title: Systematic review, meta-analysis and economic modelling of molecular diagnostic tests for antibiotic resistance in tuberculosis.
abstract: BACKGROUND
  Drug-resistant tuberculosis (TB), especially multidrug-resistant (MDR, resistance to rifampicin and isoniazid) disease, is associated with a worse patient outcome. Drug resistance diagnosed using microbiological culture takes days to weeks, as TB bacteria grow slowly. Rapid molecular tests for drug resistance detection (1 day) are commercially available and may promote faster initiation of appropriate treatment.
  
  
  OBJECTIVE
  To (1) conduct a systematic review of evidence regarding diagnostic accuracy of molecular genetic tests for drug resistance, (2) conduct a health-economic evaluation of screening and diagnostic strategies, including comparison of alternative models of service provision and assessment of the value of targeting rapid testing at high-risk subgroups, and (3) construct a transmission-dynamic mathematical model that translates the estimates of diagnostic accuracy into estimates of clinical impact.
  
  
  METHODS
  A standardised search strategy identified relevant studies from EMBASE, PubMed, MEDLINE, Bioscience Information Service (BIOSIS), System for Information on Grey Literature in Europe Social Policy & Practice (SIGLE) and Web of Science, published between 1 January 2000 and 15 August 2013. Additional 'grey' sources were included. Quality was assessed using quality assessment of diagnostic accuracy studies version 2 (QUADAS-2). For each diagnostic strategy and population subgroup, a care pathway was constructed to specify which medical treatments and health services that individuals would receive from presentation to the point where they either did or did not complete TB treatment successfully. A total cost was estimated from a health service perspective for each care pathway, and the health impact was estimated in terms of the mean discounted quality-adjusted life-years (QALYs) lost as a result of disease and treatment. Costs and QALYs were both discounted at 3.5% per year. An integrated transmission-dynamic and economic model was used to evaluate the cost-effectiveness of introducing rapid molecular testing (in addition to culture and drug sensitivity testing). Probabilistic sensitivity analysis was performed to evaluate the impact on cost-effectiveness of diagnostic and treatment time delays, diagnosis and treatment costs, and associated QALYs.
  
  
  RESULTS
  A total of 8922 titles and abstracts were identified, with 557 papers being potentially eligible. Of these, 56 studies contained sufficient test information for analysis. All three commercial tests performed well when detecting drug resistance in clinical samples, although with evidence of heterogeneity between studies. Pooled sensitivity for GenoType® MTBDRplus (Hain Lifescience, Nehren, Germany) (isoniazid and rifampicin resistance), INNO-LiPA Rif.TB® (Fujirebio Europe, Ghent, Belgium) (rifampicin resistance) and Xpert® MTB/RIF (Cepheid Inc., Sunnyvale, CA, USA) (rifampicin resistance) was 83.4%, 94.6%, 95.4% and 96.8%, respectively; equivalent pooled specificity was 99.6%, 98.2%, 99.7% and 98.4%, respectively. Results of the transmission model suggest that all of the rapid assays considered here, if added to the current diagnostic pathway, would be cost-saving and achieve a reduction in expected QALY loss compared with current practice. GenoType MTBDRplus appeared to be the most cost-effective of the rapid tests in the South Asian population, although results were similar for GeneXpert. In all other scenarios GeneXpert appeared to be the most cost-effective strategy.
  
  
  CONCLUSIONS
  Rapid molecular tests for rifampicin and isoniazid resistance were sensitive and specific. They may also be cost-effective when added to culture drug susceptibility testing in the UK. There is global interest in point-of-care testing and further work is needed to review the performance of emerging tests and the wider health-economic impact of decentralised testing in clinics and primary care, as well as non-health-care settings, such as shelters and prisons.
  
  
  BACKGROUND
  This study is registered as PROSPERO CRD42011001537.
  
  
  BACKGROUND
  The National Institute for Health Research Health Technology Assessment programme.
authors.affiliation: Public Health England National Mycobacterium Reference Laboratory, London, UK.
authors.forename: Francis
authors.initials: F
authors.lastname: Drobniewski
authors.affiliation: Centre for Infectious Disease Epidemiology, Research Department of Infection and Population Health, University College London, London, UK.
authors.forename: Mary
authors.initials: M
authors.lastname: Cooke
authors.affiliation: Health Economics Research Group, Brunel University, Uxbridge, UK.
authors.forename: Jake
authors.initials: J
authors.lastname: Jordan
authors.affiliation: Department of Infectious Diseases and Immunity, Imperial College London, London, UK.
authors.forename: Nicola
authors.initials: N
authors.lastname: Casali
authors.affiliation: Modelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
authors.forename: Tendai
authors.initials: T
authors.lastname: Mugwagwa
authors.affiliation: Department of Infectious Diseases and Immunity, Imperial College London, London, UK.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Broda
authors.affiliation: Imperial College London, London, UK.
authors.forename: Catherine
authors.initials: C
authors.lastname: Townsend
authors.affiliation: Department of Microbiology, Barts Health NHS Trust, London, UK.
authors.forename: Anand
authors.initials: A
authors.lastname: Sivaramakrishnan
authors.affiliation: Modelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
authors.forename: Nathan
authors.initials: N
authors.lastname: Green
authors.affiliation: Modelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
authors.forename: Mark
authors.initials: M
authors.lastname: Jit
authors.affiliation: Division of Medicine, University College London, London, UK.
authors.forename: Marc
authors.initials: M
authors.lastname: Lipman
authors.affiliation: Health Economics Research Group, Brunel University, Uxbridge, UK.
authors.forename: Joanne
authors.initials: J
authors.lastname: Lord
authors.affiliation: Modelling and Economics Unit, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: White
authors.affiliation: Centre for Infectious Disease Epidemiology, Research Department of Infection and Population Health, University College London, London, UK.
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Abubakar
mesh_terms: D000995:Antitubercular Agents / Q000494:pharmacology; D001431:Bacteriological Techniques; D003362:Cost-Benefit Analysis; D004352:Drug Resistance, Microbial; D006801:Humans; D007538:Isoniazid / Q000494:pharmacology; D017059:Models, Econometric; D021141:Nucleic Acid Amplification Techniques / Q000191:economics*; D010342:Patient Acceptance of Health Care; D019057:Quality-Adjusted Life Years; D012293:Rifampin / Q000494:pharmacology; D017421:Sequence Analysis; D013222:State Medicine; D013673:Technology Assessment, Biomedical; D013997:Time Factors; D018088:Tuberculosis, Multidrug-Resistant / Q000175:diagnosis* / Q000635:transmission; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis* / Q000635:transmission; D006113:United Kingdom
chemical_list: D000995:Antitubercular Agents; D007538:Isoniazid; D012293:Rifampin