Flashcards in Clinical Trials Deck (22)

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1

## Define Bias

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Bias = a systematic error in design, conduct or analysis of a study which produces a mistaken estimate of treatment effect.

2

## Define Confounding

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Confounding = when a variable (or factor) is related to both the study variable and the outcome so the effect of the study variable on the outcome is distorted.

3

## List the hierarchy of studies in order from highest to lowest. (7 in total)

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1) Systematic reviews and meta-analyses

2) Randomised Control Trials

3) Cohort Studies

4) Case-Control Studies

5) Cross-sectional Studies

6) Case Series

7) Case Reports

4

## Difference between observational and experimental study?

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Observational studies= independent variable cannot be controlled

Experimental studies= independent variable controlled

e.g. most epidemiological studies are observational, they are observing the population but the statistician does not input any medical intervention that could change the final outcome. Whereas an experiment done on rats could have an intervention (the independent variable) that has an effect on the final outcome

5

## What is a clinical trial?

### planned experiment in humans

6

## Purpose of clinical trial? How is it different to epidemiological studies?

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• Designed to measure the effectiveness of an intervention:

○ A new drug

○ A surgical procedure

○ A vaccine

○ Complementary therapy

• Different from epidemiological studies because most epidemiological studies are OBSERVATIONAL whereas clinical trials are normally EXPERIMENTAL

7

## Key components of a clinical trial? (4)

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• Define your intervention

• Define your comparator:

○ Placebo

○ Alternative treatment

○ Standard of care

• Define your inclusion criteria

• Define your exclusion criteria

8

## Why do you need a control group?

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-Compare to intervention group

-To show that any difference is due to the intervention

-Placebo may have some effect on patient and so it is worth having a control group to see this

9

## Purpose of randomisation?

### Eliminate bias. especially bias in treatment allocation (i.e. control group or intervention group)

10

## 3 ways of randomising?

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Methods of Randomising:

Block Randomisation - assign people to group A or group B randomly

Stratification - divides sample by important characteristics e.g. Male/female and then randomise within each gender into 2 groups:control and intervention. This allows you to e.g. compare effect of drug in male against females

Minimisation - calculates imbalance and you allocate the sample a little to try and maintain the balance

11

## What is involved in each of the 4 phases of clinical trials?

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1) Phase I

○ Test the safety of a new treatment

○ Small number of, usually healthy, volunteers

2) Phase II

○ Test to see if the treatment is efficacious - at least in the short term

○ Continue to look at safety

○ A few hundred people usually with the condition

3) Phase III

○ Compare the new treatment with the current or placebo

○ Look at how well the new treatment works (effectiveness)

○ Continue to monitor side effects

○ Several thousand patients

4) Phase IV

○ After the drug has been marketed

○ Measure effect in various populations

○ Look out for rare side effects

12

## Difference between efficacy and effect? Which phase of clinical trials are these 2 elements tested?

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• Efficacy

○ The biological effect

○ Can it work?

○ Phase II

• Effectiveness

○ The true OVERALL effect

○ Does it work in the real world?

○ Phase III

Efficacy determines whether the drug will achieve expected and desired results under ideal circumstances. Effectiveness determines whether or not the drug will work in the 'real world'

13

## What is the 'power' of a study?

### Power is the probability of rejecting the null hypothesis when the alternative hypothesis is true. It measures the ability of a test to reject the null hypothesis when it should be rejected. At a given significance level, the power of the test is increased by having a larger sample size.

14

## What does the 'α' symbol mean?

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Chance of rejecting null hypothesis when it is true.

aka Chance of false positive (type I error)

e.g. α=0.05 means 5% chance of rejecting null hypothesis when it is in fact true.

This is the same as hypothesis testing from A-level stats

15

## What does the β symbol mean?

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Chance of accepting null hypothesis when it is in fact false

aka false negative (type II error)

16

## What is the 'power' of a test?

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Power= 1-β

Power measures the ability of a test to reject the null hypothesis when it should be rejected. Since β is the probability of accepting the the null hypothesis when it should be rejected. Tests normally have 80-90% power usually.

17

## What is control event rate?

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The incidence in the control group

e.g. mortality in control group= 30%

18

## What is experimental event rate?

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the incidence in the treatment group

e.g. mortality in intervention group= 20%

19

## What is absolute risk reduction?

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Control event rate - intervention rate

e.g. mortality in control group=30%

mortality in intervention group=20%

ARR=30-20=10%=0.1

20

## What is relative risk reduction?

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Absolute risk reduction/control event rate

i.e. how much the risk has been reduced in the treatment group compared to the control group expressed as a proportion of the no of incidences in the control group

21

## What does 'number needed to treat' mean and how is it calculated?

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number of patients that need to be treated for one to get benefit

1/Absolute risk reduction

reminder:

ARR= Control event rate-experimental event rate

e.g. if ARR=5%

then 1/0.05=20

22