Understanding Real Research 4 Randomised controlled trials Professor Kate O’Donnell
Jan 17, 2016
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.