Decoding Estimands in Clinical Research

Decoding Estimands in Clinical Research

Insight

Decoding Estimands in Clinical Research

Estimands are statistical tools that help define a specific research question in terms of the treatment effect to be estimated from the data collected. This insight explains their use in clinical research.

Clinical research is a systematic study to understand the effects, risks, and benefits of a medical product or procedure. Central to this evaluation are estimands, a concept recently gaining traction in the field. Estimands are statistical tools that help define a specific research question in terms of the treatment effect to be estimated from the data collected. They serve as the link between the study objectives and the statistical analysis plan.

The International Council for Harmonisation (ICH) has provided an E9 (R1) addendum to clarify the role of estimands in clinical trials. The addendum explains that an estimand describes what is to be estimated in a clinical trial and sets the stage for the design, conduct, analysis, and interpretation of the study.

An estimand is comprised of four elements:

the treatment condition

the treatment condition

what is being compared

the population

the population

who is being studied

the variable of interest

the variable of interest

what is being measured

the strategy for handling intercurrent events

the strategy for handling intercurrent events

events occurring post-randomization that might affect the interpretation of the results

The treatment condition refers to what is being compared, the population describes who is being studied, and the variable of interest describes what is being measured. Lastly, the intercurrent events refer to the events occurring post-randomization that might affect the interpretation of the results, such as use of rescue medication, disease progression, or even death. The strategy for handling these events forms a key part of defining the estimand.

For instance, suppose we are conducting a trial to assess the effect of a new drug on reducing blood pressure. Here, the treatment condition is the new drug versus placebo, the population might be adult patients with hypertension, and the variable of interest is blood pressure. If an intercurrent event such as use of rescue medication occurs, we could choose to handle it in several ways, such as considering it as treatment failure or ignoring its effect.

The application of estimands in clinical research has clear benefits. It aids in ensuring that the study objective and statistical analysis are in alignment. It also helps in handling intercurrent events and reducing biases in estimating treatment effects.

In conclusion, the use of estimands in clinical trials is crucial for the clear definition of research objectives and ensuring the validity and interpretability of results. The concept offers a comprehensive framework to align study design, conduct, and statistical analysis with the research question at hand. As the medical research community grows more familiar with estimands, they will undoubtedly become a staple of well-conducted clinical research.