Center for Disease Dynamics, Economics and Policy, Washington, D.C., United States of America.
PLoS One. 2012;7(1):e29838. doi: 10.1371/journal.pone.0029838. Epub 2012 Jan 11.
Historically, antibiotic treatment guidelines have aimed to maximize treatment efficacy and minimize toxicity, but have not considered the evolution of antibiotic resistance. Optimizing the duration and dosing of treatment to minimize the duration of symptomatic infection and selection pressure for resistance simultaneously has the potential to extend the useful therapeutic life of these valuable life-saving drugs without compromising the interests of individual patients.Here, using mathematical models, we explore the theoretical basis for shorter durations of treatment courses, including a range of ecological dynamics of bacteria that cause infections or colonize hosts as commensals. We find that immunity is an important mediating factor in determining the need for long duration of treatment. When immunity to infection is expected, shorter durations that reduce the selection for resistance without interfering with successful clinical outcome are likely to be supported. Adjusting drug treatment strategies to account for the impact of the differences in the ecological niche occupied by commensal flora relative to invasive bacteria could be effective in delaying the spread of bacterial resistance.
从历史上看,抗生素治疗指南旨在最大限度地提高治疗效果并最大限度地降低毒性,但并未考虑抗生素耐药性的演变。优化治疗的持续时间和剂量,以同时最小化症状感染的持续时间和耐药性的选择压力,有可能在不损害个体患者利益的情况下延长这些宝贵的救命药物的治疗寿命。在这里,我们使用数学模型探讨了缩短治疗疗程的理论基础,包括引起感染或定植于宿主的共生细菌的一系列生态动力学。我们发现,免疫是决定需要长时间治疗的重要中介因素。当预计存在感染免疫时,减少耐药性选择而不干扰成功临床结果的较短疗程可能会得到支持。调整药物治疗策略以考虑共生菌群与侵袭性细菌所占据的生态位的差异的影响,可能有助于延缓细菌耐药性的传播。