= Solution
Choose a <group sequential design>. Randomize patients among the three arms, schedule interim analyses after prespecified amounts of information, and calculate the two <Wald test> statistics at each look. Prespecify efficacy boundaries and a futility rule; allow early stopping of an ineffective experimental arm or of the trial when sufficiently convincing efficacy evidence is obtained. Calibrate the boundaries for both repeated looks and the two shared-control comparisons so that the <familywise error rate> remains controlled. An <alpha-spending function> is one way to allocate the error probability across looks.
\b[Two potential benefits] are lower expected recruitment and shorter duration when a treatment is clearly effective or futile, and earlier identification of benefit or lack of benefit, reducing continued exposure to an ineffective experimental treatment. These benefits concern expected performance; the maximum sample size may still be required.
\b[Two drawbacks] are the extra operational work needed for rapid, reliable outcomes and confidential interim analyses, and more complicated inference: repeated testing requires adjusted boundaries, and ordinary fixed-sample effect estimates and <confidence intervals> can be misleading after data-dependent stopping. Continuing two comparisons against a shared control also requires care if an arm is stopped.
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