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Compared to other therapeutic studies, oncology studies are generally complex and difficult for programmers and statisticians. There is more to understand and to know such as different clinical study types, specific data collection points and analysis. In this seminar, programmers and statisticians will learn oncology specific knowledge in clinical studies and will understand a holistic view of oncology studies from data collection, CDISC datasets, and analysis. Programmers and statisticians will also find out what makes oncology studies unique and learn how to lead oncology study projects effectively. The seminar will cover four different sub types and their response criteria guidelines. The first sub type, Solid Tumor study, usually follows RECIST (Response Evaluation Criteria in Solid Tumor). The second sub type, Immunotherapy study, usually follows irRC (immune-related Response Criteria). The third sub type, Lymphoma study, usually follows Cheson. Lastly, Leukemia studies follow study specific guidelines (e.g., IWCLL for Chronic Lymphocytic Leukemia). The seminar will show how to use response criteria guidelines for data collections and response evaluation.   Programmers and statisticians will learn how to create SDTM tumor specific datasets (RS, TU, TR), what SDTM domains are used for certain data collection, and what Controlled Terminology (e.g., CR, PR, SD, PD, NE) will be applied. They will also learn how to create Time-to-Event ADaM datasets from SDTM domains and how to use ADaM datasets to derive efficacy analysis (e.g., OS, PFS, TTP, ORR, DFS) and Kaplan Meier Curves using SAS Procedures such as PROC LIFETEST and PHREG.   Finally, programmers and statistician will understand how to build end-to-end standards driven oncology studies from protocol, study sub-types, response criteria, data collection, SDTM, ADaM to analysis.   Presented by Kevin Lee.    REGISTER today.
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A Review of "Free" Massive Open Online Content (MOOC) for SAS® Learners Leading online providers are now offering SAS® users with “free” access to content for learning how to use and program in SAS. This content is available to anyone in the form of massive open online content (or courses) (MOOC). Not only is all the content offered for “free”, but it is designed with the distance learner in mind, empowering users to learn using a flexible and self-directed approach. A MOOC represents online content such as a PDF document, course, video or other resources and content that is freely available to the masses using the web. Topics include the various ways anyone who wants to learn SAS programming techniques can access “free” learning technologies including SAS On-Demand for Academics and SAS Studio software, SAS technical support, published PDF “white” papers, code examples, comprehensive notes, instructor lesson plans, hands-on exercises, data files, webinars, videos, audio files, and other content.   Intended Audience: All SAS users Prerequisites: None Type of Presentation: Tutorial with access to MOOC providers Length: 50 minutes   Presented by: Kirk Paul "sasNerd" Lafler Kirk Paul Lafler is a consultant, developer, programmer, educator, and data scientist, and has been a SAS user since 1979. Kirk works as a lecturer and adjunct professor at San Diego State University; and teaches dozens of SAS, SQL, Python, and Excel courses, workshops, and webinars to users around the world. Kirk is the author of several books including PROC SQL: Beyond the Basics Using SAS, Third Edition (SAS Press. 2019) along with hundreds of papers and articles on a variety of SAS, SQL, Python, and Excel topics. Kirk currently serves as the Open-source Advocate and Coordinator for the Western Users of SAS Software (WUSS) organization, and has been selected as an Invited speaker, educator, keynote and section leader at conferences and meetings worldwide; and is the recipient of 29 “Best” contributed paper, hands-on workshop (HOW), and poster awards.   Register today!
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