Amalia Magaret1, Derek C Angus2, Neill K J Adhikari3, Patrick Banura4, Niranjan Kissoon5, James V Lawler6, Shevin T Jacob7. 1. Department of Laboratory Medicine, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA. Electronic address: amag@uw.edu. 2. Department of Critical Care Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA. 3. Department of Critical Care Medicine and Sunnybrook Research Institute, Sunnybrook Health Sciences Centre and Interdepartmental Division of Critical Care, University of Toronto, Toronto, Ontario, Canada. 4. Austere environments Consortium for Enhanced Sepsis Outcomes, Frederick, MD, USA. 5. Department of Pediatrics, British Columbia's Children's Hospital and The University of British Columbia, Vancouver, BC, Canada; Department of Emergency Medicine, British Columbia's Children's Hospital and The University of British Columbia, Vancouver, BC, Canada. 6. Austere environments Consortium for Enhanced Sepsis Outcomes, Frederick, MD, USA; United States Naval Medical Research Center, Frederick, MD, USA. 7. Austere environments Consortium for Enhanced Sepsis Outcomes, Frederick, MD, USA; Department of Medicine, University of Washington, Seattle, WA, USA; International Respiratory and Severe Illness Center (INTERSECT), University of Washington, Seattle, WA, USA.
Abstract
BACKGROUND: Clinical trial designs that include multiple treatments are currently limited to those that perform pairwise comparisons of each investigational treatment to a single control. However, there are settings, such as the recent Ebola outbreak, in which no treatment has been demonstrated to be effective; and therefore, no standard of care exists which would serve as an appropriate control. METHODS/ DESIGN: For illustrative purposes, we focused on the care of patients presenting in austere settings with critically ill 'sepsis-like' syndromes. Our approach involves a novel algorithm for comparing mortality among arms without requiring a single fixed control. The algorithm allows poorly-performing arms to be dropped during interim analyses. Consequently, the study may be completed earlier than planned. We used simulation to determine operating characteristics for the trial and to estimate the required sample size. RESULTS: We present a potential study design targeting a minimal effect size of a 23% relative reduction in mortality between any pair of arms. Using estimated power and spurious significance rates from the simulated scenarios, we show that such a trial would require 2550 participants. Over a range of scenarios, our study has 80 to 99% power to select the optimal treatment. Using a fixed control design, if the control arm is least efficacious, 640 subjects would be enrolled into the least efficacious arm, while our algorithm would enroll between 170 and 430. This simulation method can be easily extended to other settings or other binary outcomes. CONCLUSION: Early dropping of arms is efficient and ethical when conducting clinical trials with multiple arms.
RCT Entities:
BACKGROUND: Clinical trial designs that include multiple treatments are currently limited to those that perform pairwise comparisons of each investigational treatment to a single control. However, there are settings, such as the recent Ebola outbreak, in which no treatment has been demonstrated to be effective; and therefore, no standard of care exists which would serve as an appropriate control. METHODS/ DESIGN: For illustrative purposes, we focused on the care of patients presenting in austere settings with critically ill 'sepsis-like' syndromes. Our approach involves a novel algorithm for comparing mortality among arms without requiring a single fixed control. The algorithm allows poorly-performing arms to be dropped during interim analyses. Consequently, the study may be completed earlier than planned. We used simulation to determine operating characteristics for the trial and to estimate the required sample size. RESULTS: We present a potential study design targeting a minimal effect size of a 23% relative reduction in mortality between any pair of arms. Using estimated power and spurious significance rates from the simulated scenarios, we show that such a trial would require 2550 participants. Over a range of scenarios, our study has 80 to 99% power to select the optimal treatment. Using a fixed control design, if the control arm is least efficacious, 640 subjects would be enrolled into the least efficacious arm, while our algorithm would enroll between 170 and 430. This simulation method can be easily extended to other settings or other binary outcomes. CONCLUSION: Early dropping of arms is efficient and ethical when conducting clinical trials with multiple arms.
Authors: Helen Mossop; Michael J Grayling; Ferdia A Gallagher; Sarah J Welsh; Grant D Stewart; James M S Wason Journal: Br J Cancer Date: 2021-11-08 Impact factor: 7.640
Authors: Nigel Stallard; Lisa Hampson; Norbert Benda; Werner Brannath; Thomas Burnett; Tim Friede; Peter K Kimani; Franz Koenig; Johannes Krisam; Pavel Mozgunov; Martin Posch; James Wason; Gernot Wassmer; John Whitehead; S Faye Williamson; Sarah Zohar; Thomas Jaki Journal: Stat Biopharm Res Date: 2020-07-29 Impact factor: 1.452