WITHDRAWN Treatment effect evaluation with permissible non-concurrent controls in platform trials

Music City Center 

Platform trials efficiently evaluate treatment effects by permitting the addition of multiple treatment groups using a common control group within a trial. While non-concurrent control data can improve statistical power, it can also introduce serious bias in the estimated treatment effect if heterogeneity occurs between the non-concurrent and concurrent control data. Existing methods fully borrow non-concurrent control data, ignoring the possibility of reduced heterogeneity among data closer in time to the concurrent controls.
We developed a novel method for evaluating treatment effects, in that, based on the likelihood ratio, the non-concurrent control data regarded as the low possibility heterogeneity for the concurrent control data back in time is determined.
A simulation study comparing the performance of the proposed method with five others revealed two distinct types; one is unbiased estimates, non-inflated α error rates and typical power, and the other is biased estimates, inflated α error rates and higher power. The proposed method belonged to the latter type and, in this type, had a smaller bias and less inflated α error rates than the other methods.

Platform Trial

Non-concurrent control

Time-trend heterogeneity 

Section on Statistics in Epidemiology