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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

Research output: Contribution to journalArticle

  • Marlieke EA de Kraker
  • Harriet Sommer
  • Femke de Velde
  • Isaac Gravestock
  • Emmanuel Weiss
  • Alexandra McAleenan
  • Stavros Nikolakopoulos
  • Ohad Amit
  • Teri Ashton
  • Jan Beyersmann
  • Leonhard Held
  • Andrew M Lovering
  • Alasdair MacGowan
  • Johan W Mouton
  • Jean-François Timsit
  • David Wilson
  • Martin Wolkewitz
  • Esther Bettiol
  • Aaron Dane
  • Stephan Harbarth
Original languageEnglish
Article numberciy516
Number of pages10
JournalClinical Infectious Diseases
Early online date13 Aug 2018
DateAccepted/In press - 15 Jun 2018
DateE-pub ahead of print (current) - 13 Aug 2018


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.

    Research areas

  • randomized clinical trials, multidrug-resistant organisms, novel biostatistical methods, clinical trial design, antibacterial drug development

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