Question 6

College answer

a) Allocation concealment                                         
Procedure for protecting the randomization process and ensuring that the clinical investigators and those involved in the conduct of the trial are not aware of the group to which the subject has been allocated 
 
b) Block randomisation  
Simple randomisation may result in unequal treatment group sizes; block randomisation is a method that may protect against this problem and is particularly useful in small trials. 
 
In the context of a trial evaluating drug A or drug B and with block sizes of 4, there are 6 possible blocks of randomisation: AABB, ABAB, ABBA, BAAB, BABA, BBAA.  
 
One of the 6 possible blocks is selected randomly, and the next 4 study participants is assigned according to the order of the block.  The process is then repeated as needed to achieve the necessary sample size.  
  
c) Stratification                                              
Stratification is a process that protects against imbalance in prognostic factors/confounders that are present at the time of randomisation.   
A separate randomisation list is generated for each prognostic subgroup.  Usually limited to 2-3 variables because of increasing complexity with more variables.  
  
d) Minimisation algorithm                                         
This is an alternative to stratification for maintaining balance in several prognostic variables.  
The minimisation algorithm maintains a running total of the prognostic variables in patients that have already been randomised and then subsequent patients are assigned using a weighting system that minimizes imbalance in those prognostic variables.  

Discussion

This question is virtually identical to Question 19 from the first paper of 2019, where the trainees were expected to explain these terms rather than offer a rationale for them. The college answer to both questions is identical, suggesting that the examiners do not see any distinction in their wording (or, that they are indifferent to the candidates' interpretation of the question). Either way, for whatever reason the first time around this SAQ did very poorly (only one candidate passed, and barely at that), whereas this time it seems 49.3% scored over 5.0, and some EBM genius scored 8.5.

 Without further ado:

Allocation concealment:

• This is a technique of preventing selection bias.
• The selection of patients is randomised, and nobody knows what treatment the next enrolled patient will receive.
• A truly random sequence of allocations prevents the investigators from being able to predict the allocated treatment on the basis of previously allocated treatments.
• Allocation concealment prevents the investigators from predicting who is getting what treatment before the patient is enrolled, whereas blinding prevents the investigators from knowing who is getting what treatment after the patient is enrolled.

Block randomisation:

• The arrangement of experimental subjects in blocks, designed to keep the group numbers the same.
• Usually, the block size is a multiple of the number of treatments (i.e. if it is a binary Drug A vs Drug B trial, the blocks would be in multiples of two).
• Small blocks are better than large blocks.
• The example offered by the college answer is the same example used by Bland and Altman in their classical 1999 article, "How to randomise".  That example now, verbatim:

• "...sometimes we want to keep the numbers in each group very close at all times. Block randomisation (also called restricted randomisation) is used for this purpose. For example, if we consider subjects in blocks of four at a time there are only six ways in which two get A and two get B: 1:AABB 2:ABAB 3:ABBA 4:BBAA 5:BABA 6:BAAB.  We choose blocks at random to create the allocation sequence. Using the single digits of the previous random sequence and omitting numbers outside the range 1 to 6 we get 5623665611. From these we can construct the block allocation sequence BABA/BAAB/ABAB/ABBA/BAAB, and so on. The numbers in the two groups at any time can never differ by more than half the block length. Block size is normally a multiple of the number of treatments."

Stratification:

• Stratification is the partitioning of subjects and results by a factor other than the treatment given.
• Stratification ensures that pre-identified confounding factors are equally distributed, to achieve balance. The objective is to remove "nuisance variables", eg. the presence of neutropenic bone marrow transplant recipients in a trial performed on septic patients. One would want to ensure that the treatment group and the placebo group had equal numbers of these haematology disasters.

Minimisation algorithm:

• Minimisation is a method of adaptive stratified sampling.
• The objective is to minimise the imbalance between groups of patients in a clinical trial by ensuring that the treatment group and placebo group each get an equal number of patients with some sort of predetermined characteristics which might act as confounding factors.
• The minimisation algorithm carefully places patients in groups according to the pre-identified confounding factors. Only the first patient is randomly allocated.
• Minimisation is methodologically equivalent to true randomisation but does not correct for unknown confounders (only the  known pre-determined ones)