Meta-narrative review of molecular methods for diagnosis and monitoring of multidrug-resistant tuberculosis treatment in adults

成人多重耐药结核病诊断和治疗监测的分子方法荟萃分析

阅读:1

Abstract

Early and accurate diagnosis and rigorous clinical and microbiological monitoring of multidrug-resistant tuberculosis (MDR-TB) treatment can curb morbidity and mortality. While others are still under evaluation, the World Health Organization has recommended few novel molecular methods for MDR-TB diagnosis only. We present current molecular methods for diagnosis and monitoring of MDR-TB treatment in TB-endemic settings. A systematic meta-narrative review was conducted according to the RAMESES recommendations. Electronic databases were searched for relevant articles published in English language from January 2013 to June 2018. Based on predefined criteria, two independent reviewers extracted the key messages from relevant articles. Disagreement between them was resolved through discussion and the involvement of a third reviewer, if needed. Key messages were synthesized to create the meta-narratives for method's accuracy, drug-susceptibility capability, and laboratory infrastructure required. We included 33 articles out of 1213 records retrieved, of which 16 (48%) and 12 (36%) were conducted in high- and low-TB-endemic settings, respectively. Xpert(®) MTB/RIF, GenoType MTBDRplus, GenoType MTBDRsl, FlouroType™ MTBDR, TB TaqMan(®) array card, and DNA sequencers can accurately guide effective treatment regimens. Molecular bacterial load assay quantifies mycobactericidal impact of these regimens. Although they present inherent advantages compared to the current standard of care, they carry important limitations to implementation and/or scale-up. Therefore, considerable effort must now be directed to implementation and health systems research to maximize these forecasted benefits for individual patient's health outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。