Why to Randomize a Randomized Controlled Trial? (and how to do it) - PowerPoint PPT Presentation


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Why to Randomize a Randomized Controlled Trial? (and how to do it)


Why to Randomize a Randomized Controlled Trial? (and how to do it) John Matthews University of Newcastle upon Tyne Schema of a simple trial Outline of talk Many ... – PowerPoint PPT presentation

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Title: Why to Randomize a Randomized Controlled Trial? (and how to do it)

Why to Randomize a Randomized Controlled Trial?
(and how to do it)
  • John MatthewsUniversity of Newcastle upon Tyne

Schema of a simple trial
Rx group 1
Eligible patients
Rx group 2
Outline of talk
  • Many aspects to a trial this talk focuses on
    just two
  • Why you should randomize
  • benefits of doing so
  • dangers of failing to do so
  • How to randomize
  • often glossed over unspecified

Why Randomize?
  • Compare groups at the end of the trial
  • Difference is because of the Rx
  • For this you need comparable groups
  • Purpose of randomization is to make the treatment
    groups comparable
  • Ensures that only difference in groups is due to
    trial treatments

How does it do it?
  • Each group is a random sample of eligible
    patients, so both are representative of that same
  • In this sense they are comparable
  • same proportions of males, stage IV tumours,
    ambulant cases, elderly patients etc.
  • Anything which subsequently changes the groups
    will destroy this balance.

Why Randomize?
  • Other benefits are
  • Randomization is largely unpredictable
  • Why this is a good thing and why it might not
    obtain will emerge in the talk
  • Randomization provides a valid basis for
    statistical inference
  • This is important but is not addressed at all in
    this talk

What is wrong with non-randomized studies?
  • Two main types of study, those with and those
    without concurrent control groups

Non-randomized studies II
  • Without concurrent controls
  • Uncontrolled
  • cannot really make much of such studies if there
    is any variation in outcomes.
  • Historical controls
  • type of patient may change, due to eligibility
  • environment changes, due to trial
  • data quality often quite different between groups

Non-randomized studies III
  • Non-randomized concurrent controls
  • Alternation
  • Odd/Even hospital no. or date of birth
  • First letter of surname
  • Difficult to argue that one group is different
    from another but allocation is predictable, so
    bias can arise from selection of patients see
    Keirse (1988)
  • so randomization must be unpredictable

Features of a RCT
  • Provide reliable evidence of Rx efficacy
  • Essentially simple
  • Much attendant methodology
  • ensure reliability of evidence
  • give credibility to results
  • CONSORT statements www.consort-statement.orgindic
    ate good practice in trial reporting

How to Randomize
  • Toss a coin
  • Essentially the right thing to do
  • Try not to do it in front of the patient
  • More sophisticated implementations possible

Is coin tossing OK?
  • OK for big trials
  • For small trials, such simple randomization can
    lead to imbalance in group sizes

Example trial with 30 patients
  • If 30 patients are in a trial randomized using
    coin tossing there is a 14 chance of 1515 split
  • For 1614 chance is 27
  • Worse than 2010 is 10
  • Why worse?
  • Because imbalance leads to loss of power

  • Could use a restricted randomization scheme
  • legitimate, intended to protect power
  • but often not mentioned in trial report see
    Altman Doré, 1990 Schulz et al., 1994
  • Needs to be done properly
  • Only ensures similar numbers in groups
  • Combine with stratification to ensure
    comparability for prognostic factors

Random Permuted Blocks
  • An allocation sequence is, e.g.,A,B,A,A,A,A,B,B,B
    ,Ai.e. 6 As, 4 Bs
  • This sequence built up by using a computer to
    toss a coin
  • Random Permuted Blocks (RPBs) is an alternative
    method which ensures imbalance can never be

  • All sequences of length 4 comprising 2 As and 2
    Bs are1. AABB 2. ABAB 3. ABBA4. BBAA 5.
    BABA 6. BAAB
  • Generate random sequence of numbers 1 to 6, say
    6,5,2,6, and substitute from above to give
    allocation sequence ofBAAB BABA ABAB BAAB

  • Such sequences cannot be more than two out of
  • Must be in exact balance after 4, 8, 12, etc.
    patients have been recruited
  • So RPBs are, to some extent, predictable
  • To avoid this, vary block length at random use
    blocks of length six (3t) as well as 4 (2t)

Is it enough to equalise numbers?
  • No, can still have imbalance in important
    prognostic factors
  • E.g. two groups of size 15 one comprises 14
    young children and the other comprises 14
    adolescents in a trial for diabetes
  • Stratify recruitment with respect to age
  • i.e. use separate allocation sequence within each

  • RPBs can be used without stratification
  • Stratification without using RPB (or an
    equivalent device) is nonsensical
  • Separate allocation sequence in each stratum can
    become cumbersome with many prognostic factors
  • e.g. ambulant/not, over/under 55, M/F gives 8
    allocation sequences

  • More complicated, in principle
  • ensures balance on each factor separately, not
    for all combinations
  • keeps track of patients already in trial,
    computes an imbalance score and allocates to
    minimise this
  • can include a random element
  • Less cumbersome, in practice
  • largely because you need a computer
  • Good if there are many prognostic factors

How to serve it all up
  • Methods for delivering randomisation sequences to
    the clinic are important.
  • They hold the key to ensuring adequate
    concealment of the allocation until the patient
    has been randomized.

Implementation methods
  • Need to separate the person who generates
    allocation from those who assess eligibility
  • Third party schemes
  • Telephone randomization service
  • Pharmacy randomization
  • Web-based service?
  • Envelopes
  • Serially numbered, sealed and opaque

Then what?
  • You will have two groups that are comparable and
    free from bias
  • Well, sort of
  • You have the best start, certainly
  • Drop-outs, protocol violations etc. etc. disturb
    the comparability
  • Might not have been comparable to start with!
  • Need to allow for baseline imbalance and
    stratifying variables

  • Randomization is needed in all clinical trials
  • As with most aspects of trial design, the details
    of how you randomize are important
  • The analysis needs to respect the design (esp.
    stratification) and make sensible adjustment for
  • All looking more awkward if there isnt a
    statistician involved.
  • Some details given atwww.mas.ncl.ac.uk/njnsm/tal
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