Biostatistics and Data Management Core

University Of Pennsylvania, Philadelphia PA

Investigators

Linked publications & trials

Abstract

The goal of Core C (Biostatistics & Data Management) is to provide expert guidance and consultation in the[unreadable] biostatistical and data management aspects of the design, conduct, and analysis of research projects[unreadable] generated by the P01. Core C will provide statistical collaboration and also support the P01 's clinical[unreadable] research activities by designing, implementing and operating a data management system for the projects'[unreadable] gene therapy clinical trials. Core C will provide its services to P01 projects at every stage of the research:[unreadable] Prior to the initiation of studies, Core staff will consult with P01 investigators to help them select efficient[unreadable] designs and sample sizes that will give adequate power to address study objectives. For gene therapy[unreadable] clinical trials, they will establish data management systems and design case report forms that collect all[unreadable] required information in an unambiguous way. As studies proceed, Core staff will enter data, manage and[unreadable] monitor clinical trial databases, implement and execute data quality control activities, and prepare data[unreadable] reports. When studies are finished, the Core will conduct correct and efficient data analyses, prepare any[unreadable] necessary graphs and tables, assist investigators with the preparation of presentations and manuscripts, and[unreadable] consult on the design of subsequent research. The work of Core C will involve close integration with the[unreadable] efforts of all the research projects. Core C staff members have extensive experience supporting cancer[unreadable] research, with strong backgrounds in basic science, translational research, clinical trials, research[unreadable] computing, and data management. With their many years of experience in applied and methodologic[unreadable] statistical research, they stand ready to choose the best approaches from the pool of existing methods and[unreadable] to adapt or develop new methods as needed.