Abstract
BackgroundAn estimand is a precise description of the treatment effect to be estimated from a trial (the question) and is distinct from the methods of statistical analysis (how the question is to be answered). The potential use of estimands to improve trial research and reporting has been underpinned by the recent publication of the ICH E9(R1) Addendum on the use of estimands in clinical trials in 2019. We set out to assess how well estimands are described in published trial protocols.MethodsWe reviewed 50 trial protocols published in October 2020 in Trials and BMJ Open. For each protocol, we determined whether the estimand for the primary outcome was explicitly stated, not stated but inferable (i.e. could be constructed from the information given), or not inferable.ResultsNone of the 50 trials explicitly described the estimand for the primary outcome, and in 74% of trials, it was impossible to infer the estimand from the information included in the protocol. The population attribute of the estimand could not be inferred in 36% of trials, the treatment condition attribute in 20%, the population-level summary measure in 34%, and the handling of intercurrent events in 60% (the strategy for handling non-adherence was not inferable in 32% of protocols, and the strategy for handling mortality was not inferable in 80% of the protocols for which it was applicable). Conversely, the outcome attribute was stated for all trials. In 28% of trials, three or more of the five estimand attributes could not be inferred.ConclusionsThe description of estimands in published trial protocols is poor, and in most trials, it is impossible to understand exactly what treatment effect is being estimated. Given the utility of estimands to improve clinical research and reporting, this urgently needs to change.
Highlights
IntroductionAn estimand is a precise description of the treatment effect to be estimated from a trial (the question) and is distinct from the methods of statistical analysis (how the question is to be answered)
An estimand is a precise description of the treatment effect to be estimated from a trial and is distinct from the methods of statistical analysis
This is not necessarily the case; some statistical methods will include all randomised participants in the analysis, but the treatment effect will only apply to a subset of participants
Summary
An estimand is a precise description of the treatment effect to be estimated from a trial (the question) and is distinct from the methods of statistical analysis (how the question is to be answered). Kahan et al Trials (2021) 22:686 data for patients who had died), and secondly, they analysed the available data using a repeated-measures mixed-model, which implicitly imputed what the missing data would have been had patients been alive and not progressed [2] While it is debatable whether there is value in knowing the effect of a new cancer treatment in the hypothetical setting where patients never die nor experience disease progression (the very thing most treatments aim to prevent), it is clear that understanding exactly what treatment effect is being estimated is essential to the proper interpretation of study results. The cabazitaxel trial above is merely an illustrative example used to highlight a widespread issue that is not unique to this particular study This lack of clarity is problematic, as even with expert statistical knowledge, it can be challenging to understand what treatment effect is being estimated (Table 1). The converse can be true, where some patients may be excluded from the analysis, and yet the estimated treatment effect still applies to the entire trial population under certain assumptions [18]
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