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Stats in Medicine

Crossover Trials
Crossover trial is a clinical trial in which each individual consecutively receives each of the
treatments under study. Thus, in a crossover design, each participant is randomized to a
sequence of two or more treatments therefore the participant is used as his or her own control.
Crossover trials produce within participant comparisons, whereas parallel designs produce
between participant comparisons. For example, in the simplest case, participants are
randomised to receive either intervention A followed by intervention B or randomised to
intervention B followed by intervention A. This design is called a two-period crossover design.
In other words, this approach randomly assigns participants to one group, who then “crossover”
to another treatment arm during the course of the trial. This means that even if they are initially
put into a placebo group, they will also eventually receive the study drug or standard of care
during the trial. Often, a washout period is used to ensure data integrity. The washout period is
defined as the rest period between two treatment periods for which the effect of one treatment
administered at one dosing period does not carry over to the next. In a crossover design the
washout period must be long enough for the treatment effect to wear off so that there is no
carryover effect from one treatment period to the next. This period reduces carryover effects
from the previous treatments and helps researchers determine whether the outcome of the study
is due to the effects of the study drug.
In a simple crossover trial, involving 2 treatments (A and B), 2 periods, random assignment of
subjects to AB or BA is represented in the figure below.
Crossover trials can be used to investigate chronic conditions, such as asthma, where the
objective is to investigate the participants’ short term response to therapy. The condition must
also be stable, so that the circumstances at the beginning of each period are more likely to be
the same. Clearly, not all interventions can be studied in crossover designs. For example,
comparing surgical procedures or evaluating long term outcomes such as 5-year survival where
it is impossible to crossover to another intervention.
Basically a crossover design has the following advantages:
1. It allows a within-patient comparison between treatments, since each patient serves as
his or her own control.
2. It removes the interpatient variability from the comparison between treatments.
3. With a proper randomization of patients to the treatment sequences, it provides the best
unbiased estimates for the differences between treatments.
Illustrative example: Forty-nine participants were randomised to follow either a margarine or
butter diet for six weeks. At the end of his period, participants were crossed over to the other
intervention for six weeks. Outcomes were measured every four days throughout the study.
Cluster Randomised Trials
A cluster randomised trial is a study design which randomises groups of participants to each
arm of a study rather than individuals. This is done when it would be difficult give a new
treatment to an individual within a community or social group without it affecting the outcome
in the standard care arm of the study.
For example, if individuals from the same village were recruited to trial a new vaccine in a
study using individual randomisation, vaccinated individuals would not be susceptible to the
disease it prevents. Thus leaving a smaller proportion of unvaccinated individuals susceptible
to the disease and possibly affecting transmission rates and reduce overall incidence of the
disease within both groups. This would distort the study findings and not give a true picture of
vaccine efficacy. However, if the unit of randomisation was the whole village and other villages
were also recruited, villages would be randomised to the vaccine arm or standard care arm.
This would allow for an analysis between arms which would more closely indicate the true
efficacy of the vaccine.
Illustrative example: Populations served by single health centres were randomised to receive
improved services for the treatment of sexually transmitted diseases.
Illustrative example: Families were randomised to evaluate the effectiveness of treated nasal
tissues versus placebo tissues upon the incidence of respiratory illness.
Factorial Trials
Factorial clinical trials test the effect of two or more treatments simultaneously using various
combinations of the treatments. The simplest factorial design is known as a 2x2 factorial
design, whereby participants are randomly allocated to one of four combinations of two
interventions (A and B). These combinations are A alone, B alone, both A and B; neither A
nor B (control). This design allows the investigators to compare the experimental interventions
with the control, compare the experimental interventions with each other, and investigate
possible interactions between them. That is, comparison of the sum of the effects of A and B
given separately with the effects of the combination.
If there is no interaction between the interventions, the factorial design will have greater
statistical power than a traditional multiple arm trial. This implies that two interventions can
be studied in the same trial without increasing the required number of participants. The
downside is that it is often very difficult to guarantee that no interaction took place and so
results can be difficult to interpret.
Illustrative example: Patients were randomised to one of 4 groups – intravenous reptokinase,
oral aspirin, both or neither – and mortality was measured.
Pocock, S. J. (2013). Clinical trials: a practical approach. John Wiley & Sons.
Kerry, S. M., & Bland, J. M. (1998). Analysis of a trial randomised in clusters. Bmj, 316(7124),
Sibbald, B., & Roberts, C. (1998). Understanding controlled trials Crossover trials. Bmj,
316(7146), 1719-1720.
Senn, S. S., & Senn, S. (2002). Cross-over trials in clinical research (Vol. 5). John Wiley &
Chow, S. C., & Liu, J. P. (2008). Design and analysis of clinical trials: concepts and
methodologies (Vol. 507). John Wiley & Sons.