Statistical Consulting offer comprehensive expertise on the design and implementation of estimands in clinical trials. Using our in silico clinical trial simulation tool, KerusCloud, we can prospectively factor in different estimands for review and quantification of the impact on the probability of success of a trial.
Estimands were implemented in the ICH E9 (R1) addendum in 2019, and are a structured framework to facilitate alignment of the clinical trial objectives, design, conduct, analysis and interpretation. It also ensures transparency of the objectives from different stakeholders (e.g. regulators, payors, sponsors and patients). The ultimate goal is to make sure that clinical trials provide clearly defined information on the effects of the investigative treatments.
What are estimands?
An estimand is a description of the treatment effect associated with a clinical trial objective. There are five elements to an estimand:
- Endpoint of interest (outcome)
- Target patient population
- Treatment condition(s)
- Strategy for intercurrent events (post randomisation events)
- Population level summary measures
When to consider estimands?
Estimands should be clearly and precisely defined within the protocol. It is critical that the objectives are clearly stated at the start of the study before developing any estimands. A study can have multiple estimands related to different objectives. Estimands are mandated by the regulators for all primary and secondary objectives.
Why consider estimands?
The estimands framework brings clarity and transparency to the design and analysis of clinical trials. The choice of estimands has a clinically relevant impact on the trial results. This leads to a better understanding of the treatment effect to be estimated and hence increases the probability of success of the trial.
What are estimands?
An estimand is a description of the treatment effect associated with a clinical trial objective. There are five elements to an estimand:
- Endpoint of interest (outcome)
- Target patient population
- Treatment condition(s)
- Strategy for intercurrent events (post randomisation events)
- Population level summary measures
When to consider estimands?
Estimands should be clearly and precisely defined within the protocol. It is critical that the objectives are clearly stated at the start of the study before developing any estimands. A study can have multiple estimands related to different objectives. Estimands are mandated by the regulators for all primary and secondary objectives.
Why consider estimands?
The estimands framework brings clarity and transparency to the design and analysis of clinical trials. The choice of estimands has a clinically relevant impact on the trial results. This leads to a better understanding of the treatment effect to be estimated and hence increases the probability of success of the trial.
Common questions around the use of estimands addressed by our Statistical Consulting and Data Science teams include:
So, if you:
- have a regulatory study and are unsure how to implement the estimands framework
- are new to estimands and would like support in how to incorporate this into your study protocol and analysis plans
- are concerned about missing data and approaches to deal with this in the design and analysis of your trial
- would like support choosing between different estimands strategies
…our teams can help. Book a consultation to find out more about our expertise in Estimands.
