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Multi-arm multi-stage trials can improve the efficiency of finding effective treatments for stroke: a case study
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Journal Article
Multi-arm multi-stage trials can improve the efficiency of finding effective treatments for stroke: a case study
2018
Overview
Background
Many recent Stroke trials fail to show a beneficial effect of the intervention late in the development. Currently a large number of new treatment options are being developed. Multi-arm multi-stage (MAMS) designs offer one potential strategy to avoid lengthy studies of treatments without beneficial effects while at the same time allowing evaluation of several novel treatments.
In this paper we provide a review of what MAMS designs are and argue that they are of particular value for Stroke trials. We illustrate this benefit through a case study based on previous published trials of endovascular treatment for acute ischemic stroke.
We show in this case study that MAMS trials provide additional power for the same sample size compared to alternative trial designs. This level of additional power depends on the recruitment length of the trial, with most efficiency gained when recruitment is relatively slow. We conclude with a discussion of additional considerations required when starting a MAMS trial.
Conclusion
MAMS trial designs are potentially very useful for stroke trials due to their improved statistical power compared to the traditional approach.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
Subject
Adaptive Clinical Trials as Topic - methods
/ Adaptive Clinical Trials as Topic - statistics & numerical data
/ Analysis
/ Brain Ischemia - physiopathology
/ Data Interpretation, Statistical
/ Debate
/ Endovascular Procedures - adverse effects
/ Endovascular Procedures - statistics & numerical data
/ Humans
/ Ischemia
/ Medicine
/ Multi-arm multi-stage trials
/ Non-coronary artery cardiac disease
/ Randomized Controlled Trials as Topic - methods
/ Randomized Controlled Trials as Topic - statistics & numerical data
/ Research Design - statistics & numerical data
/ Stroke
