从抗菌药物监测数据预测淋病奈瑟菌的抗菌药物耐药性发展:一项数学建模研究。
Projecting the development of antimicrobial resistance in Neisseria gonorrhoeae from antimicrobial surveillance data: a mathematical modelling study.
机构信息
Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
UK Health Security Agency, London, UK.
出版信息
BMC Infect Dis. 2023 Apr 20;23(1):252. doi: 10.1186/s12879-023-08200-4.
BACKGROUND
The World Health Organization recommends changing the first-line antimicrobial treatment for gonorrhoea when ≥ 5% of Neisseria gonorrhoeae cases fail treatment or are resistant. Susceptibility to ceftriaxone, the last remaining treatment option has been decreasing in many countries. We used antimicrobial resistance surveillance data and developed mathematical models to project the time to reach the 5% threshold for resistance to first-line antimicrobials used for N. gonorrhoeae.
METHODS
We used data from the Gonococcal Resistance to Antimicrobials Surveillance Programme (GRASP) in England and Wales from 2000-2018 about minimum inhibitory concentrations (MIC) for ciprofloxacin, azithromycin, cefixime and ceftriaxone and antimicrobial treatment in two groups, heterosexual men and women (HMW) and men who have sex with men (MSM). We developed two susceptible-infected-susceptible models to fit these data and produce projections of the proportion of resistance until 2030. The single-step model represents the situation in which a single mutation results in antimicrobial resistance. In the multi-step model, the sequential accumulation of resistance mutations is reflected by changes in the MIC distribution.
RESULTS
The single-step model described resistance to ciprofloxacin well. Both single-step and multi-step models could describe azithromycin and cefixime resistance, with projected resistance levels higher with the multi-step than the single step model. For ceftriaxone, with very few observed cases of full resistance, the multi-step model was needed to describe long-term dynamics of resistance. Extrapolating from the observed upward drift in MIC values, the multi-step model projected ≥ 5% resistance to ceftriaxone could be reached by 2030, based on treatment pressure alone. Ceftriaxone resistance was projected to rise to 13.2% (95% credible interval [CrI]: 0.7-44.8%) among HMW and 19.6% (95%CrI: 2.6-54.4%) among MSM by 2030.
CONCLUSIONS
New first-line antimicrobials for gonorrhoea treatment are needed. In the meantime, public health authorities should strengthen surveillance for AMR in N. gonorrhoeae and implement strategies for continued antimicrobial stewardship. Our models show the utility of long-term representative surveillance of gonococcal antimicrobial susceptibility data and can be adapted for use in, and for comparison with, other countries.
背景
世界卫生组织建议,当淋病奈瑟菌的治疗失败或耐药率≥5%时,应更换一线抗菌治疗药物。许多国家的头孢曲松的敏感性(作为最后一种治疗选择)一直在下降。我们使用抗菌药物耐药性监测数据和建立数学模型来预测达到淋病奈瑟菌一线抗菌药物耐药性 5%阈值的时间。
方法
我们使用了 2000-2018 年英格兰和威尔士的淋病奈瑟菌耐药性监测计划(GRASP)的数据,包括最低抑菌浓度(MIC)值,涉及环丙沙星、阿奇霉素、头孢克肟和头孢曲松,以及两组人群(异性恋男性和女性(HMW)和男男性接触者(MSM))的抗菌治疗情况。我们开发了两个易感-感染-易感模型来拟合这些数据,并预测到 2030 年的耐药比例。单步模型代表了单个突变导致抗菌药物耐药性的情况。在多步模型中,MIC 分布的变化反映了耐药突变的顺序积累。
结果
单步模型很好地描述了对环丙沙星的耐药性。单步和多步模型都可以描述阿奇霉素和头孢克肟的耐药性,多步模型的预测耐药水平高于单步模型。对于头孢曲松,由于观察到的完全耐药病例很少,因此需要多步模型来描述耐药的长期动态。根据治疗压力,从观察到的 MIC 值上升趋势推断,到 2030 年,仅基于治疗压力,就可能达到头孢曲松的耐药性≥5%的阈值。到 2030 年,预计 HMW 人群中头孢曲松耐药率将上升至 13.2%(95%可信区间[CrI]:0.7-44.8%),MSM 人群中上升至 19.6%(95%CrI:2.6-54.4%)。
结论
需要新的淋病一线抗菌治疗药物。与此同时,公共卫生当局应加强淋病奈瑟菌的 AMR 监测,并实施继续进行抗菌药物管理的策略。我们的模型表明,对淋病奈瑟菌抗菌药物敏感性的长期代表性监测数据具有实用性,并可用于其他国家/地区,或用于与其他国家/地区进行比较。