Journal
INTERNATIONAL JOURNAL OF TECHNOLOGY ASSESSMENT IN HEALTH CARE
Volume 32, Issue 3, Pages 160-166Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S026646231600026X
Keywords
Decision making; Statistical models; Survival analysis; Randomized controlled trials; Treatment switching; Treatment crossover
Categories
Funding
- Bellberry
- Amgen
- AstraZeneca
- Janssen
- Merck Sharpe and Dohme
- Pfizer
- Roche
- National Institute for Health Research [DRF-2009-02-82] Funding Source: researchfish
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Objectives: Treatment switching refers to the situation in a randomized controlled trial where patients switch from their randomly assigned treatment onto an alternative. Often, switching is from the control group onto the experimental treatment. In this instance, a standard intention-to-treat analysis does not identify the true comparative effectiveness of the treatments under investigation. We aim to describe statistical methods for adjusting for treatment switching in a comprehensible way for nonstatisticians, and to summarize views on these methods expressed by stakeholders at the 2014 Adelaide International Workshop on Treatment Switching in Clinical Trials. Methods: We describe three statistical methods used to adjust for treatment switching: marginal structural models, two-stage adjustment, and rank preserving structural failure time models. We draw upon discussion heard at the Adelaide International Workshop to explore the views of stakeholders on the acceptability of these methods. Results: Stakeholders noted that adjustment methods are based on assumptions, the validity of which may often be questionable. There was disagreement on the acceptability of adjustment methods, but consensus that when these are used, they should be justified rigorously. The utility of adjustment methods depends upon the decision being made and the processes used by the decision-maker. Conclusions: Treatment switching makes estimating the true comparative effect of a new treatment challenging. However, many decision-makers have reservations with adjustment methods. These, and how they affect the utility of adjustment methods, require further exploration. Further technical work is required to develop adjustment methods to meet real world needs, to enhance their acceptability to decision-makers.
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