谭寿南, 郑志刚, 黄宝杨, 覃振华, 谭金雪, 韦吴迪, 梁冰玉, 廖艳研, 潘沛江, 蒋俊俊, 叶力, 梁浩. 2014-2019年广西壮族自治区柳州市耐药结核病趋势分析[J]. 疾病监测, 2021, 36(7): 714-718. DOI: 10.3784/jbjc.202009040311
引用本文: 谭寿南, 郑志刚, 黄宝杨, 覃振华, 谭金雪, 韦吴迪, 梁冰玉, 廖艳研, 潘沛江, 蒋俊俊, 叶力, 梁浩. 2014-2019年广西壮族自治区柳州市耐药结核病趋势分析[J]. 疾病监测, 2021, 36(7): 714-718. DOI: 10.3784/jbjc.202009040311
Tan Shounan, Zheng Zhigang, Huang Baoyang, Qin Zhenhua, Tan Jinxue, Wei Wudi, Liang Bingyu, Liao Yanyan, Pan Peijiang, Jiang Junjun, Ye Li, Liang Hao. Analysis on trend of drug resistance tuberculosis, Liuzhou, Guangxi[J]. Disease Surveillance, 2021, 36(7): 714-718. DOI: 10.3784/jbjc.202009040311
Citation: Tan Shounan, Zheng Zhigang, Huang Baoyang, Qin Zhenhua, Tan Jinxue, Wei Wudi, Liang Bingyu, Liao Yanyan, Pan Peijiang, Jiang Junjun, Ye Li, Liang Hao. Analysis on trend of drug resistance tuberculosis, Liuzhou, Guangxi[J]. Disease Surveillance, 2021, 36(7): 714-718. DOI: 10.3784/jbjc.202009040311

2014-2019年广西壮族自治区柳州市耐药结核病趋势分析

Analysis on trend of drug resistance tuberculosis, Liuzhou, Guangxi

  • 摘要:
      目的  了解广西壮族自治区柳州市耐药结核病(DR-TB)现状及随时间序列改变的发展趋势,为有效控制DR-TB传播提供依据。
      方法  利用中国耐药结核病监测网络数据库,计算年度耐药发病率变化百分比(APC),根据线性、二项式回归等构建回归模型,利用直线/曲线拟合方法对APC进行假设检验,了解DR-TB现状并评估发展趋势。
      结果  2014 — 2019年,柳州市监测发现571例DR-TB患者,占新报告TB病例的2.14%(571/26 691),DR-TB患者数由50例上升到189例,上升了2.60倍;单耐异烟肼(INH)结核病(IMR-TB)占DR-TB患者数的30.30%(173/571),占新登记TB患者比例从2014年0.37%上升到2019年1.15%;单耐利福平(RFP)结核病(RMR-TB)占19.26%(110/571),占新登记TB患者比例从2014年0.15%上升到2019年0.64%;耐多药(MDR)结核病(MDR-TB)占29.25%(167/571),占新登记TB患者比例从2014年0.55%上升到2019年0.72%;广泛耐药(XDR)结核病(XDR-TB)占7.01%(40/571),MDR-TB中XDR-TB比例为23.95%,占新登记TB患者比例从2014年0.15%上升到2019年0.17%。 APC检验结果显示,2016年后(二阶段)总DR-TB、IMR-TB和RMR-TB上升趋势有统计学意义(P值分别为0.031、0.018和0.043);尽管MDR-TB和XDR-TB患者随时间变化呈上升趋势,但无统计学意义。
      结论  柳州市总DR-TB、IMR-TB、RMR-TB上升趋势显著,MDR-TB和XDR-TB患者数量随时间变化呈上升趋势,但无统计学意义。 对于DR-TB所造成的公共卫生威胁,可通过连续监测结果,制定以证据为基础的应对措施。因此,应确保连续开展DR-TB监测,使其成为有效控制结核病和DR-TB传播的关键干预工具。

     

    Abstract:
      Objective  To understand the spread trend of drug resistant tuberculosis (DR TB) over time in Liuzhou City, Guangxi Zhuang Autonomous Region, and provide evidences to contain the spread and transmission of DR-TB.
      Methods  Data from the DR TB surveillance network in Liuzhou were analyzed. The percentage of DR-TB cases among the newly registered TB cases and the average annual percentage change (APC) were calculated. The regression model was constructed with linear and binomial regression. The hypothesis testing of the average APC was conducted by using line/curve fitting approach.
      Results  A total of 571 DR-TB cases were detected through the DR surveillance network in Liuzhou from 2014 to 2019, accounting for 2.14% (571/26691) of new registered TB cases. The number of DR-TB cases increased from 50 in 2014 to 189 in 2019, an increase of 2.60 times. Of those with drug resistant TB, 30.30% (173/571) were isoniazid resistant, 19.26% (110/571) were rifampin resistant, 29.25% (167/571) were multi-drug resistant (MDR), and 7.01% (40/571) were extensive drug resistant (XDR). In MDR TB cases, XDR TB cases accounted for 23.95%. From 2014 to 2019, the proportion of XDR-TB cases among newly registered TB cases increased from 0.15% to 0.17%. After 2016, the result of APC testing indicated that the total number of DR TB, isoniazid resistant TB cases and rifampin resistant TB were significant increased among new tuberculosis cases (P=0.031, P=0.018, P=0.043). Although the increasing trends of MDR TB and XDR TB cases were observed among new tuberculosis cases, the differences were not significant (PMDR TB=0.098, PXDR TB=0.484).
      Conclusion  The average APCs of DR TB, isoniazid resistant TB and rifampin resistant TB cases significantly increased in Liuzhou overtime, but the difference in case increase over time between MDR TB and XDR TB had no significance. It is necessary to conduct consecutive surveillance to facilitate the development of evidence based prevention and control measures for DR TB and improve the prevention and control of TB and the spread of DR TB.

     

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