Key result
The decision theory approach for sample size calculation in non-inferiority trials yielded an optimal sample size of 500 patients compared to 788 patients using the classic frequentist approach.
Absolute Event Rate: 500% vs 788%
The decision theory approach may be more appropriate than the frequentist approach for sample size calculation in non-inferiority trials as it incorporates costs and health consequences.
May support smaller non-inferiority trials via decision theory; leaves open prospective validation before adoption.
BACKGROUND: Non-inferiority trials are performed when the main therapeutic effect of the new therapy is expected to be not unacceptably worse than that of the standard therapy, and the new therapy is expected to have advantages over the standard therapy in costs or other (health) consequences. These advantages however are not included in the classic frequentist approach of sample size calculation for non-inferiority trials. In contrast, the decision theory approach of sample size calculation does include these factors. The objective of this study is to compare the conceptual and practical aspects of the frequentist approach and decision theory approach of sample size calculation for non-inferiority trials, thereby demonstrating that the decision theory approach is more appropriate for sample size calculation of non-inferiority trials. METHODS: The frequentist approach and decision theory approach of sample size calculation for non-inferiority trials are compared and applied to a case of a non-inferiority trial on individually tailored duration of elastic compression stocking therapy compared to two years elastic compression stocking therapy for the prevention of post thrombotic syndrome after deep vein thrombosis. RESULTS: The two approaches differ substantially in conceptual background, analytical approach, and input requirements. The sample size calculated according to the frequentist approach yielded 788 patients, using a power of 80% and a one-sided significance level of 5%. The decision theory approach indicated that the optimal sample size was 500 patients, with a net value of €92 million. CONCLUSIONS: This study demonstrates and explains the differences between the classic frequentist approach and the decision theory approach of sample size calculation for non-inferiority trials. We argue that the decision theory approach of sample size estimation is most suitable for sample size calculation of non-inferiority trials.
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Bouman et al. (2015) studied Post thrombotic syndrome after deep vein thrombosis (case study). Decision theory approach for sample size calculation vs. Frequentist approach was evaluated on Calculated sample size. The decision theory approach for sample size calculation in non-inferiority trials yielded an optimal sample size of 500 patients compared to 788 patients using the classic frequentist approach.
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