Statistical Methods for Cancer Clinical Trials

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DESCRIPTION (provided by applicant): The overarching goal of this ambitious program project continues to be to develop innovative, transformative statistical methods for cancer clinical trials that have the potential to hasten successful introduction of new therapies and treatment strategies into practice. Advances in the biologic, genomic, statistical, and computational sciences hold great promise for the development of personalized cancer treatments. Our multi-institutional, interdisciplinary team of investigators will leverage these advances to create new clinical trial designs and data analysis approaches that resolve many of the key limitations of current statistical methods and that maximize the effectiveness of clinical trials for personalized cancer medicine. In addition, we will foster translation of these methods into practice, including carrying out pilot animal and human studies based on the new methodology. The program will achieve these objectives through five, interrelated research projects carried out by investigators with complementary expertise in the statistical, computational, and clinical sciences from three institutions. The first four projects focus on developing new trial designs and analysis methods that integrate biomarkers for efficient discovery of new, personalized treatments; on creating methods for analysis of existing data on biomarkers and patient reported outcomes to inform and improve the design of future studies; developing methods for maximizing the power of pharmacogenomics for identifying biomarkers and candidate individualized therapies; and creating new methods for discovering and validating sequential, personalized decision-making strategies for cancer treatment. The fifth project will integrate the methods into novel preclinical and clinical studies of pancreatic cancer. Our comprehensive approach involves an energetic and coordinated process for implementation, communication, and dissemination of results, including development of professional, public-use software and associated tutorials; workshops and other outreach mechanisms; and program-sponsored symposia and events, to accelerate the adoption of the methods in practice. The proposed clinical trial design and analysis innovations have the potential to effect a paradigm shift in the way cancer clinical trials are conducted for discovery and validation of personalized medicine. This comprehensive, multi-institutional effort will lead to significant innovations in cancer clinical trial practice that will result in improved health of cancer patients.