Value-based trials aim to maximize the expected net benefit by balancing technology adoption decisions and clinical trial costs. Adaptive trials offer additional efficiency. This paper provides guidance on determining whether a value-based sequential design is the best option for an adaptive two-arm trial, illustrated through a case study. We outline four steps for the value-based sequential approach. The case study re-evaluates the Big CACTUS trial design using pilot trial data and a model-based health economic analysis. Expected net benefit is computed for (a) original fixed design, (b) value-based design with fixed sample size, and (c) optimal value-based sequential design with adaptive stopping. We compare pre-trial modelling with actual Big CACTUS trial results. Over ten years, the adoption decision would impact approximately 215,378 patients. Pre-trial modelling shows that the expected net benefit minus costs is (a) £102m for the original fixed design, (b) £107m (+5.3% higher) for the value-based design with optimal fixed sample size, and (c) £109m (+6.7% higher) for the optimal value-based sequential design with maximum sample size of 435 per arm. Post hoc analysis using actual Big CACTUS trial data indicates that the value-adaptive trial with a maximum sample size of 95 participant pairs wouldn't have stopped early. Bootstrap simulations reveal a 9.76% probability of early completion with n=95, compared to 31.50% with n=435. The four-step approach to value-based sequential two-arm design with adaptive stopping was successfully implemented. Further application of value-based adaptive approaches could be useful to assess efficiency of alternative study designs.