools for the diagnosis of tuberculosis. Int J Tuberc Lung Dis 12: 1021–1029.
52. PooleD, RafteryAE (2000) Inference for deterministic simulation models: the Bayesian melding approach. J Am Stat Assoc 95: 452.
53. RafteryAE, GivensGH, ZehJE (1995) Inference from a deterministic population dynamics model for bowhead whales. J Am Stat Assoc 90: 402–430.
54. AlkemaL, RafteryAE, BrownT (2008) Bayesian melding for estimating uncertainty in national HIV prevalence estimates. Sex Transm Infect 84: i11–i16.
55. AlkemaL, RafteryAE, ClarkSJ (2007) Probabilistic projections of HIV prevalence using Bayesian melding. Ann Appl Stat 1: 229–248.
56. BrownT, BaoL, RafteryAE, SalomonJA, BaggaleyRF, et al. (2010) Modelling HIV epidemics in the antiretroviral era: the UNAIDS Estimation and Projection package 2009. Sex Transm Infect 86 (Suppl 2)
ii3–ii10.
57. World Health Organization (2011) Tuberculosis (TB) [database]. Available: http://www.who.int/tb/country/data/download/en/index.html. Accessed 30 September 2011. Geneva: World Health Organization.
58. World Health Organization (2010) Multidrug and extensively drug-resistant TB (M/XDR-TB): 2010 global report on surveillance and response. Geneva: World Health Organization.
59. Rubin D (1988) Using the SIR algorithm to simulate posterior distributions. In: Bernardo JM, DeGroot MH, Lindley DV, Smith AFM, editors. Bayesian statistics 3. Oxford: Oxford University Press. pp. 395–402.
60. Joint United Nations Programme on HIV/AIDS (2010) Towards universal access: scaling up priority HIV/AIDS interventions in the health sector. Progress report 2010. Geneva: Joint United Nations Programme on HIV/AIDS.
61. World Health Organization (2006) Antiretroviral therapy for HIV infection in adults and adolescents: recommendations for a public health approach—2006 revision. Geneva: World Health Organization.
62. World Health Organization (2010) Antiretroviral therapy for HIV infection in adults and adolescents: recommendations for a public health approach—2010 revision. Geneva: World Health Organization.
63. World Health Organization (2011) Global price reporting mechanism for HIV, tuberculosis and malaria. Available: http://www.who.int/hiv/amds/gprm/en/. Accessed 21 May 2011. Geneva: World Health Organization.
64. Meyer-RathG, SchnippelK, LongL, MacLeodW, SanneI, et al. (2012) The impact and cost of scaling up GeneXpert MTB/RIF in South Africa. PLoS ONE 7: e36966 doi:10.1371/journal.pone.0036966.
65. SchnippelK, Meyer-RathG, LongL, MacleodW, SanneI, et al. (2012) Scaling up Xpert MTB/RIF technology: the costs of laboratory- vs. clinic-based roll-out in South Africa. Trop Med Int Health 17: 1142–1151.
66. Murray CJL, Lopez AD (1996) The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and projected to 2020. Cambridge (Massachusetts): Harvard University Press.
67. World Health Organization (2004) Global burden of disease 2004 update: disability weights for diseases and conditions. Geneva: World Health Organization.
68. Tan Torres T, Baltussen R, Adam T, Hutubessy R, Acharya A, et al.. (2003) Making choices in health: WHO guide to cost effectiveness analysis. Geneva: World Health Organization.
69. WeinsteinMC, SiegelJE, GoldMR, KamletMS, RussellLB (1996) Recommendations of the Panel on Cost-effectiveness in Health and Medicine. JAMA 276: 1253–1258.
70. HutubessyR, ChisholmD, EdejerTT (2003) Generalized cost-effectiveness analysis for national-level priority-setting in the health sector. Cost Eff Resour Alloc 1: 8.
71. ImanRL, HeltonJC, CampbellJE (1981) An approach to sensitivity analysis of computer models: part I—introduction, input variable selection and preliminary variable assessment. J Qual Technol 13: 174–183.
72. ImanRL, HeltonJC, CampbellJE (1981) An approach to sensitivity analysis of computer models: part II—ranking of input variables, response surface validation, distribution effect, and technique synopsis variable assessment. J Qual Technol 13: 232–240.
73. World Bank (2011) World development indicators 2011. Washington (District of Columbia): World Bank.
74. National Health Laboratory Service (2012) Xpert testing algorithm. South Africa: National Health Laboratory Service.
75. WilliamsBG, GranichR, De CockKM, GlaziouP, SharmaA, et al. (2010) Antiretroviral therapy for tuberculosis control in nine African countries. Proc Natl Acad Sci U S A 107: 19485–19489.
76. Schnippel K, Rosen S, Shearer K, Martinson N, Long L, et al.. (2012) The cost of inpatient treatment for multi-drug resistant tuberculosis in South Africa [abstract]. International AIDS Economics Network 7th AIDS & Economics Pre-Conference; 22–27 July 2012; Washington, District of Columbia, US.
77. VassallA, van KampenS, SohnH, MichaelJS, JohnKR, et al. (2011) Rapid diagnosis of tuberculosis with the Xpert MTB/rif assay in high burden countries: a cost-effectiveness analysis. PLoS Med 8: e1001120 doi:10.1371/journal.pmed.1001120.
78. AndrewsJR, LawnSD, RusuC, WoodR, NoubaryF, et al. (2012) The cost-effectiveness of routine tuberculosis screening with Xpert MTB/RIF prior to initiation of antiretroviral therapy: a model-based analysis. AIDS 26: 987–995.
79. RachowA, ClowesP, SaathoffE, MtafyaB, MichaelE, et al. (2012) Increased and expedited case detection by Xpert MTB/RIF assay in childhood tuberculosis: a prospective cohort study. Clin Infect Dis 54: 1388–1396.
80. ZarHJ, WorkmanL, IsaacsW, MunroJ, BlackF, et al. (2012) Rapid molecular diagnosis of pulmonary tuberculosis in children using nasopharyngeal specimens. Clin Infect Dis 55: 1088–1095.
81. DyeC, WilliamsBG (2008) Eliminating human tuberculosis in the twenty-first century. J R Soc Interface 5: 653–662.
82. Frieden T (2004) Toman's tuberculosis: case detection, treatment and monitoring: questions and answers, 2nd edition. Geneva: World Health Organization.
83. LevyH, FeldmanC, SachoH, van der MeulenH, KallenbachJ, et al. (1989) A reevaluation of sputum microscopy and culture in the diagnosis of pulmonary tuberculosis. Chest 95: 1193–1197.
84. DowdyDW, ChaissonRE, MaartensG, CorbettEL, DormanSE (2008) Impact of enhanced tuberculosis diagnosis in South Africa: a mathematical model of expanded culture and drug susceptibility testing. Proc Natl Acad Sci U S A 105: 11293–11298.
85. AnglaretX, MingaA, GabillardD, OuassaT, MessouE, et al. (2012) AIDS and non-AIDS morbidity and mortality across the spectrum of CD4 cell counts in HIV-infected adults before starting antiretroviral therapy in Cote d'Ivoire. Clin Infect Dis 54: 714–723.
86. BadriM, LawnSD, WoodR (2006) Short-term risk of AIDS or death in people infected with HIV-1 before antiretroviral therapy in South Africa: a longitudinal study. Lancet 368: 1254–1259.
87. EggerM, MayM, CheneG, PhillipsAN, LedergerberB, et al. (2002) Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet 360: 119–129.
88. MayM, SterneJA, SabinC, CostagliolaD, JusticeAC, et al. (2007) Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies. AIDS 21: 1185–1197.
89. PhillipsA, PezzottiP, CollaborationCascade (2004) Short-term risk of AIDS according to current CD4 cell count and viral load in antiretroviral drug-naive individuals and those treated in the monotherapy era. AIDS 18: 51–58.
90. When To Start Consortium (2009) SterneJA, MayM, CostagliolaD, de WolfF, et al. (2009) Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet 373: 1352–1363.
91. AlbertH (2004) Economic analysis of the diagnosis of smear-negative pulmonary tuberculosis in South Africa: incorporation of a new rapid test, FASTPlaqueTB, into the diagnostic algorithm. Int J Tuberc Lung Dis 8: 240–247.
92. FloydK, SkevaJ, NyirendaT, GausiF, SalaniponiF (2003) Cost and cost-effectiveness of increased community and primary care facility involvement in tuberculosis care in Lilongwe District, Malawi. Int J Tuberc Lung Dis 7: S29–S37.
93. HauslerHP, SinanovicE, KumaranayakeL, NaidooP, SchoemanH, et al. (2006) Costs of measures to control tuberculosis/HIV in public primary care facilities in Cape Town, South Africa. Bull World Health Organ 84: 528–536.
94. HudsonCP, WoodR, MaartensG (2000) Diagnosing HIV-associated tuberculosis: reducing costs and diagnostic delay. Int J Tuberc Lung Dis 4: 240–245.
95. NgandaB, Wang'ombeJ, FloydK, KangangiJ (2003) Cost and cost-effectiveness of increased community and primary care facility involvement in tuberculosis care in Machakos District, Kenya. Int J Tuberc Lung Dis 7: S14–S20.
96. SamandariT, BishaiD, LuteijnM, MosimaneotsileB, MotsamaiO, et al. (2011) Costs and consequences of additional chest x-ray in a tuberculosis prevention program in Botswana. Am J Respir Crit Care Med 183: 1103–1111.
97. SuarezPG, FloydK, PortocarreroJ, AlarconE, RapitiE, et al. (2002) Feasibility and cost-effectiveness of standardised second-line drug treatment for chronic tuberculosis patients: a national cohort study in Peru. Lancet 359: 1980–1989.
98. van CleeffMR, Kivihya-NduggaLE, MemeH, OdhiamboJA, KlatserPR (2005) The role and performance of chest X-ray for the diagnosis of tuberculosis: a cost-effectiveness analysis in Nairobi, Kenya. BMC Infect Dis 5: 111.
99. ReschSC, SalomonJA, MurrayM, WeinsteinMC (2006) Cost-effectiveness of treating multidrug-resistant tuberculosis. PLoS Med 3: e241 doi:10.1371/journal.pmed.0030241.
100. AdamT, EvansDB, MurrayCJ (2003) Econometric estimation of country-specific hospital costs. Cost Eff Resour Alloc 1: 3.
101. BikillaAD, JereneD, RobberstadB, LindtjornB (2009) Cost estimates of HIV care and treatment with and without anti-retroviral therapy at Arba Minch Hospital in southern Ethiopia. Cost Eff Resour Alloc 7: 6.
102. BrattJH, TorpeyK, KabasoM, GondweY (2011) Costs of HIV/AIDS outpatient services delivered through Zambian public health facilities. Trop Med Int Health 16: 110–118.
103. HarlingG, WoodR (2007) The evolving cost of HIV in South Africa: changes in health care cost with duration on antiretroviral therapy for public sector patients. J Acquir Immune Defic Syndr 45: 348–354.
104. MenziesNA, BerrutiAA, BerzonR, FillerS, FerrisR, et al. (2011) The cost of providing comprehensive HIV treatment in PEPFAR-supported programs. AIDS 25: 1753–1760.
105. RosenS, LongL, SanneI (2008) The outcomes and outpatient costs of different models of antiretroviral treatment delivery in South Africa. Trop Med Int Health 13: 1005–1015.
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