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

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...

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Detalles Bibliográficos
Autores principales: de Kraker, Marlieke E A, Sommer, Harriet, de Velde, Femke, Gravestock, Isaac, Weiss, Emmanuel, McAleenan, Alexandra, Nikolakopoulos, Stavros, Amit, Ohad, Ashton, Teri, Beyersmann, Jan, Held, Leonhard, Lovering, Andrew M, MacGowan, Alasdair P, Mouton, Johan W, Timsit, Jean-François, Wilson, David, Wolkewitz, Martin, Bettiol, Esther, Dane, Aaron, Harbarth, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6260160/
https://www.ncbi.nlm.nih.gov/pubmed/30107400
http://dx.doi.org/10.1093/cid/ciy516
Descripción
Sumario: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.