clinical trials and P values Flashcards
P-values
The lower the P value the more likely the results are going to be significant and we can reject the null hypothesis
what does a P value of <0.0001 show
null hypothesis can be rejected
accept that there is a significant difference
definition of P-value
probability of obtaining the study result if null hypothesis is true
easier to reject null hypothesis - smaller P value
significance and key components in clinical trail design
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
critical features of clinical trial design
objective patient selection - representative of everyone and then randomise to treatment A or B control study size unbiased data collection specific design ethics analysis
ethics of a clinical trial
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
objectives of the clinical trial
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
Bias in clinical trial
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
what are the advantages of randomisation
validates statistics
excludes bias allocation
prognostic values should be balanced - may do stratification eg between geographical regions - ie because they have differnet treatment programs
baseline data
at baseline results should be similar
might have to have further adjustments
how do you reduce effect of drop out in clinical trial
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
why do we need a control group in clinical trial
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
what is regression to the mean
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
Sample size and error
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
bias and sponsorship
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
