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Updated: Sep 26, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Missing data in palliative care research: estimands and estimators
Jessica Roydhouse1,2, Lysbeth Floden3, Sabine Braat4
1University of Tasmania Menzies Institute for Medical Research, Hobart, Tasmania, Australia jessica.roydhouse@utas.edu.au.
Abstract:
There are several methodological challenges when conducting randomised controlled trials in palliative care. These include worsening function and high mortality, leading to treatment discontinuation, some of which will be unrelated to the intervention being evaluated.Recently, a new framework for handling postrandomisation events, such as attrition, has been released. This framework aims to align trial objectives, design, conduct and analysis by clarifying what and how to estimate treatment effects in the presence of data affected by postrandomisation events.The purpose of this paper is to introduce palliative care researchers to this framework and how it can guide trial design, and efficacy and safety analysis in a palliative care context where individual withdrawal from the trial is common.In this paper, we describe the estimand framework and the background for it. We also consider postrandomisation events that are frequently encountered in palliative care trials and how these might affect objectives of interest. We then construct efficacy and safety estimands for a trial in palliative care. Better trial design and alignment of objectives with analysis can improve our understanding of what treatments do and do not work in palliative care.
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