%0 Journal Article %1 Stallard:2003:Stat-Med:12587100 %A Stallard, N %A Todd, S %D 2003 %J Stat Med %K ClinicalTrials statistics %N 5 %P 689-703 %R 10.1002/sim.1362 %T Sequential designs for phase III clinical trials incorporating treatment selection %U https://www.ncbi.nlm.nih.gov/pubmed/12587100 %V 22 %X Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power.

@article{Stallard:2003:Stat-Med:12587100, abstract = {Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power.}, added-at = {2019-11-17T06:52:04.000+0100}, author = {Stallard, N and Todd, S}, biburl = {https://www.bibsonomy.org/bibtex/2b60c5c1f74e95f9696c7ec4b3924977f/jkd}, description = {Sequential designs for phase III clinical trials incorporating treatment selection. - PubMed - NCBI}, doi = {10.1002/sim.1362}, interhash = {201b9c41115fa4e342389c64f0f1fdf4}, intrahash = {b60c5c1f74e95f9696c7ec4b3924977f}, journal = {Stat Med}, keywords = {ClinicalTrials statistics}, month = mar, number = 5, pages = {689-703}, pmid = {12587100}, timestamp = {2019-11-17T06:52:04.000+0100}, title = {Sequential designs for phase III clinical trials incorporating treatment selection}, url = {https://www.ncbi.nlm.nih.gov/pubmed/12587100}, volume = 22, year = 2003 }