clinical trials and P values Flashcards

1
Q

P-values

A

The lower the P value the more likely the results are going to be significant and we can reject the null hypothesis

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2
Q

what does a P value of <0.0001 show

A

null hypothesis can be rejected

accept that there is a significant difference

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3
Q

definition of P-value

A

probability of obtaining the study result if null hypothesis is true
easier to reject null hypothesis - smaller P value

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4
Q

significance and key components in clinical trail design

A

population based studies
inference about causal relationships - see the burden of risk factor
think how much time you have - long time, collect events over that time - short, case series individual patients that you see
compare and assess effectiveness of 2 treatments

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5
Q

critical features of clinical trial design

A
objective
patient selection - representative of everyone and then randomise to treatment A or B 
control 
study size
unbiased data collection 
specific design 
ethics 
analysis
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6
Q

ethics of a clinical trial

A

clinical equipoise - genuine uncertainty as to whether the treatment is more effective
need informed consent
placebo denies people of treatment
need to analyse the results before the trial is unblinded

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7
Q

objectives of the clinical trial

A

have a primary end point and population looking at - event driven - short study and long follow up or long study and short follow up when looking for a body count or take population more likely to have events
power

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8
Q

Bias in clinical trial

A

systematic error in design, conduct/analysis of a study which produces a mistaken estimate of exposure on the risk of disease.
need randomisation prior to entry in study
block randomisation - eg 10 patients in 1 group, next 10 patients in the next group

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9
Q

what are the advantages of randomisation

A

validates statistics
excludes bias allocation
prognostic values should be balanced - may do stratification eg between geographical regions - ie because they have differnet treatment programs

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10
Q

baseline data

A

at baseline results should be similar

might have to have further adjustments

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11
Q

how do you reduce effect of drop out in clinical trial

A

similar number of people at start so that a similar number of people from each group drop out
need to try and get people back on - allowed to go off it for a short amount of time
keep the trial blind - so patients who are on the treatment don’t know and drop out because they fear side effects
dropping out reduces power

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12
Q

why do we need a control group in clinical trial

A

consistency between groups - see if excess compared to placebo/if side effects are the same in both
without control no reason to assume that the observed effect is due to the intervention
regression to the mean
acclimatisation
seasonal effect
basis of study question

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13
Q

what is regression to the mean

A

intervention in bad time - outliers move towards middle
without control you wouldn’t know if this was going to happen anyway
extreme on 1st measurement will be closer to the mean on second measurement

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14
Q

Sample size and error

A

even if there are significant results - might be due to chance if the sample is too small
when have sig p value
power of study calculated by B
number of effects and magnitude of treatment goes up - increase power
how many end points needed to see that it is a real result

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15
Q

bias and sponsorship

A

sponsors fund the trail
not involved in conduct - they’re non-voting members
independent statistician - only person who knows who is on which treatment
independent analysis and reporting
data must be in a public domain - don’t let sponsors block information
sponsor only release top line - the study design and result

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16
Q

Bias and analysis

A

must consider the people who drop out of trials
need to complete follow up otherwise you might achieve the same result but it might not be representative
not stat sig, maybe to chance
intention to treat - need to keep them is study and use their results - this is decided before. they were equal
differential discontinuation rate for med - perprotocol analysis - if only take people taking drug groups aren’t balanced
keep as many people in as possible
want accurate follow up data - otherwise count against you

17
Q

what is the problem with subgroups

A

fewer in trial
no power
can only do it as a comparison
trial only designed to look at primary end point in original group

18
Q

what is a cross over study

A

everyone is own control - because of genetics biological effects should be similar
have wash out period - don’t want carryover
increased power

19
Q

adherence to study drug

A

only if you look at this that the results are reasonable

20
Q

what is the problem with testing a lot of things

A

more likely to get a chance association