Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?
Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?
复制标题
DOI：
10.1371/journal.pcbi.1004689
复制
发表时间：
2016-01
影响因子：
4.3
通讯作者：
Read AF
中科院分区：
文献类型：
--
作者：
Day T;Read AF
长期以来，高剂量化疗一直被认为是控制感染性疾病耐药性的一种手段，但最近的实证研究开始挑战这一观点。我们开发了一个非常通用的框架，从进化生物学的原则为基础的建模和理解阻力出现。我们使用这个框架来展示高剂量化疗如何产生相反的进化过程，涉及耐药菌株的突变输入和它们从生态竞争中的释放。因此，这种疗法是否是控制耐药性的最佳方法取决于这些过程的相对强度。这些相反的过程通常导致药物压力和耐药性出现之间的单峰关系。因此，最佳药物剂量位于临床可接受浓度的治疗窗的两端。我们用一个简单的模型来说明我们的研究结果，该模型显示了参数值中看似微小的变化如何改变结果，从高剂量化疗最佳的结果改变为使用最小临床有效剂量最佳的结果。对现有经验证据的审查为这些一般性结论提供了广泛的支持。我们的分析开辟了目前不被认为是耐药管理策略的治疗选择，它还简化了确定最能延缓患者耐药出现的药物剂量所需的实验。耐药性病原体的进化威胁着现代医学的大部分领域。一百多年来，人们一直建议“重拳出击”，相信高剂量的抗菌药物最能抑制耐药性的演变。我们认为，在进化论中没有任何东西支持这一点，认为这是在挑战医学的情况下的一个很好的经验法则。相反，我们表明，唯一的一般性是使用最高耐受药物剂量或最低临床有效剂量，即治疗窗口的两个边缘之一。这种方法提出了目前尚未考虑的治疗方案，并简化了确定最佳延缓耐药性演变的剂量所需的实验。
High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients. The evolution of antimicrobial resistant pathogens threatens much of modern medicine. For over one hundred years, the advice has been to ‘hit hard’, in the belief that high doses of antimicrobials best contain resistance evolution. We argue that nothing in evolutionary theory supports this as a good rule of thumb in the situations that challenge medicine. We show instead that the only generality is to either use the highest tolerable drug dose or the lowest clinically effective dose; that is, one of the two edges of the therapeutic window. This approach suggests treatment options not currently considered, and simplifies the experiments required to identify the dose that best retards resistance evolution.