Impact of replacing smear microscopy with Xpert MTB/RIF for diagnosing tuberculosis in Brazil: a stepped-wedge cluster-randomized trial

Betina Durovni, Valeria Saraceni, Susan van den Hof, Anete Trajman, Marcelo Cordeiro-Santos, Solange Cavalcante, Alexandre Menezes, Frank Cobelens, Betina Durovni, Valeria Saraceni, Susan van den Hof, Anete Trajman, Marcelo Cordeiro-Santos, Solange Cavalcante, Alexandre Menezes, Frank Cobelens

Abstract

Background: Abundant evidence on Xpert MTB/RIF accuracy for diagnosing tuberculosis (TB) and rifampicin resistance has been produced, yet there are few data on the population benefit of its programmatic use. We assessed whether the implementation of Xpert MTB/RIF in routine conditions would (1) increase the notification rate of laboratory-confirmed pulmonary TB to the national notification system and (2) reduce the time to TB treatment initiation (primary endpoints).

Methods and findings: We conducted a stepped-wedge cluster-randomized trial from 4 February to 4 October 2012 in 14 primary care laboratories in two Brazilian cities. Diagnostic specimens were included for 11,705 baseline (smear microscopy) and 12,522 intervention (Xpert MTB/RIF) patients presumed to have TB. Single-sputum-sample Xpert MTB/RIF replaced two-sputum-sample smear microscopy for routine diagnosis of pulmonary TB. In total, 1,137 (9.7%) tests in the baseline arm and 1,777 (14.2%) in the intervention arm were positive (p<0.001), resulting in an increased bacteriologically confirmed notification rate of 59% (95% CI = 31%, 88%). However, the overall notification rate did not increase (15%, 95% CI = -6%, 37%), and we observed no change in the notification rate for those without a test result (-3%, 95% CI = -37%, 30%). Median time to treatment decreased from 11.4 d (interquartile range [IQR] = 8.5-14.5) to 8.1 d (IQR = 5.4-9.3) (p = 0.04), although not among confirmed cases (median 7.5 [IQR = 4.9-10.0] versus 7.3 [IQR = 3.4-9.0], p = 0.51). Prevalence of rifampicin resistance detected by Xpert was 3.3% (95% CI = 2.4%, 4.3%) among new patients and 7.4% (95% CI = 4.3%, 11.7%) among retreatment patients, with a 98% (95% CI = 87%, 99%) positive predictive value compared to phenotypic drug susceptibility testing. Missing data in the information systems may have biased our primary endpoints. However, sensitivity analyses assessing the effects of missing data did not affect our results.

Conclusions: Replacing smear microscopy with Xpert MTB/RIF in Brazil increased confirmation of pulmonary TB. An additional benefit was the accurate detection of rifampicin resistance. However, no increase on overall notification rates was observed, possibly because of high rates of empirical TB treatment.

Trial registration: ClinicalTrials.gov NCT01363765. Please see later in the article for the Editors' Summary.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1. Stepped-wedge design with 14 clusters…
Figure 1. Stepped-wedge design with 14 clusters (study laboratories with serviced clinics) and eight monthly measurement periods.
Figure 2. Flowchart showing study inclusion in…
Figure 2. Flowchart showing study inclusion in baseline (smear examination) and intervention (Xpert MTB/RIF) arms.
Bold arrows indicate cross-linkage between databases.
Figure 3. Sensitivity analysis for laboratory-confirmed TB…
Figure 3. Sensitivity analysis for laboratory-confirmed TB diagnoses.
Variation in unadjusted cluster-averaged notification rate ratio for laboratory-confirmed notifications, by proportion of missing notifications for laboratory-confirmed TB diagnoses that are due to failed linkage of records in the laboratory and notification databases.
Figure 4. Box-and-whisker plot of cluster-averaged time…
Figure 4. Box-and-whisker plot of cluster-averaged time interval between processing of sputum and start of first-line drug treatment in the baseline (smear examination) and intervention (Xpert MTB/RIF) arms.
Delays are shown for three groups: (1) all TB patients notified for whom a sputum test was performed, (2) TB patients notified with bacteriological confirmation, and (3) TB patients notified without bacteriological confirmation. Left: per-protocol analysis; right: ITT analysis.

References

    1. Raviglione M, Marais B, Floyd K, Lönnroth K, Getahun H, et al. (2012) Scaling up interventions to achieve global tuberculosis control: progress and new developments. Lancet 379: 1902–1913 10.1016/S0140-6736(12)60727-2
    1. Boehme CC, Nabeta P, Hillemann D, Nicol MP, Shenai S, et al. (2010) Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med 363: 1005–1015 10.1056/NEJMoa0907847
    1. Boehme CC, Nicol MP, Nabeta P, Michael JS, Gotuzzo E, 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 10.1016/S0140-6736(11)60438-8
    1. Theron G, Zijenah L, Chanda D, Clowes P, Rachow A, et al. (2014) 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 383: 424–435 10.1016/S0140-6736(13)62073-5
    1. Steingart KR, Schiller I, Horne DJ, Pai M, Boehme CC, et al. (2014) Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults. Cochrane Database Syst Rev 1: CD009593 10.1002/14651858.CD009593.pub3
    1. Choi HW, Miele K, Dowdy D, Shah M (2013) Cost-effectiveness of Xpert® MTB/RIF for diagnosing pulmonary tuberculosis in the United States. Int J Tuberc Lung Dis 17: 1328–1335 10.5588/ijtld.13.0095
    1. Menzies NA, Cohen T, Lin H-H, Murray M, Salomon JA (2012) Population health impact and cost-effectiveness of tuberculosis diagnosis with Xpert MTB/RIF: a dynamic simulation and economic evaluation. PLoS Med 9: e1001347 10.1371/journal.pmed.1001347
    1. Vassall A, van Kampen S, Sohn H, Michael JS, John KR, 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 10.1371/journal.pmed.1001120
    1. World Health Organization (2012) Tuberculosis diagnostics Xpert MTB/RIF test. WHO endorsement and recommendations. Available: . Accessed 9 November 2013.
    1. World Health Organization (2011) Automated real-time nucleic acid amplification technology for rapid and simultaneous detection of tuberculosis and rifampicin resistance: Xpert MTB/RIF assay for the diagnosis of pulmonary and extrapulmonary TB in adults and children. Available: . Accessed 13 November 2014.
    1. Small PM, Pai M (2010) Tuberculosis diagnosis—time for a game change. N Engl J Med 363: 1070–1071.
    1. Schunemann HJ, Oxman AD, Brozek J, Glasziou P, Jaeschke R, et al. (2008) Grading quality of evidence and strength of recommendations for diagnostic tests and strategies. BMJ 336: 1106–1110 10.1136/
    1. Cobelens F, van den Hof S, Pai M, Squire SB, Ramsay A, et al. (2012) Which new diagnostics for tuberculosis, and when? J Infect Dis 205 Suppl 2: S191–S198 10.1093/infdis/jis188
    1. Hanrahan CF, Selibas K, Deery CB, Dansey H, Clouse K, et al. (2013) Time to treatment and patient outcomes among TB suspects screened by a single point-of-care Xpert MTB/RIF at a primary care clinic in Johannesburg, South Africa. PLoS ONE 8: e65421 10.1371/journal.pone.0065421
    1. Yoon C, Cattamanchi A, Davis JL, Worodria W, den Boon S, et al. (2012) Impact of Xpert MTB/RIF testing on tuberculosis management and outcomes in hospitalized patients in Uganda. PLoS ONE 7: e48599 10.1371/journal.pone.0048599
    1. World Health Organization (2014) TB diagnostics and laboratory strengthening: WHO monitoring of Xpert MTB/RIF roll-out. Available: . Accessed 31 October 2014.
    1. Zwarenstein M, Treweek S, Gagnier JJ, Altman DG, Tunis S, et al. (2008) Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ 337: a2390.
    1. World Health Organization (2014) Global tuberculosis report 2014. Available: . Accessed 13 November 2014.
    1. Brasil Ministério da Saúde Secretaria de Vigilância Sanitária Programa Nacional de Controle da Tuberculose (2011) Manual de recomendações para o controle da tuberculose no Brasil. Available: . Accessed 13 November 2014.
    1. Brasil Ministério da Saúde Secretaria de Vigilância em Saúde Programa Nacional de Controle da Tuberculose (2013) Programa Nacional de Controle da Tuberculose. Available: . Accessed 31 March 2014.
    1. Portal da Saúde (2013). Sistema de Informação de Agravos de Notificação—SINAN. O que é o SINAN. Available: . Accessed 4 July 2013.
    1. Portal da Saúde (2013) DATASUS: Informações de Saúde—demográficas e socioeconômicas [database]. Available: . Accessed 8 July 2013.
    1. Cepheid (n.d.) The new GeneXpert® system. Available: . Accessed 13 November 2014.
    1. Cepheid (2009) Xpert®MTB/RIF: two-hour detection of MTB and resistance to rifampicin. Available: . Accessed 31 March 2014.
    1. Brown CA, Lilford RJ (2006) The stepped wedge trial design: a systematic review. BMC Med Res Methodol 6: 54 10.1186/1471-2288-6-54
    1. Hayes RJ, Moulton LH (2009) Cluster randomized trials. Boca Raton (Florida): Chapman & Hall/CRC.
    1. Moulton LH, Golub JE, Durovni B, Cavalcante SC, Pacheco AG, et al. (2007) Statistical design of THRio: a phased implementation clinic-randomized study of a tuberculosis preventive therapy intervention. Clin Trials 4: 190–199 10.1177/1740774507076937
    1. Camargo KR Jr, Coeli CM (2000) [Reclink: an application for database linkage implementing the probabilistic record linkage method.]. Cad Saude Publica 16: 439–447.
    1. Sistema de Informação de Tratamentos Especiais de Tuberculose (2014) SITETB. Available: . Accessed 13 November 2014.
    1. Instituto Brasileiro de Geografia e Estatística (2013) Estimativas da população: metodologia adotada nas estimativas populacionais municipais. Available: . Accessed 5 December 2013.
    1. Hussey MA, Hughes JP (2007) Design and analysis of stepped wedge cluster randomized trials. Contemp Clin Trials 28: 182–191 10.1016/j.cct.2006.05.007
    1. Fielding KL, McCarthy K, Cox H, Erasmus L, Ginindza S, et al.. (2014) Xpert as the first-line TB test in South Africa: yield, initial loss to follow-up, proportion treated [abstract]. 2014 Conference on Retroviruses and Opportunistic Infections; 3–6 March 2014; Boston, Massachusetts, US.
    1. Theron G, Peter J, Dowdy D, Langley I, Squire SB, et al. (2014) Do high rates of empirical treatment undermine the potential effect of new diagnostic tests for tuberculosis in high-burden settings? Lancet Infect Dis 14: 527–532.
    1. World Health Organization (2007) Improving the diagnosis and treatment of smear-negative pulmonary and extra-pulmonary tuberculosis among adults and adolescents: recommendations for HIV-prevalent and resource-constrained settings. Available: . Accessed 5 March 2014.
    1. Walusimbi S, Bwanga F, De Costa A, Haile M, Joloba M, et al. (2013) Meta-analysis to compare the accuracy of GeneXpert, MODS and the WHO 2007 algorithm for diagnosis of smear-negative pulmonary tuberculosis. BMC Infect Dis 13: 507.
    1. Selig L, Guedes R, Kritski A, Spector N, Lapa E, Silva JR, et al. (2009) Uses of tuberculosis mortality surveillance to identify programme errors and improve database reporting. Int J Tuberc Lung Dis 13: 982–988.
    1. Oliveira LM, PinheiroII RS (2011) Óbitos e internações por tuberculose não notificados no Município do Rio de Janeiro. Rev Saude Publica 45: 31–39.
    1. Harries AD, Rusen ID, Chiang C-Y, Hinderaker SG, Enarson DA (2009) Registering initial defaulters and reporting on their treatment outcomes. Int J Tuberc Lung Dis 13: 801–803.
    1. Rhoda DA, Murray DM, Andridge RR, Pennell ML, Hade EM (2011) Studies with staggered starts: multiple baseline designs and group-randomized trials. Am J Public Health 101: 2164–2169 10.2105/AJPH.2011.300264
    1. Theron G, Peter J, van Zyl-Smit R, Mishra H, Streicher E, 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 10.1164/rccm.201101-0056OC
    1. Foundation for Innovative New Diagnostics (2011) Performance of Xpert MTB/RIF version G4 assay. Geneva: Foundation for Innovative New Diagnostics. Available: . Accessed 2 February 2014.
    1. Osman M, Simpson JA, Caldwell J, Bosman M, Nicol MP (2014) GeneXpert MTB/RIF version G4 for identification of rifampin-resistant tuberculosis in a programmatic setting. J Clin Microbiol 52: 635–637 10.1128/JCM.02517-13
    1. Van Deun A, Aung KJM, Bola V, Lebeke R, Hossain MA, et al. (2013) Rifampin drug resistance tests for tuberculosis: challenging the gold standard. J Clin Microbiol 51: 2633–2640 10.1128/JCM.00553-13
    1. Rufai SB, Kumar P, Singh A, Prajapati S, Balooni V, et al. (2014) Comparison of Xpert MTB/RIF with line probe assay for detection of rifampin-monoresistant Mycobacterium tuberculosis. J Clin Microbiol 52: 1846–1852 10.1128/JCM.03005-13
    1. Kwak N, Choi SM, Lee J, Park YS, Lee C-H, et al. (2013) Diagnostic accuracy and turnaround time of the Xpert MTB/RIF assay in routine clinical practice. PLoS ONE 8: e77456 10.1371/journal.pone.0077456
    1. Durovni B, Saraceni V, Cordeirodo-Santos M, Cavalcante SC, Soares E, et al. (2014) Operational lessons drawn from pilot implementation of Xpert MTB/Rif in Brazil. Bull World Health Organ 92: 613–617.

Source: PubMed

3
Abonnieren