|Title||Estimation of treatment effect for the sequential parallel design.|
|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Tamura, Roy N., Xiaohong Huang, and Dennis D. Boos|
|Date Published||2011 Dec 30|
|Keywords||Bias, Biostatistics, Depressive Disorder, Major, Humans, Likelihood Functions, Linear Models, Mental Disorders, Randomized Controlled Trials as Topic, Serotonin Uptake Inhibitors, Tetrahydrofolates, Treatment Outcome|
The sequential parallel clinical trial is a novel clinical trial design being used in psychiatric diseases that are known to have potentially high placebo response rates. The design consists of an initial parallel trial of placebo versus drug augmented by a second parallel trial of placebo versus drug in the placebo non-responders from the initial trial. Statistical research on the design has focused on hypothesis tests. However, an equally important output from any clinical trial is the estimate of treatment effect and variability around that estimate. In the sequential parallel trial, the most important treatment effect is the effect in the overall population. This effect can be estimated by considering only the first phase of the trial, but this ignores useful information from the second phase of the trial. We develop estimates of treatment effect that incorporate data from both phases of the trial. Our simulations and a real data example suggest that there can be substantial gains in precision by incorporating data from both phases. The potential gains appear to be greatest in moderate-sized trials, which would typically be the case in phase II trials.
|Alternate Journal||Stat Med|
|Original Publication||Estimation of treatment effect for the sequential parallel design.|
|PubMed Central ID||PMC3882761|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
P01 CA142538-01 / CA / NCI NIH HHS / United States
Estimation of treatment effect for the sequential parallel design.