N = 1, Cross-Over Trials and Balanced Designs - PowerPoint PPT Presentation

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N = 1, Cross-Over Trials and Balanced Designs

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Title: N = 1, Cross-Over Trials and Balanced Designs


1
N 1, Cross-Over Trials and Balanced Designs
2
N 1 Trials
  • Trials can be undertaken with just one
    participant. If the condition is a chronic
    relapsing problem the unit of randomisation can
    be the episode of treatment.
  • For example, n 1 trials have been used among
    people with rheumatoid arthritis to try out
    different pain relieving drugs.

3
Migraine Trial
  • A trial could be mounted to allocate a test
    treatment for each migraine attack.
  • Placebo or open treatment could be used.
  • Once the individual senses an attack coming on he
    contacts an independent statistician and she
    gives him the allocation.

4
Blinding of allocation
  • Important to blind allocation as the migraine
    sufferer may ask for treatment at different
    stages of the attack if he knew which allocation
    might come up.
  • Placebo might be useful but any effect including
    a placebo effect is worthwhile.

5
Example
  • Some suggestion that blood sugar falls prior a
    migraine perhaps boosting this with glucose
    tablets may limit attack?
  • Randomised to either 2 asprin or 2 asprin plus 3
    gluscose tables.
  • Outcome return to normal activity.

6
Sample Size
  • This is kept small (18 migraines) because it is
    paired data (within the individual) so variance
    is low.
  • Low significance level p 0.20 (treatment
    harmless, consequences of Type I error low, Type
    II error large).

7
Blocking?
  • Not used although one could stratify by severity,
    but due to single individual could easily lead to
    prediction of block size.
  • A simple allocation schedule used which is a
    single balanced block of 20 migraines to avoid
    prediction of last few allocations.

8
Time lines
  • Average migraine once a month so trial is
    unavoidably long (approx 2 years).
  • But dramatic effect could lead to early stopping.
  • Sadly no such occurrence.

9
Cross-over trials
  • Cross-over studies are when participants are
    randomly allocated to one treatment for a period
    of time and then cross-over to the other
    treatment for the second period of time.
  • Some HRT trials for treatment of menopausal
    symptoms have used cross over designs.

10
Advantages
  • The advantages of a cross-over trial is that is
    substantially strengthens the inference of an
    effect as essentially one is repeating the trial
    twice and because data are paired within
    individuals usually smaller sample sizes are
    needed.

11
Disadvantages
  • Cant be used in many if not most circumstances.
  • Cant cross people over from a cancer treatment
    to a placebo and vice versa.
  • Even when they are feasible there is can be a
    problem with washout or contamination if the
    drug remains in the patients system will dilute
    the effects.

12
Disadvantages (cont)
  • If there is a dramatic effect of treatment people
    may refuse to cross over to new treatment.
  • For example, an RCT of dietary exclusion of foods
    for IBS suffers versus sham diet, found a big
    effect in the first period BUT those in the
    real diet who benefited refused to cross to a
    sham diet.

13
Balanced Incomplete Block Designs
  • Trials of guidelines or educational packages may
    use an incomplete block design.

14
Avoiding Hawthorne Effects
  • One way of avoiding a Hawthorne effect is to use
    a balanced design whereby the control group
    also gets an intervention.
  • This can be done using a balanced design.

15
Example
  • A guidelines trial might look at the
    effectiveness of guidelines for Angina. Just
    giving guidelines to GPs might affect practice
    irrespective of the benefit of guidelines.
  • We can balance this possibility by giving
    guidelines say on diabetes to the control
    group.

16
Balanced Design
  • This design will balance out the Hawthorne
    effects of guidelines being given to one group
    alone.
  • Also allows the evaluation of two sets of
    guidelines for the price of one study.

17
Example
  • Verstappen et al wanted to control for the
    Hawthorne effect in a trial looking at an
    intervention for test ordering from GPs.
  • They also undertook some methodological research
    to see if the Hawthorne effect was real.

Verstappen et al. J Clin Epidemiol 2004571119
18
Design
  • GP teams randomised into 3 arms.
  • A tests feedback on test ordering for
    cardiovascular, upper and lower abdominal
    problems
  • B tests feedback on test ordering for
    pulmonary, non-organ related and joint
    complaints.
  • C minimal intervention control group.

19
Results
  • A comparison between B vs A test groups shows a
    small (not significant, p 0.29) difference. B
    vs C shows a much bigger nearly statistically
    significant difference ( p 0.07)

20
Conclusion
  • The change in test ordering was exaggerated by
    process of research compared with the actual
    intervention itself. Whilst the intervention had
    an effect this was relatively modest.

21
Summary
  • Both n of 1 trials and cross-over studies are not
    widely used. N of 1 trials can be combined with
    several individuals leading to a greater power
    and shorter study.
  • Balanced designs are useful in eliminating the
    possibility of Hawthorne effects.
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