Treatment estimands in clinical trials of patients hospitalised for COVID-19: ensuring trials ask the right questions
- PDF / 443,797 Bytes
- 8 Pages / 595.276 x 790.866 pts Page_size
- 102 Downloads / 162 Views
OPINION
Open Access
Treatment estimands in clinical trials of patients hospitalised for COVID-19: ensuring trials ask the right questions Brennan C. Kahan1*, Tim P. Morris1, Ian R. White1, Conor D. Tweed1, Suzie Cro2, Darren Dahly3,4, Tra My Pham1, Hanif Esmail1,5, Abdel Babiker1 and James R. Carpenter1
Abstract When designing a clinical trial, explicitly defining the treatment estimands of interest (that which is to be estimated) can help to clarify trial objectives and ensure the questions being addressed by the trial are clinically meaningful. There are several challenges when defining estimands. Here, we discuss a number of these in the context of trials of treatments for patients hospitalised with COVID-19 and make suggestions for how estimands should be defined for key outcomes. We suggest that treatment effects should usually be measured as differences in proportions (or risk or odds ratios) for outcomes such as death and requirement for ventilation, and differences in means for outcomes such as the number of days ventilated. We further recommend that truncation due to death should be handled differently depending on whether a patient- or resource-focused perspective is taken; for the former, a composite approach should be used, while for the latter, a while-alive approach is preferred. Finally, we suggest that discontinuation of randomised treatment should be handled from a treatment policy perspective, where nonadherence is ignored in the analysis (i.e. intention to treat). Keywords: COVID-19, Estimand, Randomised trial, Intercurrent events, Truncation-by-death
Background As of 8 July 2020, over 1600 clinical trials have been registered to evaluate different treatment options for coronavirus disease (COVID-19) [1, 2]. Evidence appraisal and synthesis to identify which treatments are best will require that trials address meaningful questions (for instance, by measuring clinically relevant outcomes) and that results can be meaningfully compared across trials (for instance, by standardisation of outcomes across trials). Core outcome sets have identified all-cause mortality and respiratory support as the key outcomes to be measured in trials of in-hospital treatments for COVID19 [3, 4]. Hospital resource outcomes, such as length of
* Correspondence: [email protected] 1 MRC Clinical Trials Unit at UCL, London, UK Full list of author information is available at the end of the article
stay, time in intensive care units (ICUs), and time on ventilators, have also been recommended [5–7]. However, to ensure that trials address meaningful questions, and to facilitate comparisons across trials, it is also necessary to define the estimand of interest. An estimand is a precise definition of the treatment effect to be estimated [8]; careful consideration of the estimand can help to ensure that research objectives are clearly stated, address a clinically meaningful question, and are aligned with the study procedures, including trial design, data to be collected, and planned statistical analysis.
Main text There are
Data Loading...
