Development↦Statistic Methodology↦Statistics in the Protocol↦Data-Analysis-Set
What is it? Why is it important?
A Data-Analysis-Set defines which study participants to include in an analysis.
Commonly used Data-Analysis-Sets are the:
- Full-Analysis-Set (FAS): Includes all randomized study participants, regardless of protocol adherence or deviations
- Per-Protocol-Set (PPS): Includes only participants who did strictly adhere to a predefined set of protocol requirements (i.e. as defined by the SP-INV)
The FAS aims at an Intention-To-Treat (ITT) analysis. It includes all randomly assigned participants (e.g. intervention and control group) irrespective whether they completed or received any treatment. The aim is to provide a conservative estimate of (a) treatment effect(s), while maintaining the randomized nature of the study.
The PPS aims at an efficacy analysis. It assesses the performance of an intervention among participants who did closely follow the study protocol. While a PPS analysis can provide valuable insights into the performance of an intervention, one should keep in mind that analysis results may be biased.
More
Biased results
In a Randomized Controlled Trial (RCT), the random allocation of participants to different treatment groups ensures that the two groups are comparable. When selecting a subset of randomized participants for the analysis, similarities between treatment groups can no longer be guaranteed. As a consequence a bias may occur.
Example: In an active treatment vs. placebo study, all participants with an early treatment discontinuation are removed from the PPS. This may lead to the exclusion of participants with severe side effects in the active treatment group. Consequently, the intervention group may look better than it actually is.
What do I need to do?
As a SP-INV, define applicable analysis-set(s) for you study.
- FAS: As all study participants are included its definition is usually straight forward
- PPS: Only include participants who:
- Strictly adhere to a predefined set of protocol requirements (e.g. completion of all study visits, compliance with administration of interventional product – daily intake of study drug)
- Have no major protocol deviations. Define events considered as major protocol deviations (e.g. not meeting specific eligibility criteria, not completed study visits, or visits done outside the allowed timeframe, specified missing data, non-compliance with study treatment
- Document criteria used to define Data-Analysis-Sets in the study protocol and, as applicable, in the Statistical Analysis Plan (SAP).
As required, alternative analysis-sets can be defined.
Example: A safety-analysis-set includes all participants who received at least one dose of the study drug. This allows a close monitoring and analysis of safety-related outcomes (e.g. occurrence of adverse events, laboratory abnormalities).
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
References
ICH Topic E9 – see in particular
- 5.2.1 Full analysis set
- 5.2.2 Per protocol set