The REMAP-CAP (Randomized Embedded Multifactorial Adaptive Platform for Community-acquired Pneumonia) Study. Rationale and Design

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.Clinical trial registered with www.clinicaltrials.gov (NCT02735707).

Keywords: Bayesian adaptive; community-acquired pneumonia; coronavirus disease 2019; master protocol; platform trial; randomized clinical trial.

Figure 1.

Schematic of the REMAP-CAP (Randomized Embedded Multifactorial Adaptive Platform for Community-acquired Pneumonia) design. CAP = community-acquired pneumonia; DSMB = Data Safety Monitoring Board; EHR = electronic health record; ICU = intensive care unit; RCCs = regional coordinating centers; SAC = statistical analysis committee.

Figure 2.

Overview of the REMAP-CAP (Randomized Embedded Multifactorial Adaptive Platform for Community-acquired Pneumonia) documentation and oversight. (A) Structure of the REMAP-CAP protocol and appendix documents. (B) Organogram of the REMAP-CAP oversight. ANZ = Australian and New Zealand; ANZ RMC = Australia and New Zealand Regional Management Committee; CRMC = Canadian Regional Management Committee; DSA = domain-specific appendix; DSMB = Data and Safety Monitoring Board; DSWG = domain-specific working group; EU = European; EU RMC = Europe Regional Management Committee; IIG = International Interest Group; IPWG = International Pandemic Working Group; ITSC = International Trial Steering Committee; RMC = Regional Management Committee; RSA = region specific appendix; SAC = Statistical Analysis Committee.

Figure 3.

Trial simulations comparing REMAP (Randomized Embedded Multifactorial Adaptive Platform) to traditional randomized clinical trial designs. The operating characteristics of alternative study designs are evaluated by running a Monte Carlo program, which randomly draws trial samples from simulated populations with predetermined characteristics (alternative “truths” about the true yet unknown effect of an intervention or regimen in a population). Each simulated trial accrues patients one at a time until a sample size of 2,000. The simulated trials are repeated 10,000-fold and the summary of all trials under each simulated scenario provides estimates of average trial performance. In all instances, the simulations are of trials testing eight regimens, consisting of three domains with two interventions in each domain (2³ = 8 regimens). Results are presented for a comparison of a standard trial design, with equal allocation to each arm, versus a REMAP design, using response-adaptive randomization (RAR) to preferentially assign patients over time to better-performing arms. Sample size (primary y-axis) is 250 per arm for the standard design (represented by a solid horizontal line); gray bars indicate the REMAP design. Probability of superiority (a proxy for power, secondary y-axis) is represented as an open red circle for the standard design and a solid red circle for the REMAP design. The predetermined characteristics of the underlying simulated population are represented in the upper portion of each panel. (A) Result summary under a simulated truth where regimen 8 is superior, regimen 5 is second best, and all others are inferior, but equivalent. (B) Result summary where regimens 5 and 8 are equally good, but regimens 1, 3, 4, and 7 are harmful with respect to regimens 2 and 6. In both scenarios, power is similar or superior with the REMAP design, yet, because RAR minimizes exposure to arms performing less well, results are generated with fewer deaths.