|Title||Bayesian probability of success for clinical trials using historical data.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Ibrahim, Joseph G., Ming-Hui Chen, Mani Lakshminarayanan, Guanghan F. Liu, and Joseph F. Heyse|
|Date Published||2015 Jan 30|
|Keywords||Aged, Analysis of Variance, Antibodies, Viral, Bayes Theorem, Clinical Trials, Phase II as Topic, Clinical Trials, Phase III as Topic, Computer Simulation, Data Interpretation, Statistical, Decision Making, Female, Herpes Zoster, Herpes Zoster Vaccine, Herpesvirus 3, Human, Humans, Likelihood Functions, Linear Models, Logistic Models, Male, Probability|
Developing sophisticated statistical methods for go/no-go decisions is crucial for clinical trials, as planning phase III or phase IV trials is costly and time consuming. In this paper, we develop a novel Bayesian methodology for determining the probability of success of a treatment regimen on the basis of the current data of a given trial. We introduce a new criterion for calculating the probability of success that allows for inclusion of covariates as well as allowing for historical data based on the treatment regimen, and patient characteristics. A new class of prior distributions and covariate distributions is developed to achieve this goal. The methodology is quite general and can be used with univariate or multivariate continuous or discrete data, and it generalizes Chuang-Stein's work. This methodology will be invaluable for informing the scientist on the likelihood of success of the compound, while including the information of covariates for patient characteristics in the trial population for planning future pre-market or post-market trials.
|Alternate Journal||Stat Med|
|Original Publication||Bayesian probability of success for clinical trials using historical data.|
|PubMed Central ID||PMC4676938|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States|
Bayesian probability of success for clinical trials using historical data.