Randomised Controlled Studies Flashcards

1
Q

What is a clinical trial

A

A clinical trial is an experiment in which a treatment is administered to humans in order to evaluate its efficacy and safety

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2
Q

What are the types of clinical trial

A
  • An uncontrolled trial
  • A controlled trial
  • A randomised controlled trial
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3
Q

What happens in an uncontrolled trial

A

– Everyone gets the treatment – used that so all participants without the treatment in the trial will die in a few months

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4
Q

What happens in a controlled trial

A

– A treated group is compared with an untreated group (placebo)
– Or a treated group is compared with a control group having “usual treatment”
– Controls may be geographical, historical, or randomised;

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5
Q

How is allocation determined in a randomised trial

A

– Allocation to groups is determined by chance

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6
Q

What is a geographical control and what is it subjected to

A
  • Patients with the same disorder seen at another hospital or clinic where the new intervention is not provided
  • Selection bias – patients might be more likely to die in that area anyway not necessarily due to the treatment or lack of treatment
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7
Q

What is a hospital control and what is it subjected to

A
  • Patients with the same disorder seen in the past before the use of the new intervention
  • Similar problem as with geographical controls (selection bias)
  • More biased to therapy being better
  • Can be used if outcome of standard treatment (or no treatment) are well known and vary little for a given patient population
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8
Q

What are the two types of controls

A

Geographical control

Hospital control

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9
Q

What is an allocation bias

A

Allocation bias can be defined as bias that arises from a systematic difference in how participants are assigned to treatment groups and comparison groups in a clinical trial
e.g. allocation bias may result if investigators know or predict which intervention the next eligible participant is supposed to get

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10
Q

What is a selection bias

A

Selection bias is the bias introduced by the selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed

e.g. Examples of sampling bias include self-selection, pre-screening of trial participants, discounting trial subjects/tests that did not run to completion and migration bias by excluding subjects who have recently moved into or out of the study area

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11
Q

Why can you not use alternative allocation in a randomized control study

A

You cannot do alternate allocation as the clinicians and patients can predict the treatment to be received therefore it is not random

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12
Q

How was the first trial randomised

A

Patients randomly allocated to receive streptomycin or bed rest
each centre allotted a numbered series of envelopes, each containing a card indicating ‘S’ or ‘C’. Numerical order of envelopes based on a series of random numbers. When patient approved for trial the next envelope was opened

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13
Q

What are the benefits of randomised control studies

A
  • Proper randomisation helps ensure group receiving treatment A is similar to group receiving treatment B
  • Avoids selection/allocation bias
  • The only systematic difference between treatment and control groups is the treatment (hopefully (doesn’t guarantee it))
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14
Q

what do patients have need to be before randomised

A

Patients need to have been deemed eligible and meet the inclusion criteria and consented to participate for a randomised control study

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15
Q

What are the two different types of blinding

A

single blind

double blind

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16
Q

What is a single blind trial

A

Single blind – patients do not know what treatment they are on but researchers do

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17
Q

What is a double blind trial

A

Double blind – also the observers do not know what treatment the patients are on (not always possible)and the patients do not know what treatment they are on

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18
Q

What does blinding ensure

A

• Ensures use of other potential treatments/ assessment of outcome/decision to withdraw patient not influenced by clinician’s or patient’s knowledge of treatment

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19
Q

What are the two different types of randomised controlled trials

A
  • Parallel groups

- Crossover

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20
Q

describe the parallel group type of the randomised controlled trials

A

randomise participants into group A and group B

- give them the different treatments and then follow them up and record the outcome

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21
Q

describe the crossover types of randomised controlled trials

A
  • Patients are randomised into two groups, group A and Group b
  • they are given the first treatment and then the outcome is recorded
  • then they are swapped and given the different treatment and then the outcome is reordered
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22
Q

when is the parallel type of randomised controlled trials used

A

Parallel group – when effect of treatment is not reversible

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23
Q

When is the crossover type of the randomized controlled trials used

A
  • Cross-over – when effect of treatment is reversible
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24
Q

What are the advantages and disadvantages of the cross over trials

A

Advantages

  • Each patient is their own control
  • Smaller sample size to get same number of observations
  • Better for subjective measurements

Disadvantages

  • More time consuming
  • Carry-over effects – carry over effect of one treatment into other treatment period - therefore there should be a time period for example a month when the patient does not receive any treatment so it doesn’t carry over to the next treatment phase
25
Q

What is cluster randomised trial

A
  • Don’t randomise individual but randomise pre-existing groups to one or two treatments these could be villages schools, general practises
26
Q

What is the positives of cluster randomised trials

A
  • Avoid contamination (all participants in the trial are affected by the intervention even if only some receive it)
  • Enhances compliance
27
Q

Give an example of cluster randomised trial

A
  • Cancer screening trials often done as this

- May need widespread publicity and women allocated to control might hear about the screening and demand it

28
Q

What are factorial trials

A
  • Assess 2 interventions using the same number of patients as 1 intervention
  • Usually little or no interaction between the two interventions
  • To assess 2 drugs using the same number of patients as 1 drug
29
Q

describe the phases in developing and evaluating a new drug

A

• PRECLINICAL – Non-human study
– In vitro and in vivo animal experiments to obtain preliminary efficacy, toxicity and pharmacokinetic information

• PHASE 0 – First in-human trials (not always done)
– Small number of subjects given subtherapeutic dose of drug to determine pharmacodynamics and pharmacokinetics

• PHASE 1 – Screening for safety
– Testing of drug on (usually) healthy volunteers for dose ranging.
– Determine whether the drug is safe to check for efficacy

• PHASE 2 – Assess efficacy and safety
– To determine whether drug can have a therapeutic effect
– May be designed as case series or randomised controlled trial

• PHASE 3 – Assess efficacy and safety
– Randomised controlled trial on large number of patients to determine what the therapeutic effect is

• PHASE 4 – Post-marketing surveillance
– Safety surveillance (pharmacovigilance

30
Q

How long can a clinical study last

A

Preclinical to phase 4 can take 12-18 years

31
Q

Why do all studies need to be registered

A

• All trials must be registered prospectively
– Journals will not consider trials for publication unless they are registered with one of the primary registries in the WHO network or the United States’ clinicaltrials.gov

32
Q

What are some of the registries in the WHO that clinical studies can register with

A

– International Standard Randomised Controlled Trial Number (ISRCTN)
– European Union Clinical Trials Register (EU-CTR)
– Australian New Zealand Clinical Trials Registry

33
Q

What are the advantages of using registers for clinical trials

A
  • Assist in the planning of new trials
  • Avoid unnecessary duplication of research
  • Avoid subjecting patients to trials seeking evidence that is already available
  • Encourage collaboration between research groups
  • Facilitate optimal use of research funds by funding agencies
  • Facilitate patients’ access to information and improve recruitment
  • Improve opportunities for methodological research
  • Reduce discrepancies between published results and original trial protocol
  • Help to detect publication bias in meta-analyses
34
Q

how do you work out the death in treatment group and risk of death in the control group

A

Risk of death in the treatment group = number of deaths in the treatment group/Number of patients in treatment group

Risk of death in control group = number of deaths in the control group/number of patients in control group

35
Q

What is the relative risk of death in the treatment group compared to the control group

A

Relative risk of death = risk of death in treatment group/Risk of death in control group

36
Q

if the treatment as to effect what is the relative risk

A

relative risk is 1

37
Q

Define intention to treat

A

Comparison of all subjects based on the treatment group assigned, regardless of whether they complied

38
Q

Define on treatment

A

Comparison of subjects who actually took treatment

39
Q

What is the difference between intention to treat and on treatment

A

• “Intention-to-treat”
Comparison of all subjects based on the treatment group assigned, regardless of whether they complied

• “On-treatment”
Comparison of subjects who actually took treatment

40
Q

What is the primarily analysis, intention to treat or on treatment

A

Intention to treat

41
Q

Why do you need to maximise compliance

A

• Need to maximise compliance to ensure trails results are meaningful

42
Q

What does poor compliance cause

A

• Poor compliance on an intention-to-treat analysis reduces ability to detect treatment difference (if one exists)

43
Q

How can you maximise compliance

A

– Selection of patients (not too ill)
– Double blind design
– Run in period where all get treatment (to identify those who can’t tolerate it)

44
Q

How do you know the number of patients needed to treat (How many patients would need to be treated to prevent one patient getting the disease/ disorder)

A

Work out the absolute difference in risk

Absolute risk = risk of treatment group - risk of control group

45
Q

What is the sample size

A
  • Specify number of people to recruit prior to starting the trial
46
Q

How do you work out the sample size

A
  • If too few participants may not detect a real effect: study does not have enough statistical power
  • Number needed calculated based on some prior information (eg expect relative risk of death of treatment A compared to B to be 2)
  • Power is usually fixed at 85% or higher
47
Q

if it is not statistically significant then we don’t need to determine if it is …

A

if it is not statistically significant then we don’t need to determine if it is clinically significant

48
Q

How to determine if it is clinically significant

A

if the percentage difference is large enough

49
Q

What is the purpose of a meta analysis

A

Purpose to bring together all the evidence to more powerfully estimate the effect size

50
Q

What studies can meta analysis be used in

A

• Can be done for cross-sectional, case-control, cohort studies and randomised trials

51
Q

What are the results of a meta analysis summarized in

A

• Results of individual studies and a summary estimate often shown in a Forest plot

52
Q

What are the issues in meta analysis

A

Heterogeneity

Publication bias

53
Q

What is hetrogeneity

A

Heterogeneity in statistics means that your populations, samples or results are different.

54
Q

What causes Heterogeneity

A

• Caused by
– difference in study design
– difference in participant characteristics
– difference in intervention eg drug dose
– chance

• Can be assessed statistically – is there greater heterogeneity than you would expect by chance?
– Look for causes

55
Q

What is publication bias

A

• Studies with significant or favourable results more likely to be published

56
Q

What is publication bias caused by

A

• Caused by
– investigators
– journal editors
– journal peer reviewers

57
Q

How can you assess publication bias

A

• Can be assessed statistically and graphically – funnel plot

58
Q

How do you work out funnel plots

A

Funnel plot

  • Relative risk of horizontal
  • Standard error associated with relative risk of the vertical standard
  • If there is no publication bias the points will be scattered either side of the line