Browsing by Author "Squire, S. Bertel"
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- ItemComparing tuberculosis diagnostic yield in smear/culture and xpert MTB/RIF-based algorithms using a non-randomised stepped-wedge design(Public Library of Science, 2016-03) Naidoo, Pren; Dunbar, Rory; Lombard, Carl; Du Toit, Elizabeth; Caldwell, Judy; Detjen, Anne; Squire, S. Bertel; Enarson, Donald A.; Beyers, NuldaSetting Primary health services in Cape Town, South Africa. Study Aim To compare tuberculosis (TB) diagnostic yield in an existing smear/culture-based and a newly introduced Xpert MTB/RIF-based algorithm. Methods TB diagnostic yield (the proportion of presumptive TB cases with a laboratory diagnosis of TB) was assessed using a non-randomised stepped-wedge design as sites transitioned to the Xpert based algorithm. We identified the full sequence of sputum tests recorded in the electronic laboratory database for presumptive TB cases from 60 primary health sites during seven one-month time-points, six months apart. Differences in TB yield and temporal trends were estimated using a binomial regression model. Results TB yield was 20.9% (95% CI 19.9% to 22.0%) in the smear/culture-based algorithm compared to 17.9% (95%CI 16.4% to 19.5%) in the Xpert based algorithm. There was a decline in TB yield over time with a mean risk difference of -0.9% (95% CI -1.2% to -0.6%) (p<0.001) per time-point. When estimates were adjusted for the temporal trend, TB yield was 19.1% (95% CI 17.6% to 20.5%) in the smear/culture-based algorithm compared to 19.3% (95% CI 17.7% to 20.9%) in the Xpert based algorithm with a risk difference of 0.3% (95% CI -1.8% to 2.3%) (p = 0.796). Culture tests were undertaken for 35.5% of smear-negative compared to 17.9% of Xpert negative low MDR-TB risk cases and for 82.6% of smear-negative compared to 40.5% of Xpert negative high MDR-TB risk cases in respective algorithms. Conclusion Introduction of an Xpert based algorithm did not produce the expected increase in TB diagnostic yield. Studies are required to assess whether improving adherence to the Xpert negative algorithm for HIV-infected individuals will increase yield. In light of the high cost of Xpert, a review of its role as a screening test for all presumptive TB cases may be warranted.
- ItemA comparison of multidrug-resistant tuberculosis treatment commencement times in MDRTBPlus line probe assay and XpertH MTB/RIF-based algorithms in a routine operational setting in Cape Town(PLoS, 2014-07-31) Naidoo, Pren; Du Toit, Elizabeth; Rory Dunbar, Rory; Lombard, Carl; Caldwell, Judy; Detjen, Anne; Squire, S. Bertel; Enarson, Donald A.; Beyers, NuldaBackground: Xpert MTB/RIF was introduced as a screening test for all presumptive tuberculosis cases in primary health services in Cape Town, South Africa. Study Aim: To compare multidrug-resistant tuberculosis (MDR-TB) treatment commencement times in MDRTBPlus Line Probe Assay and Xpert MTB/RIF-based algorithms in a routine operational setting. Methods: The study was undertaken in 10 of 29 high tuberculosis burden primary health facilities, selected through stratified random sampling. An observational study was undertaken as facilities transitioned to the Xpert MTB/RIF-based algorithm. MDR-TB diagnostic data were collected from electronic laboratory records and treatment data from clinical records and registers. Kaplan Meier time-to-event analysis was used to compare treatment commencement time, laboratory turnaround time and action delay between algorithms. A facility-level paired analysis was done: the median time-to-event was estimated per facility in each algorithm and mean differences between algorithms compared using a paired t-test. Cox proportional hazards regression was used to assess the effect of patient-level variables on treatment commencement time. The difference between algorithms was compared using the hazard ratio. Results: The median treatment commencement time in the Xpert MTB/RIF-based algorithm was 17 days (95% CI 13 to 22 days), with a median laboratory turnaround time (to result available in the laboratory) of <1 day (95% CI<1 to 1 day). There was a decrease of 25 days (95% CI 17 to 32 days, p<0.001) in median MDR-TB treatment commencement time in the Xpert MTB/RIF-based algorithm. We found no significant effect on treatment commencement times for the patient-level variables assessed. Conclusion: MDR-TB treatment commencement time was significantly reduced in the Xpert MTB/RIF-based algorithm. Changes in the health system may have contributed. However, an unacceptable level of delay remains. Health system and patient factors contributing to delay need to be evaluated and addressed to optimise test benefits.
- ItemTranslational research for tuberculosis elimination : priorities, challenges, and actions(Public Library of Science, 2016) Lienhardt, Christian; Lonnroth, Knut; Menzies, Dick; Balasegaram, Manica; Chakaya, Jeremiah; Cobelens, Frank; Cohn, Jennifer; Denkinger, Claudia M.; Evans, Thomas G.; Kallenius, Gunilla; Kaplan, Gilla; Kumar, Ajay M. V.; Matthiessen, Line; Mgone, Charles S.; Mizrahi, Valerie; Mukadi, Ya-diul; Nguyen, Viet Nhung; Nordstrom, Anders; Sizemore, Christine F.; Spigelman, Melvin; Squire, S. Bertel; Swaminathan, Soumya; Van Helden, Paul D.; Zumla, Alimuddin; Weyer, Karin; Weil, Diana; Raviglione, MarioSummary Points: • The WHO End TB Strategy, endorsed by the World Health Assembly in May 2014, has the ambitious goal of ending the global tuberculosis (TB) epidemic by 2035, with targets of a 95% decline in deaths due to TB (compared with 2015) and a 90% reduction in incidence of TB to ten cases/100,000 or less and no TB-affected household experiencing catastrophic costs due to TB. • Achieving this goal will only be possible through the development and rapid uptake of new tools, including rapid point-of-care diagnostics, safe and shorter treatment of latent TB infection and disease, and an efficacious TB vaccine, combined with efficient health systems and care provision, and actions on the social determinants of TB. • Research for TB elimination requires an intensification of efforts across a continuum from fundamental research to clinical, epidemiological, implementation, health system, and social science research. • Enhancing research along the full spectrum, from basic to implementation, and strengthening research capacity, particularly in low- and middle-income countries severely affected by the TB epidemics, is crucial for TB elimination. • The creation of a research-enabling environment that fosters and rewards high-quality research requires a broad-based, concerted effort by national governments and international donors to develop and promote TB research and research capacity at the country level and the effective engagement of all stakeholders.