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CLINICAL TRIAL
Clinical Trials
Strengths:– Best measure of causal relationship– Best design for controlling bias– Can measure multiple outcomes
Weaknesses:– High cost– Ethical issues may be a problem– Compliance
Intuition and Logic in Research
Dominant Mental ActivityIntuition
Feeling
Judgement
Experience
Analysis
Experiment
Control over variance
Hi
Potential for Misinterpretation
Qualitative
Research
Case Report
Case Series
Cross-sectional Study
Case-control Study
Cohort Study
Clinical trials
Lo
LoHi
Randomised Controlled Trial (RCT)
Strength of evidence
Anecdote
Observational
ProspectiveRetrospective
Experimental
Case series
Cohort studyCase-control study
RCT
Systematic Review
Randomised Controlled Trial (RCT)
RCT is a trial in which subjects are randomly
assigned to two groups: -the experimental group-the comparison group or Controls
Source: Cochrane Collaboration Glossary
CASP
Randomised controlled trial
population
Outcome
Outcome
group 1
group 2
new treatment
control treatment
inclusion/exclusion
Study population (participant) treatment / control
InvestigatorsAssessors Clinical intervention (medical,
surgical,hygiene) Outcome
Who is in control?
• Every experiment should have a “control group.”
• People in control group are treated exactly the same way as the other people in the experiment, except they do not get the “active treatment.”
• A “placebo group” is a special kind of control group.
RANDOMIZATION
Definition
advantage Pseudo randomization( quasi –R) disadvantage
بین افراد تصادفی تقسیم راههایگروهها
• coin• toss
• envelope• Random number table• Computer assisted
Blinding:Open
Single-blind Double blind :with placebo or active
control(double dummy)neither the researcher nor the individuals
know who received what
Triple blind
Potential benefits accruing dependent on those individuals successfully blinded
Individualspsychological More likely to comply with trial regimensLess likely to seek additional interventionsLess likely to leave trial
Trial investigators Less likely to transfer their inclinations or attitudes to participantsLess likely to differentially administer co-interventionsLess likely to differentially adjust doseLess likely to differentially withdraw participantsLess likely to differentially encourage or discourage participants to continue trial
Assessors Less likely to have biases affect their outcome assessments, especially with subjective outcomes
Ascertainment
selection BIAS
Inappropriate
handling of
withdrawals
publication
• SELECTION BIAS Inclusion & exclusion
Intervention
New drug on MS and depression
• Randomization• Allocation concealment
– if both patients and investigators could not predict the next assignment of treatment
Double blinding prevents ascertainment bias and protects randomization after allocation and during study
Allocation concealment prevents selection bias and protects randomization during selection
RCT IS NOT suitable for:
* ETIOLOGY AND CLINICAL COURSE smoking and cancer
* RARE & PROLONGED OUTCOME
ethics
• Phase 1 – 20-80– Toxic and pharmacologic effects
• Phase 2 – 100-200– Efficacy – immunity
• Phase 3– RCT– Multicenter
• Phase 4– After release
Quality of RCT
RCTs - a checklist• Good randomisation procedures• patients blind to treatment• clinicians blind to treatment• all participants followed up• all participants analysed in the groups to
which they were randomised (intention to treat)
limitations
• Loss to follow up• Contamination
– Drop out– Drop in
Effect
7525
8713
Yes No
Cure
A
B
Treatment100
100
16238 200
Total
Randomized Clinical Trials
• ARR(absolute risk reduction)• RR• OR• RRR:Efficacy= (risk in treatment-risk in
control)/risk in control• NNT(Number needed to treat)=1/ARR
Definition
• Number Needed to Treat (NNT):– Number of persons who would have to receive
an intervention for 1 to benefit.– 100/ARR (where ARR is %)– 1/ARR (where ARR is proportion)
NNTs from Controlled Trials
CER% EER% ARR% NNT
Population: hypertensive 60-year-oldsTherapy: oral diureticsOutcome: stroke over 5 years
2.9 1.9 1 100
Population: myocardial infarctionTherapy: ß-blockersOutcome: death over 2 years
9.8 7.3 2.5 40
Population: acute myocardial infarctionTherapy: streptokinase (thrombolytic)Outcome: death over 5 weeks
12 9.2 2.8 36
Cross over studies
Cross over studies
• Types:– planned
• Washout period• Sequence of treatment
– Unplanned
37
Factorial designs
• Two or more independent variables are manipulated in a single experiment
• They are referred to as factors• The major purpose of the research is to
explore their effects jointly• Factorial design produce efficient
experiments, each observation supplies information about all of the factors
38
A simple example• Investigate an education
program with a variety of variations to find out the best combination– Amount of time receiving
instruction• 1 hour per week vs. 4 hour per
week– Settings
• In-class vs. pull out• 2 X 2 factorial design
– Number of numbers tells how many factors
– Number values tell how many levels
– The result of multiplying tells how many treatment groups that we have in a factorial design
40
Main effects
• Main effect of time• Main effect of setting• Main effects on both
Friday, May 14, 2004 ISYS3015 Analytical Methods for IS ProfessionalsSchool of IT, The University of Sydney 44
A simple example• Investigate an education
program with a variety of variations to find out the best combination– Amount of time receiving
instruction• 1 hour per week vs. 4 hour per
week– Settings
• In-class vs. pull out• 2 X 2 factorial design
– Number of numbers tells how many factors
– Number values tell how many levels
– The result of multiplying tells how many treatment groups that we have in a factorial design
Friday, May 14, 2004 ISYS3015 Analytical Methods for IS ProfessionalsSchool of IT, The University of Sydney 45
Null outcome
• None of the treatment has any effect
• Main effect– is an outcome that is a
consistent difference between levels of a factor.
• Interaction effect– An interaction effect exists
when differences on one factor depend on the level you are on another factor.
Friday, May 14, 2004 ISYS3015 Analytical Methods for IS ProfessionalsSchool of IT, The University of Sydney 46
Main effects
• Main effect of time• Main effect of setting• Main effects on both
Friday, May 14, 2004ISYS3015 Analytical Methods for IS
ProfessionalsSchool of IT, The University of Sydney
47
Interaction effect
• An interaction effect exists when differences on one factor depend on the level of another factor
Friday, May 14, 2004 ISYS3015 Analytical Methods for IS ProfessionalsSchool of IT, The University of Sydney 48
Interaction effect
• Interaction as a difference in magnitude of response
• Interaction as a difference in direction of response
Before after study