Full Analysis Set (FAS)

Example(s):
- a set of "all patients randomly assigned to a treatment group having at least one efficacy assessment after randomisation". (In: IMUTI, 2012)
- …
Counter-Example(s):
- Per Protocol Analysis Set,
- Safety Analysis Set,
See: Intention-To-Treat (ITT) Analysis, Per-Protocol (PP) Analysis, Randomized Controlled Clinical Trial, Clinical Dataset, Clinical Trial Data Management System, Clinical Trial Design, Clinical Trial Data Analysis, Clinical Trial Randomization, Clinical Safety, Clinical Tolerability, Superiority Clinical Trial, Equivalency Clinical Trial, Non-Inferiority Clinical Trial.

References

(Wikipedia, 2022) ⇒ https://en.wikipedia.org/wiki/Glossary_of_clinical_research#F Retrieved: 2022-01-02.
- Full analysis set
  - The set of subjects that is as close as possible to the ideal implied by the intention-to- treat principle. It is derived from the set of all randomised subjects by minimal and justified elimination of subjects. (ICH E9)

(Gupta, 2011) ⇒ Sandeep K. Gupta (2011). "Intention-To-Treat Concept: A Review". In: ISCR - Perspectives in Clinical Research, 2(3). DOI:10.4103/2229-3485.83221.
- QUOTE: The International Conference on Harmonisation (ICH) E9 guideline on “Statistical Principles for Clinical Trials” uses the term “full analysis set” to describe the analysis set which is as complete as possible and as close as possible to the ITT ideal of including all randomized subjects (...)
  CPMP guideline states that in a noninferiority trial, the full analysis set based on the ITT principle and the PP analysis set have equal importance and their use should lead to similar conclusions for a robust interpretation.

(EMA, 1998) ⇒ European Medicines Agency (1998). "ICH Topic E 9 Statistical Principles for Clinical Trials". In: Note For Guidance On Statistical Principles For Clinical Trials (CPMP/ICH/363/96).
- QUOTE: In this document the term 'full analysis set' is used to describe the analysis set which is as complete as possible and as close as possible to the intention-to-treat ideal of including all randomised subjects. Preservation of the initial randomisation in analysis is important in preventing bias and in providing a secure foundation for statistical tests. In many clinical trials the use of the full analysis set provides a conservative strategy. Under many circumstances it may also provide estimates of treatment effects which are more likely to mirror those observed in subsequent practice.