Cancer Biostatistics Training Grant

University Of Pennsylvania, Philadelphia PA

Investigators

Linked publications, trials & patents

Abstract

DESCRIPTION (provided by applicant): In response to the NIH announcement regarding the Availability of Recovery Act Funds for Competitive Revision Applications (NOT-OD-09-058), the Center for Clinical Epidemiology and Biostatistics (CCEB) of the University of Pennsylvania (Penn) School of Medicine (SOM) proposes to expand the ongoing and successful pre-doctoral training program in cancer biostatistics. The objective of this program is to train individuals to be rigorous and independent academic investigators able to use the range of approaches in biostatistics to address questions in cancer research. The program is specifically built upon existing collaborative relationships among biostatistics, statistics, and cancer research faculty in the CCEB and Department of Biostatistics and Epidemiology (DBE), the Abramson Cancer Center (ACC), and Wharton's Department of Statistics (STAT) at Penn. Penn Medicine, comprised of the SOM and the University of Pennsylvania Health System (UHPS), contributes substantially to the local economy. In 2008, Penn Medicine created 37,000 jobs and $5.4B in regional economic activity, with the area's highly trained workforce producing more than 24,600 applications for just 840 open Penn staff research positions. This pre-doctoral training program for PhD students in Statistics and Biostatistics, who have advanced to the dissertation stage of their training, provides didactic training in fundamental skills, methodologies, and principles of biostatistics, with emphasis on the areas of most importance to cancer research. Trainees are required to obtain a strong background in substantive areas related to cancer through participation in research seminars and a series of interdisciplinary courses in cancer research and cancer biology that examine methodologic issues, scientific approaches, technologies, concepts, and applications of statistical approaches in cancer research. Specifically, the training program is designed to: 1) provide in-depth knowledge of the biostatistical techniques appropriate to cancer research;2) provide research experiences with mentors in both biostatistics and cancer research;and 3) provide an inter-disciplinary infrastructure, bringing together faculty and students in the CCEB, DBE, ACC, and STAT, designed to support graduate education in cancer biostatistics. The expanded program will add an additional fellowship slot in 2009-10 and 2010-11 to the four fellowships supported currently by the ongoing training program. The strengths of the program are its training program in biostatistics, including comprehensive course offerings available to students;the wide-ranging experience of the biostatistics faculty in multiple areas of biostatistics methods and cancer research;the commitment of the faculty to collaborative research and training;the established teaching program in Statistics offered by the Wharton School;the long history of successful clinical research training programs offered by the CCEB;and the existing collaborative links among CCEB and DBE faculty in biostatistics and epidemiology, the ACC, and STAT. The resources available to students include a broad array of ongoing research projects, including clinical trials, observational studies, translational research, and experimental studies. Penn's commitment to collaborative research and training and the broad range of expertise and experiences of faculty participating in this training program provide an ideal environment for this training program. RELEVANCE: Biostatistics is a field that has grown nationwide in importance and influence within the last 15 to 20 years. The need for qualified biostatisticians in academia has never been more acute, as there is an enormous national shortage of qualified personnel for academic faculty positions in biostatistics. The need for training in biostatistics in the context of cancer research is especially critical given the important and evolving statistical problems presented in clinical trials of interventions for cancer prevention and treatment, in translational studies bridging the laboratory and the bedside, and the complex problems that arise with new technologies used in clinical and basic laboratory science investigations.