van der Maas Marloes E, Mantjes Gertjan, Steuten Lotte M G
1 PANAXEA B.V., Amsterdam, The Netherlands .
2 Fred Hutchinson Cancer Research Center, Hutchinson Institute for Cancer Outcomes Research , Seattle, Washington.
OMICS. 2017 Apr;21(4):232-243. doi: 10.1089/omi.2016.0186.
Antibiotics are often recommended as treatment for patients with chronic obstructive pulmonary disease (COPD) exacerbations. However, not all COPD exacerbations are caused by bacterial infections and there is consequently considerable misuse and overuse of antibiotics among patients with COPD. This poses a severe burden on healthcare resources such as increased risk of developing antibiotic resistance. The biomarker procalcitonin (PCT) displays specificity to distinguish bacterial inflammations from nonbacterial inflammations and may therefore help to rationalize antibiotic prescriptions. We report in this study, a three-country comparison of the health and economic consequences of a PCT biomarker-guided prescription and clinical decision-making strategy compared to current practice in hospitalized patients with COPD exacerbations. A decision tree was developed, comparing the expected costs and effects of the PCT algorithm to current practice in the Netherlands, Germany, and the United Kingdom. The time horizon of the model captured the length of hospital stay and a societal perspective was also adopted. The primary health outcome was the duration of antibiotic therapy. The incremental cost-effectiveness ratio was defined as the incremental costs per antibiotic day avoided. The incremental cost savings per day on antibiotic therapy avoided were (in Euros) €90 in the Netherlands, €125 in Germany, and €52 in the United Kingdom. Probabilistic sensitivity analyses showed that in the majority of simulations, the PCT biomarker strategy was superior to current practice (the Netherlands: 58%, Germany: 58%, and the United Kingdom: 57%). In conclusion, the PCT biomarker algorithm to optimize antibiotic prescriptions in COPD is likely to be cost-effective compared to current practice. Both the percentage of patients who start with antibiotic treatment as well as the duration of antibiotic therapy are reduced with the PCT decision algorithm, leading to a decrease in total costs per patient. Economic analysis based on real-life data is recommended for further research. Biomarker-driven prescription algorithms are important instruments for personalized medicine in COPD. This also attests to the emerging convergence of biomarker innovations and the broader field of Health Technology Assessment (HTA).
抗生素常被推荐用于治疗慢性阻塞性肺疾病(COPD)急性加重期的患者。然而,并非所有COPD急性加重都是由细菌感染引起的,因此COPD患者中存在大量抗生素的误用和滥用情况。这给医疗资源带来了沉重负担,比如增加了产生抗生素耐药性的风险。生物标志物降钙素原(PCT)具有区分细菌感染性炎症和非细菌感染性炎症的特异性,因此可能有助于合理开具抗生素处方。在本研究中,我们报告了一项三国比较,即与COPD急性加重期住院患者的当前治疗方法相比,PCT生物标志物指导的处方和临床决策策略对健康和经济的影响。我们构建了一个决策树,比较了PCT算法与荷兰、德国和英国当前治疗方法的预期成本和效果。该模型的时间范围涵盖了住院时间,并采用了社会视角。主要健康结局是抗生素治疗的持续时间。增量成本效益比定义为每避免一天使用抗生素所节省的增量成本。在荷兰,每避免一天使用抗生素治疗节省的增量成本为90欧元,德国为125欧元,英国为52欧元。概率敏感性分析表明,在大多数模拟中,PCT生物标志物策略优于当前治疗方法(荷兰:58%,德国:58%,英国:57%)。总之,与当前治疗方法相比,用于优化COPD抗生素处方的PCT生物标志物算法可能具有成本效益。采用PCT决策算法可降低开始使用抗生素治疗的患者比例以及抗生素治疗的持续时间,从而降低每位患者的总成本。建议基于实际数据进行经济分析以开展进一步研究。生物标志物驱动的处方算法是COPD个性化医疗的重要工具。这也证明了生物标志物创新与更广泛的卫生技术评估(HTA)领域正在出现融合。