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Life Maintenance > Role of clinical trials > Flashcards

Role of clinical trials Flashcards

1
Q

What are the strengths of RCTs?

A
  • can determine causality
  • quantification of chance or random error

only if RCT has been well-conducted

BIAS and confounders are generally not seen in RCTs

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2
Q

What kind of interventions can be tested in experimental studies?

A

[experimental = RCTs]

many:

  • medical Rx
  • Surgical Rx
  • health promotion advice
  • dietary change
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3
Q

What are the more difficult interventions to test via RCT?

A
  • long term interventions

- ‘lifestyle’ change (other than advice)

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4
Q

What features would the ideal experimental study have?

A
  • (placebo-) controlled
  • randomised
  • double blind
  • large
  • analysed by ‘intention to treat’ method
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5
Q

Why do patients tend to get better (with or w/o Rx)?

A
  • natural tendency to recover
  • probability: regression to the mean seen for individuals at the extremes of distribution
  • placebo effect
  • effect of Rx
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6
Q

Why are controls needed?

A
  • because some patients will get better by themselves, need a comparison group
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7
Q

Why is a placebo control group needed?

A
  • take account of the placebo effect
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8
Q

What are the nature of control groups in practice?

A
  • sometimes receiving no active Rx
  • sometimes receiving usual care (without new Rx)
  • may be receiving placebo for ‘active’ intervention
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9
Q

How are individuals allocated to each group in RCTs?

A

Allocation must be RANDOM

[ reduces allocation bias and confounders ]

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10
Q

Why is random allocation in RCTs good?

A
  • avoids allocation bias
  • avoids confounding
  • simplifies interpretation of differences between groups
  • facilitates blinding process
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11
Q

What are the issues with assessing outcomes in RCTs?

A
  • vested interest in trial outcomes

ASSESSMENT BIAS”
subjective outcomes:
- patient-assessed
- observer-assessed

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12
Q

What is the solution to making outcome assessment in RCTs robust?

A

keep ‘key people’ blinded to randomisation code

  • patient
  • outcome assessor
  • statistician/analyst
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13
Q

What are the different levels of blinding in RCTs?

A

SINGLE BLIND
=> patient or outcome assessor

DOUBLE BLIND
=> patient AND outcome assessor

TRIPLE BLIND
=> patient AND outcome assessor AND statistician

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14
Q

What trial outcomes may be used in RCTs?

A
  • Sx
  • clinical sign
  • biochemical sign
  • clinical disease onset
  • death
  • objectively measured ideally
  • may have several outcomes
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15
Q

What are the 3 basic design for RCTs?

A

RANDOMISED

  • parallel group design (SINGLE INTERVENTION)
  • Crossover trial design
    (SINGLE INTERVENTION)
  • Factorial design
    (>1 INTERVENTIONS)
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16
Q

What is the crossover trial design of RCTs?

A
  • v. efficient: every participant acts as both intervention and control
  • more precise estimate of effect (than in parallel group)
  • only works for RAPIDLY ACHIEVED and REVERSIBLE outcomes
17
Q

When can crossover RCT design NOT be used?

A

NOT for irreversible events

e.g. cancer, DM, death

18
Q

What is the factorial RCT design?

A

2 interventions

4 equal sized randomised groups:

  • None (control)
  • A
  • B
  • A+B (dual intervention)

efficient design
all groups are involved in examining effect of A and B

19
Q

What are RCTs usually applied to?

A

individual patients

can also apply to groups using many individuals (= CLUSTER RCTs)

used to examine impact of community intervention

20
Q

What is the importance of trial size in RCTs?

A

RCTs are widely used, but sample size is often too small

  • limited statistical power
  • fail to detect Type 2 stats error (failing to see intervention effect)
  • trial effect estimates are imprecise
21
Q

What are the advantages of using a large sample size in trials?

A
  • higher statistical power
  • more precise effect size estimate
  • can look at sub-categories for impact of intervention
22
Q

What does a large trial sample size NOT achieve?

A

does NOT make trial more representative at large

=> dependent on SOURCE of trial population

23
Q

What are the presumptions that patients make on entering trials?

A
  • they will not come to any harm
  • will not be excluded from the usual effective Rx
  • fully informed re: prospects of benefit/risk
24
Q

What are the implications of trials in practice?

A
  • intervention must benefit rather than cause harm
  • control group: should have usual care rather than no care
  • informed consent
  • monitoring safety, adverse effects
25
Q

What are the challenges in trials?

A
  • not all patients will do what they’re meant to
  • some control patients will end up being on Rx
  • if analysis made on those who actually Rx: then imbalance of groups and biased estimate of Rx effect
26
Q

What is ‘intention to treat analysis’?

A
  • carried out on basis of original randomisation (crossovers are ignored)
  • underestimate of intervention effect
  • UNBIASED estimate of intervention effect
  • this should be the main analysis in most situations
27
Q

What is ‘per protocol analysis’?

A
  • analysis based on Rx actually taken, takes crossover between groups into account
  • less likely to underestimate intervention
  • May contain BIAS (dependent on number of drop-outs)
  • Generally a subsidiary analysis
28
Q

What are the main considerations when analysis a trial?

A
  • intervention effect?
  • chance impact?
  • limitations in trial design?
  • consistent results?
  • are results generalisable/representative?
  • recruitment rate?
29
Q

What are the main considerations in effective interventions?

A
  • cost-benefit
  • cost-effectiveness

should clinical practice be altered?

30
Q

Which trials looked at whether tight BM control reduced DM complications?

A

UKPDS

recent T2DM Dx
randomised to Rx with either insulin or sulphonylurea or usual care
aim <6 mmol/L
outcomes: DM-relate, deaths and hypos

31
Q

Which trial looked at whether cholesterol reduction with statin in DM reduced CVS risk?

A

randomised 10mg atorvastatin vs placebo

outcome: CVS disease after 4 years

32
Q

Which trial looked at whether T2DM can be prevented in high risk individuals?

A

Finnish Diabetes Prevention Study

pre-diabetic middle aged overweight

randomised to I:

  • weight reduction
  • fat intake reduction- - fibre intake
  • increased exercise

outcome: DM onset at annual OGTT

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