A Practical Guide to Applying RECIST 1.1 in Clinical Trial Data Programming
Abstract: RECIST 1.1 provides standardized rules for measuring solid tumors and assigning response categories in clinical trials. Accurate programming requires more than applying percentage cutoffs: teams must preserve lesion identity, distinguish target from non-target disease, use the correct measurement axis, compare tumor sums with the correct reference, account for new lesions, and derive time-point and best overall response according to the protocol. This tutorial translates the principal RECIST 1.1 concepts into a programming-oriented workflow and relates them to the CDISC Study Data Tabulation Model (SDTM) Tumor Identification (TU), Tumor Results (TR), and Disease Response (RS) domains. A synthetic example illustrates why progressive disease for target lesions requires both a relative increase of at least 20% from the smallest on-study sum and an absolute increase of at least 5 mm, while a qualifying new lesion may establish progression independently. The article is a narrative educational synthesis, not a systematic review, clinical study, or validation of a programming implementation. It emphasizes traceability from protocol and source assessments through standardized datasets to analysis endpoints.
Keywords: RECIST 1.1; oncology; clinical trials; SDTM; statistical programming
How to Cite?: Jyoti (Jo) Agarwal, Neetika Khurana, "A Practical Guide to Applying RECIST 1.1 in Clinical Trial Data Programming", Volume 9 Issue 2, February 2020, International Journal of Science and Research (IJSR), Pages: 1978-1980, https://www.ijsr.net/getabstract.php?paperid=SR200229112305, DOI: https://dx.doi.org/10.21275/SR200229112305