Core C The goals of Core C (Biostatistics and Data Management) are to provide expert biostatistical guidance in the design, conduct and analysis of research projects comprising the program project and to assist the clinical investigators in developing a reliable and accurate data management system. Core C will provide biostatistical support to the research projects at every stage of the research. Core staff will work with investigators to develop efficient designs and sample sizes that will give adequate power to address study objectives. For clinical studies, we will contribute to the design of case report forms that collect all required information in an unambiguous way. As studies proceed, Core staff will assist in reviewing project databases and monitoring the quantity and quality of data collected, and will suggest modifications to the design or analysis plan as appropriate. Core members will conduct correct and efficient data analyses, prepare any necessary graphs and tables, assist investigators with the preparation of presentations and manuscripts, and consult on the design of subsequent research. The work of Core C will interface with the Animal/Pathology Core, particularly with respect to study design, as animal studies are planned and executed. The Core C staff members have extensive experience supporting cancer research, with strong backgrounds in basic science, translational research and clinical trials in addition to being themselves researchers in statistical methods. With their many years of experience with the PDT group, they look forward to further collaborative opportunities for both applying existing methods and adapting or developing new methods as needed.
Core C Core C helps investigators determine whether results seen in their studies could have occurred just by chance or luck, and whether their results may be important to developing new treatments for mesothelioma.
|Simone 2nd, Charles B; Cengel, Keith A (2014) Photodynamic therapy for lung cancer and malignant pleural mesothelioma. Semin Oncol 41:820-30|
|Han, Sung Wan; Mesquita, Rickson C; Busch, Theresa M et al. (2014) A Method for Choosing the Smoothing Parameter in a Semi-parametric Model for Detecting Change-points in Blood Flow. J Appl Stat 41:26-45|
|Liang, Xing; Wang, Ken Kang-Hsin; Zhu, Timothy C (2013) Feasibility of interstitial diffuse optical tomography using cylindrical diffusing fibers for prostate PDT. Phys Med Biol 58:3461-80|
|Maas, Amanda L; Carter, Shirron L; Wileyto, E Paul et al. (2012) Tumor vascular microenvironment determines responsiveness to photodynamic therapy. Cancer Res 72:2079-88|
|Friedberg, Joseph S; Culligan, Melissa J; Mick, Rosemarie et al. (2012) Radical pleurectomy and intraoperative photodynamic therapy for malignant pleural mesothelioma. Ann Thorac Surg 93:1658-65; discussion 1665-7|
|Grossman, Craig E; Pickup, Stephen; Durham, Amy et al. (2011) Photodynamic therapy of disseminated non-small cell lung carcinoma in a murine model. Lasers Surg Med 43:663-75|
|Sandell, Julia L; Zhu, Timothy C (2011) A review of in-vivo optical properties of human tissues and its impact on PDT. J Biophotonics 4:773-87|
|Busch, Theresa M; Wang, Hsing-Wen; Wileyto, E Paul et al. (2010) Increasing damage to tumor blood vessels during motexafin lutetium-PDT through use of low fluence rate. Radiat Res 174:331-40|
|Wang, Ken Kang-Hsin; Finlay, Jarod C; Busch, Theresa M et al. (2010) Explicit dosimetry for photodynamic therapy: macroscopic singlet oxygen modeling. J Biophotonics 3:304-18|
|Busch, Theresa M (2010) Hypoxia and perfusion labeling during photodynamic therapy. Methods Mol Biol 635:107-20|
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