Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design.
Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design.
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DOI：
10.1371/journal.pone.0150487
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Beyers N
中科院分区：
文献类型：
--
作者：
Naidoo P;Dunbar R;Lombard C;du Toit E;Caldwell J;Detjen A;Squire SB;Enarson DA;Beyers N
南非开普敦的初级卫生服务。比较现有的基于涂片/培养的算法和新推出的基于 Xpert® MTB/RIF 的算法的结核病 (TB) 诊断率。随着站点过渡到基于 Xpert® 的算法，使用非随机阶梯楔形设计评估结核病诊断率（实验室诊断为结核病的推定结核病病例的比例）。我们确定了电子实验室数据库中记录的 7 个一个月时间点（相隔六个月）内 60 个初级卫生机构疑似结核病病例的完整痰液检测序列。使用二项式回归模型估计结核病产量和时间趋势的差异。基于涂片/培养的算法的结核病检出率为 20.9%（95% CI 19.9% 至 22.0%），而基于 Xpert® 的算法为 17.9%（95% CI 16.4% 至 19.5%）。随着时间的推移，结核病发生率下降，每个时间点的平均风险差异为 -0.9%（95% CI -1.2% 至 -0.6%）（p<0.001）。当根据时间趋势调整估计值时，基于涂片/培养的算法中的结核病产率为 19.1%（95% CI 17.6% 至 20.5%），而基于 Xpert® 的算法中的结核病产率为 19.3%（95% CI 17.7% 至 20.9%），风险差异为 0.3%（95% CI -1.8% 至 2.3%）（p = 0.796）。在各自的算法中，对 35.5% 的涂片阴性病例进行了培养检测，而 Xpert® 阴性低耐多药结核风险病例的培养检测率为 17.9%，对 82.6% 的涂片阴性病例进行了培养检测，而 Xpert® 阴性高耐多药结核风险病例的培养检测率为 40.5%。引入基于 Xpert® 的算法并没有带来预期的结核病诊断率提高。需要进行研究来评估提高 HIV 感染者对 Xpert® 阴性算法的依从性是否会提高产量。鉴于 Xpert® 的高成本，可能有必要对其作为所有疑似结核病病例筛查测试的作用进行审查。
Primary health services in Cape Town, South Africa. To compare tuberculosis (TB) diagnostic yield in an existing smear/culture-based and a newly introduced Xpert® MTB/RIF-based algorithm. 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. 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. 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.