Below are oncology references.
Oncology Studies Domains (TU, TR, RS) (See also Labs), Statistical Analysis, Lymphoma, Presentation
TU - Tumor Identification
TR - Tumor Results
RS - Disease Response
Over 200 different types of cancer: Men most common is prostate cancer, women is breast cancer
Response Evaluation Criteria in Solid Tumors (RECIST) - Lesions are classified as (Responded, Stable or Progress)
Objectives - Overall Survival (OS) - time from randomization until death from any cause, Classification of Tumor Lesions by size, Change in Tumor (Nadir/Best Response, Shrinkage/Response, Growth/Progression), Quality of Life (QoL)
Classification of Response: Complete Response (CR), Partial Response (PR), Stable Response (SR), Progressive Disease (PD)
Survival Endpoints:
Time to Tumor Progression (TTP) - time from randomization until radiological tumor progression
Progression Free Survival (PFS) - time from randomization until objective tumor progression or death from any cause, whichever is first,
Disease Free Survival (DFS) - time from randomization until recurrence of tumor or death from any cause, assume patient is disease-free at enrollment
Time to Treatment Failure (TTF) - time from randomization until treatment discontinue for any reason
Objective Response Rate (ORR) - Sum of complete and partial responses
Response Duration (DR)
1. Oncology Trials 101 - The Basics and Then Some, Dave Polus
2. Brief Introduction of Oncology Domains in SDTMIG, Version 3.2, Haishan Kadeerbai
3. Oncology endpoints: An unexpected journey, Waseem Jugon, Mijanur Rahman, [Presentation, Beginner]
4. Efficacy endpoints in Oncology, Angelo Tinazzi [Presentation, Survival Analysis, Biomarker, Metastasis, Presentation]
5. ADaM tips and Tricks Oncology Domains [Presentation]
6. Case Study of CDISC Submission at Novartis Oncology [Presentation]
7. What makes Oncology special?, Johanna MURSIC [Presentation]
8. SDTM Oncology Domains: From Patient to Data to Narrative, Ken Stoltzfus [Presentation] [Paper]
9. CDISC Journey in Solid Tumor using RECIST 1.1 [Presentation]
10. Oncology Basics [Presentation]
11. 7 Steps to Progression Free Survival Insights Using SASĀ®, Karen Walker
12. Objective tumor response and RECIST criteria in cancer clinical trials, Jian Yu [SAS Macro]
14. RECIST and programming challenges, Mahesh Mayakuntla, Prasanna Nidamathy [Presentation]
16. SAS Macro to Implement Survival Analyses for Oncology Trials, Adeline Yeo
17. Macro for Managing Date Variable(s) in Oncology Research, Jagannath Ghosh
18. Waterfall Charts in Oncology Trials - Ride the Wave, Niraj J. Pandya
20. Applying ADaM Principles in Developing a Response Analysis Dataset, Mei Dey, Lisa Pyle
21. IMPLEMENTATION OF ONCOLOGY SPECIFIC SDTM DOMAINS [Poster]
22. Tips for Creating Oncologic Efficacy Summary Tables using PROC LIFETEST and PROC PHREG, Scott Michael Ward [Macro]
27. Multiple Applications of ADaM Time-to-Event Datasets, Huei-Ling Chen, Helen Wang [ADTTE]
29. Implementation of Oncology Specific SDTM domains, Jacintha Eben
30. Creating Time to Event ADaM Dataset for a Complex Efficacy Endpoint in Multiple Sclerosis Therapeutic Area, Ittai Rambach [Multiple Censors]
31. Why and What Standards for Oncology Studies (Solid Tumor, Lymphoma and Leukemia)?, Kevin Lee
33. ADaM - Tips and Tricks Oncology Domains [Presentation]
34. Graphical Results in Clinical Oncology Studies, Nora Ruel, Paul Frankel
35. Data and Analysis Considerations in Oncology Clinical Trials
36. ONLINE ENDPOINT ADJUDICATION IN ONCOLOGY [Presentation]
37. Automation of SDTM Programming in Oncology Disease Response Domain, Yiwen Wang, Yu Cheng, Ju Chen
38. Useful SAS techniques in Efficacy Analysis for Oncology studies, Joy Zeng [Tutorial, Target, Non-Target, Censoring]
39. Jump Start your Oncology knowledge, Xiaoyin (Sherry) Zhong, Feng Liu
40. Analysis of Oncology Studies for Programmers and Statisticians, Kevin Lee
42. ADINTDT and ADTTE for Survival Sweep in Oncology Studies, Wenyu Hu, Christine Teng
43. Efficacy ADaMs in Oncology – Step by Step (Dataset by Dataset), Ilya Krivelevich, Ran Xie, Simon Lin
44. Creating Time to Event ADaM Dataset for a Complex Efficacy Endpoint in Multiple Sclerosis Therapeutic Area, Ittai Rambach [Relapse]