A Practical Guide to Optimal Adaptive Two‐Stage Designs for Various Endpoint Types

Description

Nico Bruder, Jan Meis, Maximilian Pilz, and Meinhard Kieser wrote a practical guide to designing adaptive two-stage clinical trials that squeeze the most from limited patients. Adaptive trials can resize themselves at an interim look, which protects both resources and conclusions. Choosing the best design settings means minimizing something like expected enrollment while holding error rates firm, yet older guidance covered mostly normal-shaped data or binary outcomes handled by brute force.

The guide shows how standard test statistics behave close enough to normal curves that the same optimization machinery extends to yes-or-no outcomes and time-to-event outcomes. Worked results show tuned designs cutting expected sample sizes and raising the power left after the interim look, compared with standard sequential plans. A warning section flags traps in two-sided testing. The authors aim the guidance squarely at rare disease research, where every patient counts.

Catalog record

Source: https://europepmc.org/article/MED/PMC13621332