Chapter 19 • The process of conducting cancer research must change in the face of prohibitive costs and limited patient resources. • Biostatistics has a tremendous impact on the level of science in cancer research, especially in the design and conducting of clinical trials. • The Bayesian statistical approach to clinical trial design and conduct can be used to develop more efficient and effective cancer studies. • Modern technology and advanced analytic methods are directing the focus of medical research to subsets of disease types and to future trials across different types of cancer. • A consequence of the rapidly changing technology for generating “omics” data is that biological assays are often not stable long enough to discover and validate a model in a clinical trial. • Bioinformaticians must use technology-specific data normalization procedures and rigorous statistical methods to account for sample collecting, batch effects, multiple testing, confounding covariates, and any other potential biases. • Best practices in developing prediction models include public access to the information, rigorous validation of the model, and model lockdown prior to its use in patient care management.
Biostatistics and Bioinformatics in Clinical Trials
Summary of Key Points
Biostatistics and Bioinformatics in Clinical Trials
