Understanding Real Research 4

Randomised controlled trials

Professor Kate O’Donnell

What can studies do?

Describe the situation: Descriptive.

Explain the situation: Analytical.

Compare approaches: Experimental.

Study designs

Descriptive

Cross-sectional, longitudinal.

Analytic

Case-control studies.

Cohort studies.

Quasi-experimental

Natural experiments, policy interventions.

Experimental

Randomised controlled trial.

Type of Study Descriptive Analytical Experimental

Case study Yes No No

Case series Yes No No

Cross-sectional Yes Yes No

Case-control Yes Yes No

Cohort Yes Yes No

Natural experiment Yes Yes Quasi

Randomised control trial Yes Yes Yes

Study designs

Prevalence Cross-sectional

Cause/

Aetiology

Cross-sectional;

Case-control;Cohort.

Prognosis Cohort.

Harm Case-control;Cohort.

Effectiveness Randomised controlled trial.

Randomised controlled trials

A clinical trial in which:

• at least two treatments, programmes, interventions are compared.

• one of these is a control group.

• allocation uses a random, unbiased method.

Population

Group 1

Group 2

Outcome

Outcome

New treatment

Control treatmentFrom: Critical Appraisal Skills Programme (CASP), Oxford.

Randomised controlled trials

Explanatory trials

Measure efficacy:

the benefit a treatment produces under ideal conditions.

e.g. Phase III drug trials.

Pragmatic trials

Measure effectiveness:

the benefit a treatment produces in routine clinical

practice.

Aim to inform choices between treatments.

Patients should be analysed in the group to which they were initially randomised, i.e. intention to treat analysis.

Intention to treat analysis

All patients allocated to one arm of a RCT are analysed in that arm, whether or not they completed the prescribed treatment/regimen.

Two by two table

Outcome event Total

Yes No

Experimental group

a b a + b

Control group c d c + d

Total a + c b + d a + b +c + d

Appraising RCTsMethodological approach:

Was assignment to the different groups randomised?

Was the randomisation process/list concealed?

Was everyone who entered the trial accounted for at the end?

Were subjects and assessors “blind” to treatment allocation when assessing outcomes?

Were groups similar at start of trial and treated similarly throughout the study?

Statistical reporting:

Were subjects analysed in the group to which they were randomised: intention to treat analysis.

Type of data – influences statistical analysis.

Reporting of risk: RRR vs ARR.

Appraising RCTs

Risk & Odds

When talking about the chance of something happening, e.g. death, hip fracture, we can talk about:

• risk and relative risk

or

• odds and odds ratio.

Risks and odds

Risks and odds

Risks

A proportion.

Numerator / Denominator.

Odds

A ratio.

Numerator / (Denominator - Numerator).

Two by two table

Outcome event Total

Yes No

Experimental group

a b a + b

Control group c d c + d

Total a + c b + d a + b +c + d

Risk

Risk is: a proportion.

Risk of event in expt. group = a = EER. a+b

Risk of event in control group = c = CER. c+d

Relative risk

Relative risk (RR) is: a ratio of proportions.

RR = EER CER.

A measure of the chance of the event occurring in the experimental group relative to it occurring in the control group.

Relative risk - 2

RR <1 if group represented in the numerator is at lower “risk” of the event.

Want this if the event is a bad outcome e.g. death.

RR >1 if group represented in numerator is at greater “risk” of the event.

Want this if the event is a good outcome e.g. smoking cessation.

Relative risk reduction

The amount by which the risk of the event is reduced by the intervention.

The difference in the risk of the event between the control and experimental groups, relative to the control group.

RRR = (CER - EER)/CER.

Use this term if the event is bad e.g. death.

Relative risk reduction - 2

An alternative way of calculating the relative risk reduction is to use the relative risk:

RRR = (1 - RR).

Use this term if the event is bad e.g. death.

Absolute risk reduction

The absolute difference between the risk of the event in the control and experimental groups.

ARR = CER - EER.

ARR can be used to calculate the number needed to treat (NNT).

Use this term if the event is bad e.g. death.

Relative benefit increase

The amount by which the risk of the event is increased by the intervention.

The difference in the risk of the event between the control and experimental groups, relative to the control group.

RBI = (CER - EER)/CER.

Use this term if the event is good e.g. smoking cessation.

Relative benefit increase - 2

An alternative way of calculating the relative benefit increase is to use the relative risk:

RBI = (1 - RR).

Use this term if the event is good e.g. smoking cessation.

Absolute benefit increase

The absolute difference between the risk of the event in the control and experimental groups.

ABI = CER - EER.

ABI can be used to calculate the number needed to treat (NNT).

Use this term if the event is good e.g. smoking cessation.

Number needed to treat

The number of patients who needed to be treated to prevent the occurrence of one adverse event (e.g. complication, death) or promote the occurrence of one beneficial event (e.g. cessation of smoking).

NNT = 1/ARR.

Odds

Odds is: a ratio.

Odds of event in expt. group = a b

Odds of event in control group = c d

Odds ration (OR) is: a ratio of ratios.

OR = ad bc.

Odds ratio

Confidence interval

The range of values within which the “true” value in the population is found.

95% CI: can be 95% confident the population value lies within those limits.

Is an estimate of the “true” value.

Confidence interval - 2

95% CI = Sample estimate +/- 1.96 x SE

The bigger the sample - the smaller the sample error (SE).

Bigger samples smaller CIs.

more precise estimate of the “true”

population value.