Optimizing the Design and Analysis of Clinical Trials for Antibacterials Against Multidrug-resistant Organisms: A White Paper From COMBACTE's STAT-Net.

Optimizing the Design and Analysis of Clinical Trials for Antibacterials Against Multidrug-resistant Organisms: A White Paper From COMBACTE's STAT-Net.
复制标题

DOI:
10.1093/cid/ciy516
复制
发表时间:
2018-11-28
期刊:
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
影响因子:
--
通讯作者:
COMBACTE-NET Consortium
COMBACTE-NET Consortium
中科院分区:
其他
文献类型:
--
作者:
de Kraker MEA;Sommer H;de Velde F;Gravestock I;Weiss E;McAleenan A;Nikolakopoulos S;Amit O;Ashton T;Beyersmann J;Held L;Lovering AM;MacGowan AP;Mouton JW;Timsit JF;Wilson D;Wolkewitz M;Bettiol E;Dane A;Harbarth S;COMBACTE-NET Consortium

文献摘要

参考文献

被引文献

相似文献

针对多重耐药微生物的抗菌药物的临床开发迫切需要创新。因此,一个欧洲公私合作工作组(STAT-Net;欧洲对抗细菌耐药性[COMBACTE]的一部分)审查并测试了几项创新试验设计和随机临床试验的分析方法,并提出了8项建议。前三个重点是药代动力学和药效学建模,强调基于人群的药代动力学模型的相关性,重新评估旧抗生素的监管程序,以及严格的质量改进。建议4和5通过使用基于等级或时间依赖的复合终点来解决对更敏感的主要终点的需求。建议6涉及分层嵌套试验设计的适用性,最后2项建议通过贝叶斯方法和/或平台试验纳入历史或伴随试验数据。虽然并非所有这些建议都直接适用,但它们提供了一种可靠的循证方法来开发新的和已建立的抗菌药物并应对这一公共卫生挑战。针对多重耐药微生物的抗生素的临床开发迫切需要创新。COMBACTE-STAT-Net为改进药代动力学-药效学建模、更敏感的主要终点、分层嵌套试验设计以及通过贝叶斯方法和/或平台试验使用历史/伴随试验数据提供了建议。
Innovations are urgently required for clinical development of antibacterials against multidrug-resistant organisms. Therefore, a European, public-private working group (STAT-Net; part of Combatting Bacterial Resistance in Europe [COMBACTE]), has reviewed and tested several innovative trials designs and analytical methods for randomized clinical trials, which has resulted in 8 recommendations. The first 3 focus on pharmacokinetic and pharmacodynamic modeling, emphasizing the pertinence of population-based pharmacokinetic models, regulatory procedures for the reassessment of old antibiotics, and rigorous quality improvement. Recommendations 4 and 5 address the need for more sensitive primary end points through the use of rank-based or time-dependent composite end points. Recommendation 6 relates to the applicability of hierarchical nested-trial designs, and the last 2 recommendations propose the incorporation of historical or concomitant trial data through Bayesian methods and/or platform trials. Although not all of these recommendations are directly applicable, they provide a solid, evidence-based approach to develop new, and established, antibacterials and address this public health challenge. Innovations are urgently required for clinical development of antibiotics against multidrug-resistant organisms. COMBACTE-STAT-Net provides recommendations for improved pharmacokinetic-pharmacodynamic modeling, more sensitive primary end points, hierarchical nested-trial designs, and use of historical/concomitant trial data through Bayesian methods and/or platform trials.
DOI: 10.1016/s0140-6736(13)61134-4
发表时间: 2013-11-23
期刊: LANCET
影响因子: 168.9
作者:
Baeten, Dominique;Baraliakos, Xenofon;Hueber, Wolfgang
通讯作者: Hueber, Wolfgang
DOI: 10.1007/s10928-017-9506-4
发表时间: 2017-04-01
影响因子: 2.5
作者:
Bush, Karen;Page, Malcolm G. P.
通讯作者: Page, Malcolm G. P.
DOI: 10.1002/sim.6233
发表时间: 2014-11-09
影响因子: 2
作者:
Huque, Mohammad F.;Valappil, Thamban;Soon, Guoxing (Greg)
通讯作者: Soon, Guoxing (Greg)
DOI: 10.1111/j.1467-9469.2012.00817.x
发表时间: 2013-09-01
影响因子: 1
作者:
Beyersmann, Jan;Di Termini, Susanna;Pauly, Markus
通讯作者: Pauly, Markus
DOI: 10.1093/jac/dkw226
发表时间: 2016-10-01
影响因子: 5.2
作者:
de Velde, Femke;de Winter, Brenda C. M.;Mouton, Johan W.
通讯作者: Mouton, Johan W.