BACKGROUND: The prevalence of latent tuberculosis infection (LTBI) is traditionally estimated using the tuberculin skin test (TST). Highly specific blood-based interferon-gamma release assays (IGRAs) are now available and could enhance the estimation of LTBI prevalence in combination with model-based methods. DESIGN: We compared conventional and model-based methods for estimating LTBI prevalence among 719 Indian health care workers who underwent both TST and QuantiFERON-TB Gold In-Tube (QFT-G). In addition to using standard cut-off points on TST and QFT-G, Bayesian mixture model analyses were performed with: 1) continuous TST data and 2) categorical data using both TST and QFT-G results in a latent class analysis (LCA), accounting for prior information on sensitivity and specificity. RESULTS: Estimates of LTBI prevalence varied from 33.8% to 60.7%, depending on the method used. The mixture model based on TST alone estimated the prevalence at 36.5% (95%CI 28.5-47.0). When results from both tests were combined using LCA, the prevalence was 45.4% (95%CI 39.5-51.1). The LCA provided additional results on the sensitivity, specificity and predictive values of joint results. CONCLUSION: The availability of novel, specific IGRAs and development of methods such as mixture analyses allow a more realistic and informative approach to prevalence estimation.
BACKGROUND: The prevalence of latent tuberculosis infection (LTBI) is traditionally estimated using the tuberculin skin test (TST). Highly specific blood-based interferon-gamma release assays (IGRAs) are now available and could enhance the estimation of LTBI prevalence in combination with model-based methods. DESIGN: We compared conventional and model-based methods for estimating LTBI prevalence among 719 Indian health care workers who underwent both TST and QuantiFERON-TB Gold In-Tube (QFT-G). In addition to using standard cut-off points on TST and QFT-G, Bayesian mixture model analyses were performed with: 1) continuous TST data and 2) categorical data using both TST and QFT-G results in a latent class analysis (LCA), accounting for prior information on sensitivity and specificity. RESULTS: Estimates of LTBI prevalence varied from 33.8% to 60.7%, depending on the method used. The mixture model based on TST alone estimated the prevalence at 36.5% (95%CI 28.5-47.0). When results from both tests were combined using LCA, the prevalence was 45.4% (95%CI 39.5-51.1). The LCA provided additional results on the sensitivity, specificity and predictive values of joint results. CONCLUSION: The availability of novel, specific IGRAs and development of methods such as mixture analyses allow a more realistic and informative approach to prevalence estimation.
Authors: Madhukar Pai; Kaustubh Gokhale; Rajnish Joshi; Sandeep Dogra; Shriprakash Kalantri; Deepak K Mendiratta; Pratibha Narang; Charles L Daley; Reuben M Granich; Gerald H Mazurek; Arthur L Reingold; Lee W Riley; John M Colford Journal: JAMA Date: 2005-06-08 Impact factor: 56.272
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Authors: Peter J Dodd; Kerry A Millington; Azra C Ghani; Junior Mutsvangwa; Anthony E Butterworth; Ajit Lalvani; Elizabeth L Corbett Journal: Am J Epidemiol Date: 2010-04-09 Impact factor: 4.897
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Authors: M Pai; R Joshi; S Dogra; A A Zwerling; D Gajalakshmi; K Goswami; M V R Reddy; A Kalantri; P C Hill; D Menzies; P C Hopewell Journal: Int J Tuberc Lung Dis Date: 2009-01 Impact factor: 2.373
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Authors: Alemnew F Dagnew; Jemal Hussein; Markos Abebe; Martha Zewdie; Adane Mihret; Ahmed Bedru; Menberework Chanyalew; Lawrence Yamuah; Girmay Medhin; Peter Bang; T Mark Doherty; Asrat Hailu; Abraham Aseffa Journal: BMC Res Notes Date: 2012-08-07