|Title||Superiority of combining two independent trials in interim futility analysis.|
|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Deng, Qiqi, Ying-Ying Zhang, Dooti Roy, and Ming-Hui Chen|
|Journal||Stat Methods Med Res|
|Date Published||2020 Feb|
|Keywords||Clinical Trials, Phase III as Topic, Data Analysis, Data Interpretation, Statistical, Dose-Response Relationship, Drug, Humans, Medical Futility, Models, Statistical, Research Design|
Traditionally, statistical methods for futility analysis are developed based on a single study. To establish a drug's effectiveness, usually at least two adequate and well-controlled studies need to demonstrate convincing evidence on its own. Therefore, in a standard clinical development program in chronic diseases, two independent studies are generally conducted for drug registration. This paper proposes a statistical method to combine interim data from two independent and similar studies for interim futility analysis and shows that the conditional power approach based on combined interim data has better operating characteristics compared to the approach based on single-trial interim data, even with small to moderate heterogeneity on the treatment effects between the two studies.
|Alternate Journal||Stat Methods Med Res|
|Original Publication||Superiority of combining two independent trials in interim futility analysis.|
|PubMed Central ID||PMC6783334|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 GM070335 / GM / NIGMS NIH HHS / United States
Superiority of combining two independent trials in interim futility analysis.