The article discusses the application of BayesPPDSurv in the context of a high-risk melanoma clinical trial. Focusing on the use of the Normalized Power Prior within a Piecewise Constant Hazard Proportional Hazards (PWCH-PH) model, the study highlights the methodology for estimating coefficients and assessing power and type I error rates for time-to-event data. A case study involving Interferon Alpha-2b treatment illustrates the advantages of incorporating historical data in Bayesian frameworks to refine survival predictions and trial outcomes, particularly for patients classified with stage four melanoma.
The proposed BayesPPDSurv method allows for accurate coefficient estimation and reliability in power and type I error rate calculations for time-to-event data in clinical trials.
Using historical data effectively enhances the Bayesian analytical approach, exemplified in the melanoma trials where the prior distributions improve estimations of survival outcomes.
Collection
[
|
...
]