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2012 - 2017年刚果民主共和国东部冲突后地区经Xpert MTB/RIF检测出的利福平耐药结核病的患病率、预测因素及成功治疗结果:一项全省范围的回顾性队列研究

Prevalence, Predictors, and Successful Treatment Outcomes of Xpert MTB/RIF-identified Rifampicin-resistant Tuberculosis in Post-conflict Eastern Democratic Republic of the Congo, 2012-2017: A Retrospective Province-Wide Cohort Study.

作者信息

Bulabula André N H, Nelson Jenna A, Musafiri Eric M, Machekano Rhoderick, Sam-Agudu Nadia A, Diacon Andreas H, Shah Maunank, Creswell Jacob, Theron Grant, Warren Robin M, Jacobson Karen R, Chirambiza Jean-Paul, Kalumuna Dieudonné, Bisimwa Bertin C, Katoto Patrick D M C, Kaswa Michel K, Birembano Freddy M, Kitete Liliane, Grobusch Martin P, Kashongwe Zacharie M, Nachega Jean B

机构信息

Department of Global Health, Division of Health Systems and Public Health, Unit for Infection Prevention and Control, Faculty of Medicine and Health Sciences, Stellenbosch University.

Infection Control Africa Network, Cape Town, South Africa.

出版信息

Clin Infect Dis. 2019 Sep 27;69(8):1278-1287. doi: 10.1093/cid/ciy1105.

DOI:10.1093/cid/ciy1105
PMID:30759187
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6763636/
Abstract

BACKGROUND

Multidrug-resistant tuberculosis (MDR-TB) jeopardizes global TB control. The prevalence and predictors of Rifampicin-resistant (RR) TB, a proxy for MDR-TB, and the treatment outcomes with standard and shortened regimens have not been assessed in post-conflict regions, such as the South Kivu province in the eastern Democratic Republic of the Congo (DRC). We aimed to fill this knowledge gap and to inform the DRC National TB Program.

METHODS

of adults and children evaluated for pulmonary TB by sputum smear microscopy and Xpert MTB/RIF (Xpert) from February 2012 to June 2017. Multivariable logistic regression, Kaplan-Meier estimates, and multivariable Cox regression were used to assess independent predictors of RR-TB and treatment failure/death.

RESULTS

Of 1535 patients Xpert-positive for TB, 11% had RR-TB. Independent predictors of RR-TB were a positive sputum smear (adjusted odds ratio [aOR] 2.42, 95% confidence interval [CI] 1.63-3.59), retreatment of TB (aOR 4.92, 95% CI 2.31-10.45), and one or more prior TB episodes (aOR 1.77 per episode, 95% CI 1.01-3.10). Over 45% of RR-TB patients had no prior TB history or treatment. The median time from Xpert diagnosis to RR-TB treatment initiation was 12 days (interquartile range 3-60.2). Cures were achieved in 30/36 (83%) and 84/114 (74%) of patients on 9- vs 20/24-month MDR-TB regimens, respectively (P = .06). Predictors of treatment failure/death were the absence of directly observed therapy (DOT; adjusted hazard ratio [aHR] 2.77, 95% CI 1.2-6.66) and any serious adverse drug event (aHR 4.28, 95% CI 1.88-9.71).

CONCLUSIONS

Favorable RR-TB cure rates are achievable in this post-conflict setting with a high RR-TB prevalence. An expanded Xpert scale-up; the prompt initiation of shorter, safer, highly effective MDR-TB regimens; and treatment adherence support are critically needed to optimize outcomes.

摘要

背景

耐多药结核病(MDR-TB)危及全球结核病控制。在冲突后地区,如刚果民主共和国(DRC)东部的南基伍省,尚未评估利福平耐药(RR)结核病(MDR-TB的替代指标)的患病率、预测因素以及标准和缩短疗程的治疗结果。我们旨在填补这一知识空白,并为DRC国家结核病规划提供信息。

方法

纳入2012年2月至2017年6月通过痰涂片显微镜检查和Xpert MTB/RIF(Xpert)评估肺结核的成人和儿童。采用多变量逻辑回归、Kaplan-Meier估计和多变量Cox回归来评估RR-TB和治疗失败/死亡的独立预测因素。

结果

在1535例Xpert检测为结核阳性的患者中,11%患有RR-TB。RR-TB的独立预测因素为痰涂片阳性(调整优势比[aOR]2.42,95%置信区间[CI]1.63-3.59)、结核病再治疗(aOR 4.92,95%CI 2.31-10.45)以及一次或多次既往结核病史(每次发作aOR 1.77,95%CI 1.01-3.10)。超过45%的RR-TB患者无既往结核病史或治疗史。从Xpert诊断到开始RR-TB治疗的中位时间为为12天(四分位间距3-60.2)。接受9个月和20/24个月MDR-TB治疗方案的患者治愈率分别为30/36(83%)和84/114(74%)(P = 0.06)。治疗失败/死亡的预测因素为未进行直接观察治疗(DOT;调整风险比[aHR]2.77,95%CI 1.2-6.66)和任何严重药物不良事件(aHR 4.28,95%CI 1.88-9.71)。

结论

在这个RR-TB患病率高的冲突后环境中,可以实现良好的RR-TB治愈率。迫切需要扩大Xpert检测规模;迅速启动更短、更安全、高效的MDR-TB治疗方案;并提供治疗依从性支持以优化治疗结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/cfa018ec1db4/ciy1105f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/822653aff582/ciy1105f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/af95688c90b9/ciy1105f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/3c1d8173b17b/ciy1105f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/cfa018ec1db4/ciy1105f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/822653aff582/ciy1105f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/af95688c90b9/ciy1105f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/3c1d8173b17b/ciy1105f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f57/6763636/cfa018ec1db4/ciy1105f0004.jpg

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