坦桑尼亚抗结核治疗药物监测临床决策支持系统(TuberXpert 项目):算法 "开发和实施协议。

IF 1.4 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Research Protocols Pub Date : 2024-10-21 DOI:10.2196/58720
Yann Thoma, Annie E Cathignol, Yuan J Pétermann, Margaretha L Sariko, Bibie Said, Chantal Csajka, Monia Guidi, Stellah G Mpagama
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引用次数: 0

摘要

背景:终结结核病(TB)战略需要一种新的病人治疗方法,而不是 "一刀切 "的模式。众所周知,每位患者的体质不同,导致药物排出速度各异。治疗药物监测(TDM)提供了一种管理药物剂量适应性的方法,但需要训练有素的药剂师,而在资源有限的环境中,药剂师非常稀缺:我们将开发一种自动临床决策支持系统(CDSS),帮助从业人员调整利福平的剂量,利福平是治疗结核病的基本药物之一,众所周知,其药代动力学变异较大,经常出现血药浓度不达标的情况。这种先进的系统将鼓励剂量个体化文化的传播,包括在非药理学专业的从业人员中传播。因此,本项目的目标是:(1) 为坦桑尼亚患者开发适用于利福平的群体药代动力学(popPK)模型;(2) 优化向从业人员报告相关信息的方式,以便调整药物剂量;(3) 根据药物浓度测量结果自动发送报告;(4) 在实地验证并实施最终系统:方法:共有 3 个团队将共同努力,提供首个结核病自动 TDM CDSS 系统。将开展一项横断面研究,以确定向临床医生显示信息的最佳方式。与此同时,还将利用已发表的文献、泛非抗结核抗生素评估联盟(panACEA)提供的现有文献数据以及在该项目中收集的样本,开发利福平 popPK 模型。将设计并实施一个决策树作为 CDSS,开发并通过选定的案例研究验证自动报告生成功能。专家药理学家将对 CDSS 进行验证,最后将在坦桑尼亚进行实地实施,并开展前瞻性研究,评估临床医生对 CDSS 建议的遵守情况:TuberXpert 项目于 2022 年 11 月启动。2024 年 7 月,在坦桑尼亚开展的临床研究完成,共招募了 50 名患者,收集了建立利福平 popPK 模型所需的数据,同时还开展了一项定性研究,确定了报告设计以及 CDSS 总体架构定义:在 TuberXpert 项目结束时,坦桑尼亚将拥有一个新工具,帮助从业人员调整针对复杂肺结核病例(肺结核或艾滋病毒、肺结核或糖尿病、肺结核或营养不良)的药物剂量。这一自动化系统将在实地得到验证和使用,并将推荐给受结核病流行影响的其他国家。此外,这种方法还将证明 CDSS 辅助 TDM 的可行性和适用性,以便在缺乏 TDM 专家的结核病重灾区进一步使用抗结核药物,包括被认为需要重点监测的二线治疗:DERR1-10.2196/58720。
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Toward a Clinical Decision Support System for Monitoring Therapeutic Antituberculosis Medical Drugs in Tanzania (Project TuberXpert): Protocol for an Algorithm' Development and Implementation.

Background: The end tuberculosis (TB) strategy requires a novel patient treatment approach contrary to the one-size-fits-all model. It is well known that each patient's physiology is different and leads to various rates of drug elimination. Therapeutic drug monitoring (TDM) offers a way to manage drug dosage adaptation but requires trained pharmacologists, which is scarce in resource-limited settings.

Objective: We will develop an automated clinical decision support system (CDSS) to help practitioners with the dosage adaptation of rifampicin, one of the essential medical drugs targeting TB, that is known for large pharmacokinetic variability and frequent suboptimal blood exposure. Such an advanced system will encourage the spread of a dosage-individualization culture, including among practitioners not specialized in pharmacology. Thus, the objectives of this project are to (1) develop the appropriate population pharmacokinetic (popPK) model for rifampicin for Tanzanian patients, (2) optimize the reporting of relevant information to practitioners for drug dosage adjustment, (3) automate the delivery of the report in line with the measurement of drug concentration, and (4) validate and implement the final system in the field.

Methods: A total of 3 teams will combine their efforts to deliver the first automated TDM CDSS for TB. A cross-sectional study will be conducted to define the best way to display information to clinicians. In parallel, a rifampicin popPK model will be developed taking advantage of the published literature, complemented with data provided by existing literature data from the Pan-African Consortium for the Evaluation of Antituberculosis Antibiotics (panACEA), and samples collected within this project. A decision tree will be designed and implemented as a CDSS, and an automated report generation will be developed and validated through selected case studies. Expert pharmacologists will validate the CDSS, and finally, field implementation in Tanzania will occur, coupled with a prospective study to assess clinicians' adherence to the CDSS recommendations.

Results: The TuberXpert project started in November 2022. In July 2024, the clinical study in Tanzania was completed with the enrollment of 50 patients to gather the required data to build a popPK model for rifampicin, together with a qualitative study defining the report design, as well as the CDSS general architecture definition.

Conclusions: At the end of the TuberXpert project, Tanzania will possess a new tool to help the practitioners with the adaptation of drug dosage targeting complicated TB cases (TB or HIV, TB or diabetes mellitus, and TB or malnutrition). This automated system will be validated and used in the field and will be proposed to other countries affected by endemic TB. In addition, this approach will serve as proof of concept regarding the feasibility and suitability of CDSS-assisted TDM for further anti-TB drugs in TB-burdened areas deprived of TDM experts, including second-line treatments considered important to monitor.

International registered report identifier (irrid): DERR1-10.2196/58720.

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