Epidemiology: Design, Applications, Strengths & Weaknesses of Intervention Studies and Randomised Controlled Trials

Intervention studies are designed to evaluate the effect of a specific treatment or practice and are considered to provide the most reliable evidence in epidemiological research.

Intervention studies can generally be considered as either preventative or therapeutic, and types of experimental intervention are listed below:¹

• Therapeutic agents
• Prophylactic agents
• Diagnostic agents
• Surgical procedures
• Health service strategies

Therapeutic trials are designed to evaluate the effect of therapies, such as new drugs or surgical procedures. They may also be known as clinical trials, and are conducted among individuals with a particular disease to assess the effectiveness of an agent or procedure in achieving a specific outcome, such as reduced mortality.¹

Preventative trials are designed to evaluate whether an agent or procedure reduces the risk of developing a particular disease. They are carried out on individuals free from the disease at the beginning of the trial, but deemed to be at risk.¹ Preventative trials may be conducted among individuals or entire communities, and examples include evaluations of new vaccines or bed nets to prevent infection with malaria.

Characteristics of an intervention study

• The intervention being tested is allocated to a group of two or more study subjects (individuals, households, communities). 
• Subjects are followed prospectively to compare the intervention vs. the control (standard treatment, no treatment or placebo).

The main intervention study design is the randomised controlled trial (RCT).

Randomised controlled trials

The randomised controlled trial is considered as the most rigorous method of determining whether a cause-effect relationship exists between an intervention and outcome.²The strength of the RCT lies in the process of randomisation which is unique to this type of study design.

Generally, in a randomised controlled trial study participants are randomly assigned to one of two groups, the experimental group who will receive the intervention being tested, and a comparison group (controls) who receive a conventional treatment or placebo.² These groups are then followed prospectively to assess the effectiveness of the intervention compared with the standard or placebo treatment.

Subjects are randomly allocated to the two study arms so that the intervention and control groups are as similar as possible in all respects, apart from the treatment. Potential confounding factors should be equally distributed between the two groups. The choice of comparison treatments may include an existing standard treatment or a placebo. A placebo is a substance that resembles the intervention treatment in all respects except that it contains no active ingredients.

Figure 1. General outline of a two-armed randomised controlled trial.
 

Basic outline of the design of a randomised controlled trial

1. Development of a comprehensive study protocol. The study protocol will include: 
• Aim and rationale of the trial
• Definition of the hypothesis
• Background/review of published literature
• Treatment schedules, dosage, toxicity data etc.
• Proposed methodology/data collection
• Ethical considerations
• Quality assurance and safety
2. Formulation of hypothesis
3. Objectives of the trial
4. Sample size calculations
5. Define reference population
6. Choice of a comparison treatment - placebo or current available best treatment
7. Selection of intervention and control groups including; source, inclusion and exclusion criteria and methods of recruitment
8. Informed consent procedures
9. Collection of baseline measurements - include all variables considered or known to affect the outcome(s) of interest
10. Random allocation of study participants to treatment groups (standard or placebo vs. new)
11. Follow up of all treatment groups, assessment of outcomes continuously, intermittently
12. Monitor compliance and losses to follow-up
13. Interim analysis
14. Analysis - comparison of treatment groups
15. Interpretation (assess the strength of effect, alternative explanations such as sampling variation, bias)
16. Publication

The gold standard of intervention studies is the randomised, double-blind placebo-controlled trial. This attempts to reduce bias in the following ways:³

• Selection bias – reduced by allocation treatment by randomisation, so each participant has an equal chance of receiving the intervention
• Blinding – reduces measurement bias because both the investigators and the participants (hence ‘double-blind’) are unaware of the treatment allocations, so this cannot affect how they are assessed.
• Ensuring the control group is as similar to the intervention group as possible

Randomisation

The aim of randomisation is to ensure that any observed differences between the study groups are due to differences in the treatment alone and not due to the effects of confounding or bias, so the groups should be similar in all respects with the exception of the intervention under investigation.

Methods of random allocation are used to ensure that all study participants have the same chance of allocation to the treatment or control group, and that the likelihood of receiving an intervention is equal regardless of when the participant entered the study. Therefore, the probability of any participant receiving the intervention should be independent of any other participant being assigned that treatment.

The assignment of study subjects to each intervention is determined by formal chance process and cannot be predicted or influenced by the investigator or participant. In a well designed RCT, the random allocation sequence is pre-determined and cannot be influenced. It is very important that those responsible for recruiting participants into a study are unaware which study arm the individual will be allocated to. Allocation concealment avoids both conscious and unconscious selection of patients into the study, and attempts to ensure that the investigators cannot manipulate the trial by influencing which arm participants are enrolled in. Examples include concealing allocation details in sealed, opaque envelopes.

The ideal scenario would be central randomisation by telephone, where the clinician calls a randomisation service to get the treatment allocation. This allocation mechanism is beyond the control of both the investigator and the participant, limiting potential bias in allocating the treatment. The process should be carried out once the participant has been determined to be eligible for inclusion and after they have given informed consent to participate.

Methods of treatment allocation

1. Systematic allocation
   For example, participants are allocated into study groups alternately, or on alternate days. Another method would be allocation on the basis of date of birth. This is not considered to be truly random and can result in selection bias. It may be possible for the investigator to manipulate the process, if they favour one study arm over another.

2. Simple randomisation
   For example, computer generated random number tables or tossing a coin. Simple randomisation may result in different numbers of patients in each group, and is rarely used. 

3. Block randomisation
   Block randomisation is a method used to ensure that the numbers of participants assigned to each group is equally distributed and is commonly used in smaller trials. Participants are allocated in blocks of 4, for example, so it is guaranteed that 2 in each block will be randomised to each study group. With blocks of 4, there are only six possible sequences to allocate 2 to group A and 2 to group B (AABB, ABAB, BABA etc…) and blocks can be chosen at random to generate the allocation sequence. Large block sizes should be avoided, but the investigators should not know the block size, to prevent them from predicting allocation for the last few participants in each block.

4. Stratified randomisation
   Stratified randomisation is used to ensure that important baseline variables (potential confounding factors) thought to be associated with the outcome are evenly distributed between groups.² Prior to randomisation, participants are separated into different subgroups or strata based on key risk factors that may influence outcome, for example sex or age. Equal numbers are then randomly allocated to each treatment arm from within the strata. This method of treatment allocation should be based on block randomisation within each stratum, to ensure there are similar numbers of participants in each arm. However, there are a limited number of baseline variables that can be balanced by stratification because of the potential for small numbers of subjects within each stratum.

5. Minimised randomisation
   Although technically not random, this method may be used in small trials where other methods of randomisation will not result in balanced groups. The treatment allocated to the next participant being enrolled in the trial depends on the characteristics of the participants already enrolled. The aim is that important prognostic factors are distributed across the groups as equally as possible.

Once allocation is complete, the success of the randomisation process should be confirmed by comparing baseline factors between the two groups, to ensure that they are similar.

Advantages of randomisation

• Eliminates confounding - tends to create groups that are comparable for all factors that influence outcome, known, unknown or difficult to measure. Therefore, the only difference between the groups should be the intervention.
• Eliminates treatment selection bias.
• Gives validity in statistical tests based on probability theory.
• Any baseline differences that exist between study groups are attributable to chance rather than bias. Though this should still be considered as a potential concern.

Disadvantages of randomisation

• Does not guarantee comparable groups as differences in confounding variables may arise by chance.

Blinding in randomised controlled trials

Blinding is used in RCTs to ensure that there are no differences in the way the study arms are assessed or managed, thus minimising bias. Bias may be introduced, for example, if the investigator is aware which treatment a subject is receiving, as this may influence (intentionally or unintentionally) the way in which they measure or interpret the outcome data. Similarly, a subject's knowledge of treatment assignment may influence their response to a specific treatment.

Blinding also involves ensuring that the intervention and standard or placebo treatment appears the same. 

In a double-blind trial, neither the investigator nor the study participant are aware of treatment assignments. However, this design is not always feasible and a single blind RCT is where the investigator, but not the study participant, knows which treatment has been allocated.

Variations of the randomised control trial

• Crossover trials
  In crossover trial each subject acts as their own control, and receives all the treatments under investigation in sequence. Random allocation determines the sequence in which each participant receives the treatments. This type of trial may be used when the intervention does not have long-term effects.
   
  A particular advantage of a crossover trial is that the groups are as similar as possible. In crossover trials it is common to have a 'washout period' where no treatment is given between each intervention to avoid the possibility of a residual effect from the previous treatment.
   
• Factorial trials
  A factorial trial is where two or more interventions are evaluated simultaneously compared with a control group in the same trial. This type of RCT is commonly used to evaluate interactions between interventions.
   
• Community or cluster-randomised controlled trials
  Cluster randomised trials involve groups of individuals or communities, as opposed to individuals. Groups or communities are randomised to receive the intervention or standard/no treatment. This type of study design may be used to evaluate preventative health services such as smoking cessation programmes. For example all patients attending a single general practice may be allocated to receive the new programme, whilst those at another practice will receive standard care. In this sort of trial, intra-cluster correlation needs to be taken into account in assessing effect size and sample size.

Ethical issues

The use of RCTs raises important ethical issues. For example there must be sufficient doubt about the particular agent being tested to allow withholding of it from half the subjects, and at the same time there must be sufficient belief in the agent's potential to justify exposing the remaining half of all willing and eligible participants.¹ This is known as clinical equipoise.

In addition, there must be sufficient belief that the intervention under investigation is safe.

Informed consent is essential in RCT. Study subjects must understand that they are participating in an experiment and that in a placebo-controlled trial they may receive an inactive product. In addition participants must be informed of the aims, methods and potential benefits or hazards of participating in the trial.

In a controlled trial careful consideration also should be given to what intervention is given to the control group. For example, if an effective treatment already exists, participants in the control group should not receive a placebo, depriving them of this.

It is essential that study participants do not suffer as a consequence of a RCT. Most RCTs incorporate a data monitoring and safety committee who are independent of the investigators.

Analysis of RCTs

The analysis of RCT data is focused on estimating the size of the difference in predefined outcomes between the intervention groups. The main measure of effect obtained is the rate or risk ratio.

For trials of preventative interventions, the protective efficacy (or effectiveness) is calculated as:

Protective efficacy  =	R(control) - R(intervention)  x  100%	=  (1 - RR) x 100%
	R (control)

Intention to treat analysis

When RCTs are analysed using intention to treat analysis (ITT), participant’s results are analysed in the group to which they were originally assigned.⁴ This should happen regardless of whether they were lost to follow-up, or the treatment they actually received. During the RCT subjects may refuse to continue to participate and stop taking their allocated treatment.

If the investigators exclude participants from the analysis if they have not adhered to their allocated treatment strategy, the estimate of the effect of the treatment is likely to be flawed. The aim of the intention to treat analysis is to provide a pragmatic estimate of the benefit of the treatment under investigation, rather than of its potential benefit in patients who receive treatment exactly as planned. Subjects who failed to take their allocated treatment may have done so because of adverse side effects, or because they felt it was not working, and - in the real world - patients do not always take their medication as prescribed.

Additionally, there is evidence to suggest that those participants who are fully compliant with their prescribed medication do better than those who do not adhere, even after adjustment for all known prognostic factors and irrespective of assignment to active treatment or placebo.

Excluding non-compliant participants from the analysis leaves those who may be destined to have a better outcome and destroys the unbiased comparison afforded by randomisation.⁵

It should be noted that full ITT is only possible when complete outcome data are available for all randomised subjects. It cannot minimize bias introduced by losses to follow-up, where patient outcome is unknown. If investigators stop following those patients who do not adhere to the study protocol, they will be unaware if those patients experienced the target outcome.

In summary, during the statistical analysis of an RCT, all study subjects should be retained in the group to which they were originally allocated regardless of whether or not that was the treatment received.

Strengths of a randomised controlled trial

• A well designed randomised controlled trial provides the strongest epidemiological evidence of any study design about the effectiveness and safety of a given intervention.
• A RCT is considered to be the best type of epidemiological study from which to draw conclusions about causality.
• Randomisation is a powerful tool for controlling for confounding, even for factors that may be unknown or difficult to measure. If a study is designed and conducted rigorously, the possibility that an observed association is due to confounding should be minimal.
• Clear temporal sequence - exposure clearly precedes outcome.
• Provides a strong basis for statistical inference.
• Enables blinding and therefore minimizes bias.
• Can measure disease incidence and multiple outcomes.

Weaknesses of a randomised controlled trial

• Ethical constraints
• Expensive and time consuming
• Requires complex design and analysis if unit of allocation is not the individual.
• Inefficient for rare diseases or diseases with a delayed outcome.
• Generalisability - subjects in an RCT may be more willing to comply with the treatment regimen and therefore may not be representative of all individuals in a population who might be eligible for the treatment.

Examples of RCTs

One of the first randomised trials to be carried out was the evaluation of streptomycin in the treatment of tuberculosis, published in 1948. Since then, there have been numerous other examples which have had a significant impact on clinical practice.

A non-randomised study published in 1980 evaluated the possible benefit of vitamin supplementation at the time of conception in women at high risk of having a baby with a neural tube defect. The investigators found that the vitamin group subsequently had fewer babies with neural tube defects than the placebo control group. The control group included women ineligible for the trial as well as women who refused to participate. As a consequence the findings were not widely accepted, and the Medical Research Council later funded a large randomised trial to answer to the question in a way that would be widely accepted (reference below).⁶

Past paper questions
RCTs are addressed by the following MFPH Part A past paper questions:

• June 2003 – Paper IA, Question 3
• January 2005 – Paper IA, Question 2

 

References

1. Hennekens CH, Buring JE. Epidemiology in Medicine, Lippincott Williams & Wilkins, 1987.
2. Kendall JM. Designing a research project: Randomised Controlled trials and their principles,Emerg Med J. 2003, March;20(2)164-168.
3. Bailey L, Vardulaki K, Langham J, Chandramohan D. Introduction to Epidemiology. Open University Press, 2005.
4. Hollis S, Campbell F, What is meant by intention to treat analysis? Survey of publishedrandomised controlled trials. BMJ 1999; 319;670-74.
5. Montori V, Guyatt G. Intention-to-treat principle. CMAJ 2001; 165 (10)
6. Altman D, Bland M. Treatment allocation in controlled trials: why randomise? BMJ 1999;318:1209-1209

Further Resources

• Pocock SJ. Clinical Trials: A practical approach, Chichester, Wiley, 1984.
• Sibbald B, Roland M, Understanding controlled trials: Why are randomised controlled trials important?, BMJ 1998, 316:201.
• Altman DG, Randomisation. BMJ 1991;302;1481-2.

© Helen Barratt, Maria Kirwan 2009