Randomized controlled trials Flashcards
How doe we know a treatment is effective?
Someone tells us - authority figures (but how do they know?)
underlying theory - pathophysiology
observational evidence - scientific method
What factors need to be taken into account when deciding whether to treat?
benefits worth harm
resource costs
patient preference
ethics
What are the 4 factors you need to consider and how can you correct for them to explain your observations ?
1) bias - study design can reduce this
2) confounding - randomization can reduce this (study design)
3) chance - statistics can check this
4) hypothesis correct= effective
What comes under external validity (generalizability)?
benefits worth harms, resource costs, patient preferences, ethics and is this applicable to my patient/population
What comes under internal validity?
explanation of observations
- bias, confounding, chance and hypothesis correct
What are the 2 groups of randomization’s in RCTs?
- individual randomization
- cluster randomisation
What does regression to the mean mean?
most things vary to some extent by chance
if you observe an extreme value (unusually high or unusually low), part of the reason for it being extreme is chance
Therefore the next observation is likely to be closer to the mean - which can give the appearance of improvement
What does bias mean?
patient’s or researchers beliefs affect outcome measurements
What does confounding mean?
Differences between groups at the start
Some other difference in the way in which groups are treated
What is the purpose of randomization?
ensures known and unknown characteristics that might affect the outcome (confounders) are distributed by chance
- any differences between groups t the start are due to chance
Minimizes confounding
What are the issues with RCTs?
choice of outcome measure ethics choice of control contamination (crossover) bias in assessment of outcome losses to follow up sample size
What are the different choices of outcome that can be measured?
- ideally measure outcome relevant to the patients - if a proxy or process measure: are we confident it is linked to the outcome? e.g. immunization rate proxy for % of population immune
- clinical effectiveness – measure clinical outcome e.g. cure or a proxy
- patient experience - generic quality of like, disease specific measure e.g. pain score
What are some of the ethical issues associated with RCTs?
are individuals disadvantaged by being randomized to intervention or control?
if we believe one is better we cannot ethically randomize - equipoise
if we don’t know which is better is it ethical NOT to evaluate effectiveness
What are the different options for choice of control?
usual care
no treatment -if there is no usual care and we don’t believe new treatment is effective
Placebo - something that appears similar to intervention - distinguishes intervention effects from placebo effects - helps to blind the patient and researcher
What does it mean by contamination or crossover?
participants randomized to the control group may unintentionally receive the intervention
participants randomized to the intervention group may NOT receive the intervention
What happens if crossover or contamination occurs?
if you analyst according to the treatments received you have allocation bias
What options do you have if your study undergoes crossover or contamination?
1) analyst according to treatment received - but no longer randomized
2) analyst by intention to treat - preferred option
- this reduces risk of allocation bias, however it may underestimate the effect
What are the final numbers in this analysis?
It includes everyone, even those that were lost to follow up
When does contamination or crossover tend to be a problem?
if the intervention is information/education
and/or if we can’t treat patients differently in the same clinic
How can you reduce crossover/contamination?
cluster randomisation - randomize groups or clusters rather than individuals, reduces crossover but the statistical analysis is more complex
How can bias occur when assessing outcomes?
influenced by patient’s expectations, researcher’s expectations and analysts expectations
What was found when assessors were non-blinded?
substantially exaggerate treatment effects - misclassification of assessed patients
Other than blinding how else can bias arise?
by stopping an intervention too early - treatment may be effective initially but over time it might not be
What are the degrees of blinding?
unblinded/open
single blind - participants don’t know if treatment or control
double blind - researcher measuring outcomes does not know
triple blind - analyst reviewing results doesn’t known
What is allocation concealment and why is it important ?
when randomization is undertaken the researcher should not know whether a participant will be allocated to intervention or control
Allocation concealment prevents researchers from influencing which participants are assigned to the intervention or control group
When does losses to FU affect results and when doesn’t it?
little effect on result if:
- losses related to treatment allocation or
- losses related to outcome
Affects results if losses related to treatment allocation and to outcome (bias)
Helpful to describe the characteristics of those lost compared to those followed up - are there systematic differences
Why is sample size important?
The correct sample size is required for results to be interpreted
- expected effect = smaller effects will need larger sample sizes
- variation in measured outcome = outcomes measured imprecisely need a larger sample size
- significance - at what significance level will we accept there is a difference
- power = how certain do we want to be to find a difference if there is one
What does selective losses in fu mean?
bias
