Clinical Trial Methodology Flashcards
What is meant by a clinical trial
A clinical trial is a planned experiment in humans, designed to measure the effectiveness of an intervention. The intervention is usually a new drug, but the method can equally be applied to the assessment of a surgical procedure, a vaccine, complementary therapy etc.
Describe how clinical trials differ from other types of studies
Experimental studies like trials are different from most epidemiological studies (surveys, cross sectional, cohort, case control, ecological) which are observational. In observational studies the investigator measures what happens but does not control it. For example, an investigator may record whether people smoke, and relates this to whether or not they develop lung cancer. In contrast, in a clinical trial, the investigator would allocate one group to smoking and the others to not smoking, and then see who got ill.
What happens in an ecological study
Summary estimate of two factors, compare, give starting point. Summary estimates of two factors- make inferences (useful when the data is hard to measure)
Describe the basic plan for a RCT
Planning an intervention (e.g. drug or surgery)
Define the population
o Defining the comparator (e.g. placebo, alternate treatment, standard of care).
o Defining the inclusion/exclusion criteria.
o Defining the control group – people eligible for the intervention but receive the comparator.
What do you do when looking at population based studies
Infer and observe potential causal relationships.
What are the uses of clinical trials
Is the drug better than no drug- used for assessing safety
Is the drug better than the best existing drug
What/how common are S/E?
‘Proof’ of causation?
What are the critical features in the design of a clinical trial
Objectives Patients selection Controls Study size Unbiased data collection Specific design Ethics Analysis
What do we need to define in a clinical trial
- entry criteria
- disease etc
- measures of response
- end points
How can we eliminate chance
Large sample size, larger number of events- this increases the power of the study.
What is meant by bias
A systematic error in design, conduct or analysis of a study which produces a mistaken estimate of an exposure on the risk of disease
How can we eliminate bias
Design of study- randomisation- this also eliminates confounding. Analyse whether this was done effectively when critically appraising articles.
What should you look for when assessing bias
- randomisation
- after entry- randomisation should happen before entry into the study
- investigator blind
What is particularly important to do when carrying out trials in different geographical locations
Stratify the patients into different groups, to ensure that the outcome can be generalised to all populations.
What are the advantages of randomisation
Validates statistics Excludes biased allocation Equally distributes prognostic factors? known unknown - need stratification? - restricted/block randomisation
What are the methods of minimising bias
o Blinding – single (patient not knowing), double (clinical team not knowing) and triple (statistician doesn’t know).
o Accurate end-point selection.
o Minimising loss to follow-up.
Why do we need to randomise
People who are eligible for the trial (i.e. have the condition you are interested in) are recruited, consent is obtained and then they are randomly allocated to the intervention or control
groups. Randomisation is done to remove treatment allocation bias. Without randomisation it is possible (indeed likely) that the investigator will choose different patients for each group. In
a famous early study of the BGC vaccine for TB in children, deaths from TB were five times higher in the control group than the vaccinated children.1 Further investigation showed that doctors had tended to offer the new vaccine to children whose parents were more ”cooperative”, and left the rest as controls.
These cooperative parents were likely to have been more educated, health conscious and therefore to have a lower mortality from TB regardless of the vaccination. Hence the need for randomisation in treatment allocation.
What is the importance of a control group
The control group is those study participants who do not receive the intervention under assessment. A control group must be included otherwise you cannot be sure why the outcome happened; it may be due to the new treatment or it may have happened anyway. Control groups may be given a placebo (an inactive substance such as a sugar pill, or water injection), or a standard treatment Placebo effect Regression to the mean Acclimatisation Seasonal effect
Describe regression to the mean
Any intervention at bad times will be followed by improvement, was this due to the intervention or not.
Describe controls
- are the basis of the comparison
Without them there is no reason to assume that the observed effect is due to the intervention.
What do we need to know about the sample size
Objective?
Difference to be detected (minimum important)
Significance of obs. difference = (p)
Confidence by which a-ve results is genuine = ß (1-power)
Variation of data (SD)
Are sponsors involved in conduct of the study
No, this is done by a separate academic committee.
Describe the potential sources of bias in RCTs
Sponsorship Study patient selection/allocation Prejudice of patient Prejudice of observer Faulty method Faulty analyses Faulty interpretation- any point in continuing when the results are not answering your hypothesis? If patients are dying as a result of the intervention, you need to stop?
Describe the relationship between sponsorships and RCTs
Critical requirement Data ownership Design issues Independent analyses Independent reporting
Which trials are sponsors more likely to fund
low relative risk trials