The remap-cap (Randomized embedded multifactorial adaptive platform for community-acquired pneumonia) Study rationale and design

Derek C. Angus, Scott Berry, Roger J. Lewis, Farah Al-Beidh, Yaseen Arabi, Wilma van Bentum-Puijk, Zahra Bhimani, Marc Bonten, Kristine Broglio, Frank Brunkhorst, Allen C. Cheng, Jean Daniel Chiche, Menno de Jong, Michelle Detry, Herman Goossens, Anthony Gordon, Cameron Green, Alisa M. Higgins, Sebastiaan J. Hullegie, Peter KrugerFrancois Lamontagne, Edward Litton, John Marshall, Anna McGlothlin, Shay McGuinness, Paul Mouncey, Srinivas Murthy, Alistair Nichol, Genevieve K. O'Neill, Rachael Parke, Jane Parker, Gernot Rohde, Kathryn Rowan, Anne Turner, Paul Young, Lennie Derde, Colin McArthur, Steven A. Webb

Research output: Contribution to journalArticleOtherpeer-review

22 Citations (Scopus)

Abstract

There is broad interest in improved methods to generate robust evidence regarding best practice, especially in settings where patient conditions are heterogenous and require multiple concomitant therapies. Here, we present the rationale and design of a large, international trial that combines features of adaptive platform trials with pragmatic point-of-care trials to determine best treatment strategies for patients admitted to an intensive care unit with severe community-acquired pneumonia. The trial uses a novel design, entitled “a randomized embedded multifactorial adaptive platform.” The design has five key features: 1) randomization, allowing robust causal inference; 2) embedding of study procedures into routine care processes, facilitating enrollment, trial efficiency, and generalizability; 3) a multifactorial statistical model comparing multiple interventions across multiple patient subgroups; 4) response-adaptive randomization with preferential assignment to those interventions that appear most favorable; and 5) a platform structured to permit continuous, potentially perpetual enrollment beyond the evaluation of the initial treatments. The trial randomizes patients to multiple interventions within four treatment domains: antibiotics, antiviral therapy for influenza, host immunomodulation with extended macrolide therapy, and alternative corticosteroid regimens, representing 240 treatment regimens. The trial generates estimates of superiority, inferiority, and equivalence between regimens on the primary outcome of 90-day mortality, stratified by presence or absence of concomitant shock and proven or suspected influenza infection. The trial will also compare ventilatory and oxygenation strategies, and has capacity to address additional questions rapidly during pandemic respiratory infections. As of January 2020, REMAP-CAP (Randomized Embedded Multifactorial Adaptive Platform for Community-acquired Pneumonia) was approved and enrolling patients in 52 intensive care units in 13 countries on 3 continents. In February, it transitioned into pandemic mode with several design adaptations for coronavirus disease 2019. Lessons learned from the design and conduct of this trial should aid in dissemination of similar platform initiatives in other disease areas.

Original languageEnglish
Pages (from-to)879-891
Number of pages13
JournalAnnals of the American Thoracic Society
Volume17
Issue number7
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Bayesian adaptive platform trial
  • Community-acquired pneumonia
  • Coronavirus disease 2019
  • Master protocol
  • Randomized clinical trial

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