Oncology Domains  

Below are oncology references.


Oncology Studies Domains (TU, TR, RS) (See also Labs), Statistical AnalysisLymphoma, 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]

13. From Local Laboratory to Standardisation and beyondApplying a common grading system, Angelo Tinazzi, Irene Corradino, Enrica Paschetto, Sonia Colombini 

14. RECIST and programming challenges, Mahesh Mayakuntla, Prasanna Nidamathy [Presentation]

15. Efficacy analysis and graphical representation in Oncology trials - A case study, Anindita Bhattacharjee and Vijayalakshmi Indana [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

19. Reliability Assessment of Image Data in Oncology and Psychology Studies, Li Zhang, David Shen, Gary Chen

20. Applying ADaM Principles in Developing a Response Analysis Dataset, Mei Dey, Lisa Pyle


22. Tips for Creating Oncologic Efficacy Summary Tables using PROC LIFETEST and PROC PHREG, Scott Michael Ward [Macro]

23. Common Variables in Adverse Event and Exposure analysis datasets specific for Oncology clinical trials Haridasan Namboodiri [Macro]

24. Design and Construct Efficacy Analysis Datasets in Late Phase Oncology Studies, Huadan Li, Changhong Shi

25. Lessons Learned From Implementation Experience of ADaM, An Oncology Case Study, Zhuoye Xu, Susan Zhao

26. Two different use cases to obtain best responses using RECIST 1.1: SDTM and ADaM, Kevin Lee, Vikash Jain

27. Multiple Applications of ADaM Time-to-Event Datasets, Huei-Ling Chen, Helen Wang [ADTTE]

28. The application of SDTM in a disease (oncology)-oriented organization, Angelo Tinazzi, Alessandro Cattaneo, Enrica Paschetto, Sonia Colombini

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

32. A Proposed SDTM Implementation of Response Data for Solid Tumor Trials in Oncology, Mei Dey, Lisa Pyle [Map]

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


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

41. Tackle Oncology Dose Intensity Analysis from EDC to ADaM, Song Liu, Mijun Hu, Jieli Fang, Cindy Song, Quting Zhang

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]

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