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基于 22 基因转录组模型预测抗结核治疗持续时间。

Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model.

机构信息

Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany

German Center for Infection Research (DZIF), Germany.

出版信息

Eur Respir J. 2021 Sep 2;58(3). doi: 10.1183/13993003.03492-2020. Print 2021 Sep.

DOI:10.1183/13993003.03492-2020
PMID:33574078
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11967237/
Abstract

BACKGROUND

The World Health Organization recommends standardised treatment durations for patients with tuberculosis (TB). We identified and validated a host-RNA signature as a biomarker for individualised therapy durations for patients with drug-susceptible (DS)- and multidrug-resistant (MDR)-TB.

METHODS

Adult patients with pulmonary TB were prospectively enrolled into five independent cohorts in Germany and Romania. Clinical and microbiological data and whole blood for RNA transcriptomic analysis were collected at pre-defined time points throughout therapy. Treatment outcomes were ascertained by TBnet criteria (6-month culture status/1-year follow-up). A whole-blood RNA therapy-end model was developed in a multistep process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment time points.

RESULTS

50 patients with DS-TB and 30 patients with MDR-TB were recruited in the German identification cohorts (DS-GIC and MDR-GIC, respectively); 28 patients with DS-TB and 32 patients with MDR-TB in the German validation cohorts (DS-GVC and MDR-GVC, respectively); and 52 patients with MDR-TB in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model (TB22) that defined cure-associated end-of-therapy time points was derived from the DS- and MDR-GIC data. The TB22 model was superior to other published signatures to accurately predict clinical outcomes for patients in the DS-GVC (area under the curve 0.94, 95% CI 0.9-0.98) and suggests that cure may be achieved with shorter treatment durations for TB patients in the MDR-GIC (mean reduction 218.0 days, 34.2%; p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%; p<0.001) and the MDR-RVC (mean reduction of 161.0 days, 23.4%; p=0.001).

CONCLUSION

Biomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-TB.

摘要

背景

世界卫生组织建议为结核病(TB)患者制定标准化的治疗持续时间。我们确定并验证了一种宿主 RNA 标志物,作为预测药敏(DS)和耐多药(MDR)-TB 患者个体化治疗持续时间的生物标志物。

方法

前瞻性纳入了来自德国和罗马尼亚的五个独立队列中的成年肺结核患者。在整个治疗过程中,在预定义的时间点收集临床和微生物学数据以及全血进行 RNA 转录组分析。通过 TBnet 标准(6 个月的培养状态/1 年随访)确定治疗结局。通过机器学习算法开发了一个全血 RNA 治疗终点模型,以确定假设的治疗结束时间点。

结果

在德国鉴定队列(DS-GIC 和 MDR-GIC)中分别招募了 50 例 DS-TB 和 30 例 MDR-TB 患者;在德国验证队列(DS-GVC 和 MDR-GVC)中分别招募了 28 例 DS-TB 和 32 例 MDR-TB 患者;在罗马尼亚验证队列(MDR-RVC)中招募了 52 例 MDR-TB 患者。从 DS 和 MDR-GIC 数据中得出了一个 22 个基因 RNA 模型(TB22),该模型定义了与治愈相关的治疗结束时间点。TB22 模型优于其他已发表的签名,能够准确预测 DS-GVC 患者的临床结局(曲线下面积 0.94,95%CI 0.9-0.98),并表明对于 MDR-GIC(平均减少 218.0 天,34.2%;p<0.001)、MDR-GVC(平均减少 211.0 天,32.9%;p<0.001)和 MDR-RVC(平均减少 161.0 天,23.4%;p=0.001)中的 TB 患者,治疗可能通过缩短疗程来实现。

结论

生物标志物指导的管理可能会显著缩短许多 MDR-TB 患者的治疗持续时间。

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