Randomisation is the process of assigning clinical trial participants to treatment groups such that each participation has a known (usually equal) chance of being assigned to any of the groups
- successful randomisation requires that group assignment cannot be predicted in advance
- knowledge of group allocation should be kept secure until after patient is enrolled; i.e. allocation concealment
- lack of allocation concealment may affect the decision to recruit a patient and so distort the accuracy of the study’s findings (loss of internal validity due to bias from systematic variation)
- minimises selection bias (study sampling involved selection of participants that are not representative of the study population)
- balances known and unknown prognostic factors
- allows probability theory to express the likelihood that any difference in outcome between groups (other than intervention) reflects chance
- facilitates blinding of investigators, participants and evaluators
- trials that lack randomisation introduce bias (systematic variation)
TYPES OF RANDOMISATION
There are 4 main types of randomisation, and all types of randomisation other than ‘simple’ are termed ‘restricted’
- commonest method
- each patient has an equal chance of being allocated to each group
- random numbers or computer-generated list
- may result in unequal numbers allocated to each group or unequal distribution of potential confounding factors (especially in smaller trials)
- aims to keep numbers of patient in each group approximately the same
- e.g. for every block of 8 subjects, 4 must be allocated to each treatment group
- blocks can vary in size
- risks subversion if someone discovers the block size
- pre-identified confounding factors act as criteria for separate randomisation schedules, ensuring they are equalised between the groups
- e.g. block randomisation based on center in multi-center trials; also: age, stage of disease or other potential confounders
- aims to minimise confounding and achieve baseline balance between study groups
- useful for small studies to ensure different strata are represented in the study sample
- not true randomisation, a method of equalising baseline characteristics
- only the first patient is truly randomly allocated, then allocation of subsequent patients is weighted (e.g. 0.8) to minimise imbalance of pre-selected factors at that time
- when wanting to equalise for several confounding variables
- if randomisation is unacceptable due to ethical concerns
- use of a random component is preferred
- unlike true randomisation does not have the theoretical basis for eliminating bias based on all known and unknown factors
- generally considered methodologically equivalent to true randomisation
Other rarely used types of restricted randomisation include the replacement, biased coin, and urn randomisation methods.
REPORTING OF RANDOMISATION IN PUBLICATIONS
- All trials that are not truly randomised are “non-randomised” (terms like “quasi-randomised” are unacceptable)
- method of sequence generation must be specified (e.g. random-number table or a computerised random number generator)
- If study participants are intentionally allocated to groups in different numbers:
- randomisation ratio should be reported
- For block randomisation provide details on:
- how the blocks were generated
- the block size or sizes
- whether the block size was fixed or randomly varied
- trialists becoming aware of the block size(s) (due to risk of code breaking)
- whether stratification was used, and if so:
- which factors were involved
- the categorisation cut-off values within strata
- method used for restriction
- minimisation, If used:
- variables incorporated into the scheme
- if a random element was used
REFERENCES AND LINKS
- Armitage P. The role of randomization in clinical trials. Stat Med 1982;1:345-52.
- Enas GG, Enas NH, Spradlin CT, Wilson MG, Wiltse CG. Baseline comparability in clinical trials: prevention of poststudy anxiety. Drug Information Journal 1990;24:541-8.
- Kleijnen J, Gøtzsche PC, Kunz R, Oxman AD, Chalmers I. So what’s so special about randomisation. In: Maynard A, Chalmers I, eds. Non-random reflections on health services research. BMJ Books, 1997:93-106.
- Lachin JM. Properties of simple randomization in clinical trials.Control Clin Trials 1988;9:312-26.
- Greenland S. Randomization, statistics, and causal inference.Epidemiology 1990;1:421-9.
- Schulz KF. Randomized controlled trials. Clin Obstet Gynecol 1998;41:245-56.
- Schulz KF. Subverting randomization in controlled trials. JAMA. 1995;274:1456-8.
- Treasure T, MacRae KD. Minimisation: the platinum standard for trials?. Randomisation doesn’t guarantee similarity of groups; minimisation does. BMJ. 1998;317:362-3.
FOAM and web resources
- CONSORT Statement — Randomisation and minimisation
Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also the Innovation Lead for the Australian Centre for Health Innovation at Alfred Health, a Clinical Adjunct Associate Professor at Monash University, and the Chair of the Australian and New Zealand Intensive Care Society (ANZICS) Education Committee. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.
After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.
He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE. He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of LITFL.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.
His one great achievement is being the father of two amazing children.
On Twitter, he is @precordialthump.