Intention-to-Treat Analyses for Randomized Controlled Trials in Hospice/Palliative Care: The Case for Analyses to be of People Exposed to the Intervention

Slavica Kochovska; Chao Huang; Miriam J Johnson; Meera R Agar; Marie T Fallon; Stein Kaasa; Jamilla A Hussain; Russell K Portenoy; Irene J Higginson; David C Currow

doi:10.1016/j.jpainsymman.2019.10.026

Intention-to-Treat Analyses for Randomized Controlled Trials in Hospice/Palliative Care: The Case for Analyses to be of People Exposed to the Intervention

J Pain Symptom Manage. 2020 Mar;59(3):637-645. doi: 10.1016/j.jpainsymman.2019.10.026. Epub 2019 Nov 9.

Authors

Affiliations

¹ IMPACCT, Faculty of Health, University of Technology Sydney, Ultimo, New South Wales, Australia.
² The University of Hull, Hull, UK.
³ The University of Hull, Hull, UK; Wolfson Palliative Care Research Centre, University of Hull, Hull, UK.
⁴ Cancer Research UK Edinburgh Centre, MRC Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK.
⁵ Institute of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim (NTNU), Trondheim, Norway.
⁶ Wolfson Palliative Care Research Centre, University of Hull, Hull, UK.
⁷ MJHS Institute for Innovation in Palliative Care, MJHS Hospice and Palliative Care, New York, New York, USA.
⁸ Cicely Saunders Institute of Palliative Care, Policy & Rehabilitation, King's College London, London, UK.
⁹ IMPACCT, Faculty of Health, University of Technology Sydney, Ultimo, New South Wales, Australia; The University of Hull, Hull, UK; Wolfson Palliative Care Research Centre, University of Hull, Hull, UK. Electronic address: david.currow@uts.edu.au.

PMID: 31707068
DOI: 10.1016/j.jpainsymman.2019.10.026

Abstract

Context: Minimizing bias in randomized controlled trials (RCTs) includes intention-to-treat analyses. Hospice/palliative care RCTs are constrained by high attrition unpredictable when consenting, including withdrawals between randomization and first exposure to the intervention. Such withdrawals may systematically bias findings away from the new intervention being evaluated if they are considered nonresponders.

Objectives: This study aimed to quantify the impact within intention-to-treat principles.

Methods: A theoretical model was developed to assess the impact of withdrawals between randomization and first exposure on study power and effect sizes. Ten reported hospice/palliative care studies had power recalculated accounting for such withdrawal.

Results: In the theoretical model, when 5% of withdrawals occurred between randomization and first exposure to the intervention, change in power was demonstrated in binary outcomes (2.0%-2.2%), continuous outcomes (0.8%-2.0%), and time-to-event outcomes (1.6%-2.0%), and odds ratios were changed by 0.06-0.17. Greater power loss was observed with larger effect sizes. Withdrawal rates were 0.9%-10% in the 10 reported RCTs, corresponding to power losses of 0.1%-2.2%. For studies with binary outcomes, withdrawal rates were 0.3%-1.2% changing odds ratios by 0.01-0.22.

Conclusion: If blinding is maintained and all interventions are available simultaneously, our model suggests that excluding data from withdrawals between randomization and first exposure to the intervention minimizes one bias. This is the safety population as defined by the International Committee on Harmonization. When planning for future trials, minimizing the time between randomization and first exposure to the intervention will minimize the problem. Power should be calculated on people who receive the intervention.

Keywords: Intention-to-treat analyses; International Committee on Harmonization; good clinical practice; imputation; missing data; palliative care; randomized controlled trials; study withdrawal.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Hospice and Palliative Care Nursing*
Hospices*
Humans
Intention to Treat Analysis*
Palliative Care
Randomized Controlled Trials as Topic*