数据驱动的个性化抗生素给药在脓毒症或脓毒性休克重症患者中的成本效益

Cost-effectiveness of data driven personalised antibiotic dosing in critically ill patients with sepsis or septic shock.

作者信息

Broulikova Hana M, Wallage Jacqueline, Roggeveen Luca, Fleuren Lucas, Guo Tingjie, Elbers Paul W G, Bosmans Judith E

机构信息

Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health research institute, Van der Boechorststraat 7, Amsterdam, 1081 BT, the Netherlands.

Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Cardiovascular Science, Amsterdam Institute for Infection and Immunity, Amsterdam Medical Data Science, Amsterdam Public Health, Amsterdam UMC, Vrije Universiteit, De Boelelaan 1117, Amsterdam, 1081 HV, the Netherlands.

出版信息

J Clin Monit Comput. 2025 Jan 24. doi: 10.1007/s10877-024-01257-9.

DOI:10.1007/s10877-024-01257-9

PMID:39853643

Abstract

PURPOSE

This study provides an economic evaluation of bedside, data-driven, and model-informed precision dosing of antibiotics in comparison with usual care among critically ill patients with sepsis or septic shock.

METHODS

This economic evaluation was conducted alongside an AutoKinetics randomized controlled trial. Effect measures included quality-adjusted life years (QALYs), mortality and pharmacokinetic target attainment. Costs were measured from a societal perspective. Missing data was multiply imputed, and bootstrapping was used to estimate statistical uncertainty. Differences in effects and costs were estimated using bivariate regression and used to calculate incremental cost-effectiveness ratios.

RESULTS

Patients in the intervention group had higher costs (€42,684 vs. 39,475), lower mortality (42% vs. 49%), more QALYs (0.184 vs. 0.153), and higher pharmacokinetic target attainment (69% vs. 48%). Only the difference for target attainment was found statistically significant. An additional €18,129, €55,576, and €123,493 needs to be invested to attain the targeted plasma levels for one more patient, to save one life and gain one QALY, respectively. The probability of cost-effectiveness for all effect outcomes is below 60% for most acceptable willingness-to-pay thresholds.

CONCLUSIONS

Data-driven personalised antibiotic dosing in critically ill patients as implemented in the AutoKinetics trial cannot be recommended for implementation as a cost-effective intervention.

TRIAL REGISTRATION

The trial was prospectively registered at Netherlands Trial Register (NTR), NL6501/NTR6689 on 25 August 2017 and at the European Clinical Trials Database (EudraCT), 2017-002478-37 on 6 November 2017.

摘要

目的

本研究对脓毒症或脓毒性休克重症患者床边数据驱动及模型指导的抗生素精准给药与常规治疗进行了经济学评估。

方法

本经济学评估与一项自动动力学随机对照试验同时进行。效果指标包括质量调整生命年（QALYs）、死亡率和药代动力学目标达成率。成本从社会角度进行衡量。对缺失数据进行多重填补，并采用自抽样法估计统计不确定性。使用双变量回归估计效果和成本差异，并用于计算增量成本效益比。

结果

干预组患者成本更高（42,684欧元对39,475欧元），死亡率更低（42%对49%），QALYs更多（0.184对0.153），药代动力学目标达成率更高（69%对48%）。仅目标达成率的差异具有统计学意义。分别需要额外投入18,129欧元、55,576欧元和123,493欧元，才能使多一名患者达到目标血浆水平、挽救一条生命并获得一个QALY。对于大多数可接受的支付意愿阈值，所有效果结果的成本效益概率均低于60%。