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Background Achieving hepatitis C elimination is hampered by the costs oftreatment and the need to treat hard-to-reach populations. Treatment accesscould be widened by shortening treatment, but limited research means it isunclear which strategies could achieve sufficiently high cure rates to beacceptable. We present the statistical aspects of a multi-arm trial designed totest multiple strategies simultaneously with a monitoring mechanism to detectand stop those with unacceptably low cure rates quickly. Methods The VIETNARMStrial will factorially randomise patients to three randomisations. We will useBayesian monitoring at interim analyses to detect and stop recruitment intounsuccessful strategies, defined as a >0.95 posterior probability of the truecure rate being <90%. Here, we tested the operating characteristics of thestopping guideline, planned the timing of the interim analyses and exploredpower at the final analysis. Results A beta(4.5, 0.5) prior for the true curerate produces <0.05 probability of incorrectly stopping a group with true curerate >90%. Groups with very low cure rates (<60%) are very likely (>0.9probability) to stop after ~25% patients are recruited. Groups with moderatelylow cure rates (80%) are likely to stop (0.7 probability) before the end ofrecruitment. Interim analyses 7, 10, 13 and 18 months after recruitmentcommences provide good probabilities of stopping inferior groups. For anoverall true cure rate of 95%, power is >90% to detect non-inferiority in theregimen and strategy comparisons using 5% and 10% margins respectively,regardless of the control cure rate, and to detect a 5% absolute difference inthe ribavirin comparison. Conclusions The operating characteristics of thestopping guideline are appropriate and interim analyses can be timed to detectfailing groups at various stages.

The design and statistical aspects of VIETNARMS: a strategic  post-licensing trial of multiple oral direct acting antiviral Hepatitis C  treatment strategies in Vietnam