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.
why do we use blocking
But the reason we bother to do this is that it ensures balance in the treatment assignment ratio over time. And this makes sense, right? Because if we’re using that block size of four, that means after every four patients, even if we have a sample size of 400, after every four patients, we’re ensured that we’ve met the allocation ratio, that two have been assigned to A and two to B. As we go along in the trial, we can’t have long runs of As or long runs of Bs that you might have in a simple randomization design
the longest possible run of a treatment for two patients is?
two
possible blocks for blok size?
factorial shit,vmultinomial coefficient
blocking implementatio?
fixed allocation ratio troughtout the trial
it is a secret (block sizes are on need t oknow basis), it should not be in protocol that investigator reads
use more than a one block size (overall sequence appears more ranom, protects against discovery especially in unmasked trials)
advantages of blocking?
-overall balance, epecially in smaler trials
- protects against time related changes
- if trail is stoped early, have a balanced groups
Analysis are more powerful
disandvantages of blocking?
can facilitate predictions of future assignments
more problematic for masked trials or poorly masked trials
what stratification ensures?
ensure ballance in treatment assigments within subgroups defined before randomization (clinic, gender, risk level)
subgroups in stratificationß
should be related to outcome- strong cofounder or effect modifier
what requires stratification?
a separete set of treatment assignments schedules for each category of each stratum
Does stratification without blocking makes sanse?
No, u could be in more risk because of that.
Example of stratificatio
minut 21 to 24 , there is a table.
Practial aspects of stratification?
can be done to only few (1-2) variables that are higly related to outcam
usually that is clinila centre, surgeon, stage of disease and sometimes demographic factors (gender, age)
if u have too many stratification?
u cound get up with imbalences and blockes that are not filled till the end
What is to take home points from stratificatio nand blocking?
And so, the take home points here are that blocking is very important in terms of ensuring that you maintain the design allocation ratio as you go throughout the trail and helps control for a number of things that can change over time. Whereas stratification, is related to baseline characteristics of the patient, or where the patient is at, that you can control the balance of the treatment assignment, that it meets the design assignment within those subgroups of patients. And indeed, for stratification to be effective, you should also apply blocking.
what is adaptive rz?
An Adaptive scheme is a process in which the probability of assignment to the treatment i.e the allocation ratio, does not remain constant over the course of the trial, but is somehow determined by the current balance of participants in the trial, or even the outcomes from patients enrolled in the trial.
two types of adaptive rz?
minimization and play the winner
what is minimizatio and its characteristics
One is based on minimization, after the first patient the treatment assignment that yields the smallest in balance is chosen
in a minimization scheme you can be balancing on a number of characteristics or prognostic factors as you go on in the trial, and ensure that your, have balance as the trial goes on.
minimizatio nhandle much more factors than stratification
allocation sequence can not be determend in advance
play the winner? what do you need to do?
you change the treatment allocation to favor the better treatment based on the primary outcome.
you need to evaluete outcomes relativly quickly.
adaptive rz- can it be implemented in stages
yes, so you might start with a, fixed allocation ratio and after you get to a certain number of patients, impliment an adaptive ratio.
purpose of masking?
The purpose of masking is to reduce information bias. In a nutshell, it helps to ensure that we treat participants assigned to the experimental and control treatments the same throughout the trial and objectively evaluate their outcomes.
Whaz is masking?
What masking means is that the treatment assignment is not known after randomization. And so it’s important to recognize that this isn’t about not knowing the treatment assignment before someone comes in. But it’s after randomization.
Rationale for masking?
is to reduce any bias that might be related to prior knowledge or beliefs about the treatment effects on the performance trial.
It promotes objectivity in :
- data reporting
- data collectio nand follow up
- concomitant treatments, behavior
- outcome assesement
- data interpetation
level of masking?
1- patient is masked
2- patient and clinical investigators
3- patient, clinical investigator and others (outcome evaluetors, data analyst, data monitoring comitees, sponsors,..)
advantages of masking?
protecs agains performance/repoting bias:
- data collection and follow up
- outcome assesement and reporting
- other care recieved during the trial
- interpetation of results
disadvantage of masking?
- may be logistically or etically impossible
- may not reflect clinical care practice
- increases logistical complexity
- increased costs
bias protection by level of masking?
table at 7:00
two questions to ask when we decide to mask participants?
is it ethical? :
- exposure to risk of placebo, sahm surgery, iv infusions
- risk if investigator doesnt know
- viable unmasking plan
is it possible?
- can u make the treatment seem identical
- can u create placebo for each treatment
- for example behavioral intervention could be impossible
two questions to ask when we decide to mask participants?
is it ethical? :
- exposure to risk of placebo, sahm surgery, iv infusions
- risk if investigator doesnt know
- viable unmasking plan
is it possible?
- can u make the treatment seem identical
- can u create placebo for each treatment
- for example behavioral intervention could be impossible, or weight loss programs
two more questions to ask when we want to do masking?
what are design features?
- type of outcame is important , the more objective it is, the more suitable for masking
- ophatmology example
- what are the comparison groups (no tretment grop should need more masking than an active control group)
Is it feasable?
- effectivness
- cost-benefit
- adhernece (many pills)
two more questions to ask when we want to do masking?
what are design features?
- type of outcame is important , the more objective it is, the more suitable for masking
- ophatmology example
- what are the comparison groups (no tretment grop should need more masking than an active control group)
Is it feasable?
- effectivness
- cost-benefit
- adhernece (many pills)
planned unmasking?
closeout design:
- common, all participants finish the trial at same time
- anniversary, ussualy after 6 months while enrolling is still on, that should not be revelad to clinical stuff, letters to participans at the end, instructions fot continuation of treatment
unplanned unmasking and methods
we usually discourage that
methods:
- drug container
- at clinicl semi-independet person responisble
- contact parties responsible for rz/masking
- 24 hour call line
- website
