Jonathon Hopkins Course Module 2 Flashcards
Masking and its objective?
Masking, sometimes referred to is blinding, is a design feature that keeps study participants and/or study investigators from knowing which treatment the study participant is assigned (by randomization) to receive. Masking helps ensure objectivity in follow-up and outcome evaluation.
besides randomization, what other features are also importatnt in clinical trials?
- standardized treatment
- prospective plan for data collection
- adverse event reporting
- regulatroy requirements
These features tends to?
distinguish clinical trials from other types of observational studies and even from non randomized studies in some cases.
History of randomization -one man?
Van Helmont proposed that people be randomly divided or divided by lots to determine their treatment because he wanted to evaluate his form of care against more standard forms of care of the day, which included bloodletting and other potentially harmful interventions.
First use of randomization?
Ronald Fischer- trying to address was to how to allocate plots of soil in agricultural settings to different treatments.
Really first introduce of randomizatio nin clinical trials?
Sir Austin Bradford Hill- trial 1948 streptomycin
Rationale for randomization?
is to avoid selection bias and to avoid confounding by indication.
Some prognsotic factor that could influence outcomes?
age
severit of disease
clinical centres
rationale for randomization?
is to avoid selection bias and to avoid confounding by indication.
tends to produce comparable treatment groups (known and unknown cofounders)
assures statistical tests will have valid significance level
defined time-point for trial entry
unequal ratio in randomization
less powerful 1:1 95%
2: 1 92%
4: 1 82%
Rationale for unequal randomazatio ratio?
-as much as evidence as possible including adverse events and toxicity
incetive for recruitment
cost issues
variance in treatment effect may be different to optimize power more patients in group with larger variance
selection bias in clinical trials?
in the trial definition of selection bias, we’re really talking about eliminating the bias associated with the prognosis of the disease. So again to eliminate the confounding by indication. And we want to, to break that link between what the intervention actually is and the patient’s characteristics. So it’s more an issue of internal validity when we’re talking about, in selection bias, in the context of clinical trials.
What type of randomization are covered?
simple, restricted and adaptive randomization schemes
Simple randomization advantages?
complete randomization (coin toss), each new asignment is independet each assignement is completly unpredictable, there scould be equal number of patioents long run
Risks of simple randomizatio?
1.IMBALANCES
number of patients
no control on teh characteristics of a patiens in a tretment group (confounding factor)
low statistical power
- May diminish credibility of results
- Inversely associated with a number of patiens
o, how have clinical trialists and biostatisticians addressed this issue of simple randomization?
Well, they’ve imposed restrictions to the randomization scheme to ensure balance across important factors in the design of, of experiments. So, when somehow there’s a constraint added to produce the expected assignment ratio, in the example we’ve been using, one to one. According to time that the study’s been going on, or on specified covariates, such as severity of disease, or gender, or clinic. And the two primary maneuvers that are used in this restricted randomization are BLOCKING and STRATIFICATION.
what is block?
is a list of treatments that achieves the treatment assignment ratio.
block of 4 vs block of 2?
So, a block of two would be an A and a B that we achieve their ratio of one to one. If we use the block size of four, that means that a block would have two As and two Bs in it.
how many possibilities in block of 4, ratio 1:1?
six
how many possibilities in block of 4?
six
If the allocation ratio is one to one, the smallest block size is?
1 plus 1 is 2. That’s the smallest block you can have, to get a one to one ratio. So, if you have a different allocation ratio, say two to one, the smallest possible block size is three because you’d have to have two As and one B. And, if you wanted to go and use larger block sizes, and I’ll discuss reasons for using different block sizes in a few minutes, the larger block sizes need to be multiples of the smallest one, so in order to meet the treatment allocation ratio of two to one, the smallest block size you can have is three. The next one is six because that is a multiple of the smallest block size and, it goes up accordingly.
