TREATMENT SWITCHING: STATISTICAL AND DECISION-MAKING CHALLENGES AND APPROACHES.
OBJECTIVE
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.
School of Health and Related Research (ScHARR),University of Sheffieldn.latimer@sheffield.ac.uk.
Nicholas R
NR
Latimer
Brunel University London.
Chris
C
Henshall
UMIT - University for Health Sciences,Medical Informatics and Technology Oncotyrol - Center for Personalized Cancer Medicine Harvard T.H. Chan School of Public Health and Massachusetts General Hospital,Harvard Medical School.
Uwe
U
Siebert
School of Health and Related Research (ScHARR),University of Sheffield.
Helen
H
Bell
D003657:Decision Making; D057915:Drug Substitution; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic; D016019:Survival Analysis
Decision making; Randomized controlled trials; Statistical models; Survival analysis; Treatment crossover; Treatment switching