Dynamic characteristics of drug resistant tuberculosis in Leiyang, Hunan, 2013–2017
-
摘要:
目的分析2013 — 2017年湖南省耒阳市结核分枝杆菌的耐药性动态变化趋势,了解该地区流行结核分枝杆菌耐药谱特征,为结核病的化疗方案制定和防控提供科学参考依据。 方法回顾性分析2013 — 2017年耒阳市收集的国家耐药监测菌株,经基质辅助激光解析电离飞行时间质谱(MALDI-TOF-MS)鉴定为结核分枝杆菌的菌株采用微孔板法测定8种常用一线二线抗结核药的最小抑菌浓度,采用统计描述和趋势χ2检验分析其耐药特征变化。 结果本研究共纳入568株结核分枝杆菌临床分离株,其中105(18.49%)株来自复治结核病患者,463(81.51%)株来自初治结核病患者。 总耐药率为22.13%(120/568),总耐多药率为6.34%(36/568),广泛耐药结核率为0.35%(2/568)。 耐药趋势分析结果显示,仅对氟喹诺酮类药物的耐药率呈逐年升高趋势(趋势χ2=8.585,P=0.003),对其他药物的耐药率、总耐药率、耐多药率等变化不大,差异无统计学意义。 结论湖南省耒阳市结核病耐药情况较严重,氟喹诺酮类耐药率在5年间呈逐年上升趋势,提示需要提高警觉,加强氟喹诺酮类药物的规范化使用;在耐药结核病患者治疗中需充分考虑其交叉耐药情况,同时加强该地区耐多药结核病患者的管理以减少原发性耐药结核病的产生。 Abstract:ObjectiveTo analyze the dynamic trend of drug resistance of Mycobacterium tuberculosis in Leiyang city, Hunan province from 2013 to 2017, and to understand the local drug resistance spectrum of M. tuberculosis, so as to provide evidences for the formulation of chemotherapy regimen of tuberculosis (TB) and TB prevention and control. MethodsThe strains of M. tuberculosis collected in Leiyang from 2013 to 2017 were analyzed retrospectively. After identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), all the M. tuberculosis strains were subjected to susceptibility tests of 8 first and second line anti-TB drugs by using microtiter plate method to understand the minimum inhibitory concentration. Statistical description and Chi-square for trend test were used to analyze the drug resistance trend. ResultsA total of 568 clinical strains of M. tuberculosis were included in this study, of which 18.49% (105/568) were from retreated TB cases, and 81.51% (463/568) form new TB cases. Overall, the drug resistance rate was 22.13% (120/568), the multi-drug resistance rate was 6.34% (36/568) and the extensively drug resistance rate was 0.35% (2/568). Drug resistance trend analysis showed that only the resistance rate to fluoroquinolones increased year by year (trend χ2=8.585, P=0.003), while the fluctuations of the drug resistance rate to other drugs, overall drug resistance rate and multi-drug resistance rate were not obvious, the differences were not statistically significant. ConclusionOverall, the drug resistance of tuberculosis in Leiyang was serious, the resistance rate to fluoroquinolones showed an increasing trend, and close attention should be paid on that. The standardized use of fluoroquinolones should be strengthened. Cross-drug resistance should be fully considered in the treatment of patients with drug resistant TB. In addition, the management of MDR-TB patients should be strengthened to reduce the incidence of primary drug resistant TB. -
Key words:
- Tuberculosis /
- Mycobacterium tuberculosis /
- Drug resistance /
- Drug susceptibility /
- Trend
-
图 2 568株结核分枝杆菌的耐药相关矩阵
注:方格里数值表示相关系数,取值范围为[−1,1],正值表示正相关,负值表示负相关,绝对值大小指示相关性强弱,绝对值越大,两变量的相关性越强,0.8~1为极强相关,0.6~0.8为强相关,0.4~0.6为中度相关,0.2~0.4为弱相关,0~0.2为极弱相关或无关,经检验表格里的相关系数均有统计学意义(P<0.05);INH. 异烟肼;RIF. 利福平;EMB. 乙胺丁醇;SM. 链霉素;OFL. 氧氟沙星;MXF. 莫西沙星;AMI. 阿米卡星;KAN. 卡那霉素
Figure 2. Correlation matrix of drug resistances of 568 M. tuberculosis strains
表 1 药物浓度范围和临界浓度值
Table 1. Concentration range and critical concentration of drugs
药物 浓度范围(μg/ml) 临界浓度(μg/ml) 异烟肼 0.03~4.00 0.20 利福平 0.12~16.00 1.00 乙胺丁醇 0.50~32.00 5.00 链霉素 0.25~32.00 2.00 氧氟沙星 0.25~32.00 2.00 莫西沙星 0.06~8.00 0.50 阿米卡星 0.12~16.00 4.00 卡那霉素 0.60~40.00 5.00 表 2 568例结核病患者的基本人口学信息
Table 2. Demographic information of 568 patients with tuberculosis
分组 病例数(例) 构成比(%) 性别 男性 450 79.23 女性 118 20.77 年龄组(岁) 0~ 82 14.44 30~ 100 17.60 45~ 210 36.97 60~ 176 30.99 居住地 农村 442 77.82 城镇 126 22.18 职业 农民 460 80.99 其他 108 19.01 文化程度 文盲或半文盲 102 17.96 小学或初中 401 70.60 高中及以上 65 11.44 初复治分类 复治 105 18.49 初治 463 81.51 表 3 568株结核分枝杆菌对一线抗结核药耐药情况
Table 3. Drug resistances of 568 M. tuberculosis strains to first-line anti-TB drugs
耐药类型 初治患者分离株(n=463) 复治患者分离株(n=105) 合计(n=568) χ2值 P值 菌株数(株) 耐药率(%) 菌株数(株) 耐药率(%) 菌株数(株) 耐药率(%) 任意耐药 68 14.69 34 32.38 102 17.96 18.188 <0.001 INH 53 11.45 23 21.90 76 13.38 8.076 0.004 RIF 26 5.62 22 20.95 48 8.45 26.022 <0.001 EMB 13 2.81 6 5.71 19 3.35 1.428 0.232 SM 36 7.78 16 15.24 52 9.15 5.731 0.017 单耐药 37 7.99 15 14.29 52 9.15 4.077 0.043 INH 22 4.75 8 7.62 30 5.28 1.407 0.236 RIF 4 0.86 4 3.81 8 1.41 3.437 0.064 EMB 0 0.00 0 0.00 0 0.00 − − SM 11 2.38 3 2.86 14 2.46 <0.001 >0.999 耐多药 22 4.75 14 13.33 36 6.34 10.618 0.001 INH+RIF 4 0.86 5 4.76 9 1.58 6.027 0.014 INH+RIF+EMB 2 0.43 1 0.95 3 0.53 − 0.459a INH+RIF+SM 6 1.30 4 3.81 10 1.76 1.842 0.175 INH+RIF+EMB+SM 10 2.16 4 3.81 14 2.46 0.404 0.525 多耐药 9 1.94 5 4.76 14 2.46 1.777 0.183 INH+SM 8 1.73 1 0.95 9 1.58 0.020 0.887 RIF+SM 0 0.00 3 2.86 3 0.53 − 0.006a INH+EMB+SM 1 0.22 0 0.00 1 0.18 − >0.999a RIF+EMB+SM 0 0.00 1 0.95 1 0.18 − 0.185a 注:INH. 异烟肼;RIF. 利福平;EMB. 乙胺丁醇;SM. 链霉素;a. 由Fisher确切概率法计算;−. 无法计算;任意耐药指经体外药敏试验证实结核分枝杆菌对指定的抗结核药物耐药,而不考虑对其他药物是否耐药 表 4 568株结核分枝杆菌对二线抗结核药耐药情况
Table 4. Drug resistances of 568 M. tuberculosis strains to second-line anti-TB drugs
耐药类型 初治患者分离株(n=463) 复治患者分离株(n=105) 合计(n=568) χ2值 P值 菌株数(株) 耐药率(%) 菌株数(株) 耐药率(%) 菌株数(株) 耐药率(%) 任意耐药 31 6.70 8 7.62 39 6.87 0.114 0.735 OFL 22 4.75 7 6.67 29 5.11 0.648 0.421 MXF 27 5.83 8 7.62 35 6.16 0.473 0.492 KAN 7 1.51 0 0.00 7 1.23 − 0.359a AMI 6 1.30 0 0.00 6 1.06 − 0.599a 单药耐药 6 1.30 1 0.95 7 1.23 <0.001 >0.999 OFL 0 0.00 0 0.00 0 0.00 − − MXF 5 1.08 1 0.95 6 1.06 − >0.999a KAN 1 0.22 0 0.00 1 0.18 − >0.999a AMI 0 0.00 0 0.00 0 0.00 − − 多药耐药 25 5.40 7 6.67 32 5.63 0.258 0.611 OFL+MXF 19 4.10 7 6.67 26 4.58 0.767 0.381 KAN+AMI 3 0.65 0 0.00 3 0.53 − >0.999a OFL+MXF+KAN+AMI 3 0.65 0 0.00 3 0.53 − >0.999a Pre-XDR-TB 7 1.51 4 3.81 11 1.94 1.323 0.250 XDR-TB 2 0.43 0 0.00 2 0.35 − >0.999a 注:OFL.氧氟沙星;MXF.莫西沙星;KAN.卡那霉素;AMI.阿米卡星;a.由Fisher确切概率法算得P值;−.无法计算;任意耐药指经体外药敏试验证实结核分枝杆菌对指定的抗结核药物耐药,而不考虑对其他药物是否耐药;Pre-XDR-TB.广泛耐药结核前期;XDR-TB.广泛耐药结核 表 5 2013-2017年湖南省耒阳市结核分枝杆菌的耐药趋势比较
Table 5. Drug resistance trend of M. tuberculosis in Leiyang from 2013 to 2017
耐药模式 2013年(n=165) 2014年(n=94) 2015年(n=140) 2016年(n=86) 2017年(n=83) 趋势χ2 P值 INH 19(11.52) 12(12.77) 23(16.43) 15(17.44) 7(8.43) 0.031 0.860 RIF 10(6.06) 12(12.77) 11(7.86) 7(8.14) 8(9.64) 0.353 0.552 EMB 4(2.42) 5(5.32) 2(1.43) 4(4.65) 4(4.82) 0.623 0.430 SM 12(7.27) 10(10.64) 11(7.86) 12(13.95) 7(8.43) 0.643 0.423 OFL 2(1.21) 3(3.19) 8(5.71) 9(10.47) 7(8.43) 11.299 0.001 MXF 5(3.03) 3(3.19) 9(6.43) 10(11.63) 8(9.64) 8.585 0.003 AMI 1(0.61) 1(1.06) 2(1.43) 2(2.33) 0(0.00) 0.057 0.811 KAN 1(0.61) 1(1.06) 3(2.14) 2(2.33) 0(0.00) 0.092 0.762 MDR-TB 7(4.24) 8(8.51) 9(6.43) 5(5.81) 7(8.43) 0.937 0.333 Pre-XDR-TB 2(1.21) 1(1.06) 2(1.43) 2(2.33) 4(4.82) 3.258 0.071 XDR-TB 0(0.00) 1(1.06) 0(0.00) 1(1.16) 0(0.00) 0.093 0.760 DR-TB 27(16.34) 16(17.02) 37(26.43) 25(29.07) 15(18.07) 2.436 0.119 注:括号外数据是菌株数,括号内数据是耐药率;INH. 异烟肼;RIF. 利福平;EMB. 乙胺丁醇;SM. 链霉素;OFL. 氧氟沙星;MXF. 莫西沙星;AMI. 阿米卡星;KAN. 卡那霉素;MDR-TB. 耐多药结核;Pre-XDR-TB. 广泛耐药结核前期;XDR-TB. 广泛耐药结核;DR-TB. 耐药结核 -
[1] Dheda K, Gumbo T, Maartens G, et al. The Lancet Respiratory Medicine Commission: 2019 update: epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant and incurable tuberculosis[J]. Lancet Respir Med, 2019,7(9):820–826. DOI: 10.1016/S2213−2600(19)30263−2. [2] Gandhi NR, Nunn P, Dheda K, et al. Multidrug-resistant and extensively drug-resistant tuberculosis: a threat to global control of tuberculosis[J]. Lancet, 2010,375(9728):1830–1843. DOI: 10.1016/S0140−6736(10)60410−2. [3] World Health Organization. Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis[M]. Geneva: World Health Organization, 2014. [4] 高谦, 梅建, 谭卫国. 实事求是抓住核心 脚踏实地精准防控[J]. 中国防痨杂志,2019,41(10):1074–1079. DOI: 10.3969/j.issn.1000−6621.2019.10.002.Gao Q, Mei J, Tan WG. Tuberculosis control strategy based on the discovery of infectious sources[J]. Chin J Antituberc, 2019,41(10):1074–1079. DOI: 10.3969/j.issn.1000−6621.2019.10.002. [5] 全国第五次结核病流行病学抽样调查技术指导组, 全国第五次结核病流行病学抽样调查办公室. 2010年全国第五次结核病流行病学抽样调查报告[J]. 中国防痨杂志,2012,34(8):485–508.Technical Guidance Group of the Fifth National TB Epidemiological Survey, Office of the Fifth National Tuberculosis Epidemiological Sampling Survey. The fifth national tuberculosis epidemiological survey in 2010[J]. Chin J Antituberc, 2012,34(8):485–508. [6] Glasauer S, Altmann D, Hauer B, et al. First-line tuberculosis drug resistance patterns and associated risk factors in Germany, 2008–2017[J]. PLoS One, 2019,14(6):e0217597. DOI: 10.1371/journal.pone.0217597. [7] 胡冬梅, 宋渝丹, 焦怡琳, 等. 结核病防治的精准之路[J]. 结核病与肺部健康杂志,2016,5(2):151–155. DOI: 10.3969/j.issn.2095−3755.2016.02.022.Hu DM, Song YD, Jiao YL, et al. The precision road of tuberculosis control and prevention[J]. J Tuberc Lung Health, 2016,5(2):151–155. DOI: 10.3969/j.issn.2095−3755.2016.02.022. [8] 赵雁林, 逄宇. 结核病实验室检验规程[M]. 北京: 人民卫生出版社, 2015: 30–35.Zhao YL, Pang Y. TB laboratory testing procedures[M]. Beijing: People's Medical Publishing House, 2015: 30–35. [9] Quinlan P, Phelan E, Doyle M. Matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) mass spectrometry (MS) for the identification of mycobacteria from MBBacT ALERT 3D liquid cultures and Lowenstein-Jensen (LJ) solid cultures[J]. J Clin Pathol, 2015,68(3):229–235. DOI: 10.1136/jclinpath−2014−202374. [10] CLSI. CLSI document M24-A2 (ISBN 1-56238-746-4) Susceptibility testing of mycobacteria, nocardiae, and other aerobic actinomycetes; approved standard—second edition[S]. Wayne, PA: Clinical and Laboratory Standards Institute, 2011. [11] 顾瑾, 张立群, 李亮, 等. WHO 2014年版《耐药结核病规划管理指南伙伴手册》解读之二(概念和定义)[J]. 中国防痨杂志,2015,37(4):411–412. DOI: 10.3969/j.issn.1000−6621.2015.04.019.Gu J, Zhang LQ, Li L, et al. Interpretation ii (concepts and definitions) of the WHO 2014 edition of the partnership handbook for programme management of drug-resistant tuberculosis[J]. Chin J Antituberc, 2015,37(4):411–412. DOI: 10.3969/j.issn.1000−6621.2015.04.019. [12] Jan F, Wali S, Sadia S, et al. Drug resistance pattern in Mycobacterium tuberculosis to the first line drugs of pulmonary tuberculosis patients at Hazara Region, Pakistan[J]. Tuberk Toraks, 2018,66(1):26–31. DOI: 10.5578/tt.60781. [13] 李静, 张阳奕, 武洁, 等. 2007-2012年上海市结核病耐药趋势分析[J]. 中国防痨杂志,2014,36(1):25–30. DOI: 10.3969/j.issn.1000−6621.2014.01.006.Li J, Zhang YY, Wu J, et al. Trends of drug-resistant tuberculosis in Shanghai from 2007 to 2012[J]. Chin J Antituberc, 2014,36(1):25–30. DOI: 10.3969/j.issn.1000−6621.2014.01.006. [14] Zhao YL, Xu SF, Wang LX, et al. National survey of drug-resistant tuberculosis in China[J]. N Engl J Med, 2012,366(23):2161–2170. DOI: 10.1056/NEJMoa1108789. [15] World Health Organization. Global tuberculosis report 2019[M]. Geneva: WHO, 2019. [16] Pang Y, Zong ZJ, Huo FM, et al. In Vitro drug susceptibility of bedaquiline, delamanid, linezolid, clofazimine, moxifloxacin, and gatifloxacin against extensively drug-resistant tuberculosis in Beijing, China[J]. Antimicrob Agents Chemother, 2017,61(10):e00900–17. DOI: 10.1128/AAC.00900−17. [17] Willby M, Sikes RD, Malik S, et al. Correlation between GyrA substitutions and ofloxacin, levofloxacin, and moxifloxacin cross-resistance in Mycobacterium tuberculosis[J]. Antimicrob Agents Chemother, 2015,59(9):5427–5434. DOI: 10.1128/AAC.00662−15. [18] Falzon D, Gandhi N, Migliori GB, et al. Resistance to fluoroquinolones and second-line injectable drugs: impact on multidrug-resistant TB outcomes[J]. Eur Respir J, 2013,42(1):156–168. DOI: 10.1183/09031936.00134712. [19] Canetti G, Fox W, Khomenko A, et al. Advances in techniques of testing mycobacterial drug sensitivity, and the use of sensitivity tests in tuberculosis control programmes[J]. Bull World Health Organ, 1969,41(1):21–43. [20] Akyar I, Çavuşoğlu C, Ayaş M, et al. Evaluation of the performance of MALDI-TOF MS and DNA sequence analysis in the identification of mycobacteria species[J]. Turk J Med Sci, 2018,48(6):1351–1357. DOI: 10.3906/sag−1801−198. [21] Costa-Alcalde JJ, Barbeito-Castineiras G, Gonzalez-Alba JM, et al. Comparative evaluation of the identification of rapidly growing non-tuberculous mycobacteria by mass spectrometry (MALDI-TOF MS), GenoType Mycobacterium CM/AS assay and partial sequencing of the rpoβ gene with phylogenetic analysis as a reference method[J]. Enferm Infecc Microbiol Clin, 2019,37(3):160–166. DOI: 10.1016/j.eimc.2018.04.012. [22] Colangeli R, Jedrey H, Kim S, et al. Bacterial factors that predict relapse after tuberculosis therapy[J]. N Engl J Med, 2018,379(9):823–833. DOI: 10.1056/NEJMoa1715849. [23] Forsman LD, Jonsson J, Wagrell C, et al. Minimum inhibitory concentrations of fluoroquinolones and pyrazinamide susceptibility correlate to clinical improvement in multidrug-resistant tuberculosis patients: a nationwide Swedish cohort study over 2 decades[J]. Clin Infect Dis, 2018,69(8):1394–1402. DOI: 10.1093/cid/ciy1068. -
2020-0052 2013—2017年湖南省耒阳市结核分枝杆菌耐药性特征的动态研究.docx
-