Duke Health - Module 3 Flashcards
Three overarching questions
- How serious is the risk of bias?
- What are the results?
- Will the results help in caring for my patient?
Were patients randomized?
* The assignment or patients to either group (treatment or control) must be done by
a random allocation
Were patients randomized?
* The assignment or patients to either group (treatment or control) must be done by a random allocation
* This might include:
(2)
o A coin toss
o Computer generated randomization tables
- Randomization balances the groups for …
This reduces the chance of …
known prognostic factors (such as age, weight, gender, etc.) and unknown prognostic factors (such as compliance, genetics, socioeconomics, etc.).
over-representation of any one characteristic within the study groups.
Was group allocation concealed?
* The randomization sequence should be concealed from the clinicians and researchers of the study to further eliminate
conscious or unconscious selection bias.
- Concealment, which is part of the enrollment process, ensures that
the researchers cannot predict or change the assignments of patients to treatment groups
- If allocation is not concealed it may be possible to influence the outcome consciously or unconsciously by changing:
(2)
o The enrollment order
o The order of randomly assigned treatment
- Concealed allocation can be done by using
(2)
o A remote call center for enrolling patients
o The use of opaque, sealed envelopes with assignments
- This is different from blinding which happens — randomization
AFTER
Were patients in the study groups similar with respect to known prognostic variables?
* The treatment and the control groups should be similar for all prognostic characteristics except …
* A good way to verify that randomization results in similar groups is to reference a …
whether or not they received the experimental treatment
Baseline Characteristics Table
- Blinding means that
people involved in the study do not know which treatments were given to which patients. Patients, researchers, data collectors and others involved in the study should not know which treatment is being administered
- This helps eliminate (2)
assessment bias and preconceived notions as to how the treatments should be working
- When it is difficult or even unethical to blind patients to a treatment, such as a surgical procedure, then …
a “blinded” clinician or researcher is needed to interpret the results
- The study should begin and end with
the same number of patients in each group. Patients lost to the study must be accounted for or risk making the conclusions invalid
o Patients may drop out because of the — of the therapy being tested
o If not accounted for, this can lead to conclusions that may be …
adverse effects
overly confident in the efficacy of the therapy
- Good studies will have better than –% follow up for their patients. When there is a large loss to follow-up, the lost patients should be assigned to the “—” outcomes and the results recalculated. If these results still support the original conclusion of the study, then the loss may be acceptable
80
worst-case
Were patients analyzed in the groups to which they were first allocated?
* Anything that happens after randomization can affect the chances that a patient in a study has an —
* Patients who forget or refuse their treatment should not be …
* Excluding noncompliant patients from a study group may leave only those that may be more likely to have a positive outcome, thus compromising the unbiased comparison that we got from the process of randomization. Therefore …
event
eliminated from the study results or allowed to “change groups.”
all patients must be analyzed within their assigned group.
- Randomization must be preserved. This is called “—” analysis
intention to treat
- Stopping trials early when one sees an apparent large benefit or because of a perceived harm to participants is risky
- One of the main reason is that these truncated RCTs can
greatly overestimate the treatment benefit, particularly in trials with small sample sizes
When we review the results, we typically ask how large and precise was the treatment effect
* We want to balance the (2) of the treatment effect with a consideration of — significance versus — significance
size and precision
clinical, statistical
o Experimental event rate (EER):
outcome present/total in experimental group
o Control event rate (CER):
outcome present/total in control group
o Absolute benefit increase (ABI):
the arithmetic difference between the rates of events in the experimental and control group. Refers to the increase of a good event as a result of the intervention
EER - CER
o Relative risk (RR):
the ratio of the risk in the experimental group compared to the risk in the control group. Proportional reduction in risk between the rates of events in the control group and the experimental group
EER / CER
o Relative benefit increase (RBI):
the proportional increase in benefit between the rates of events in the control group and the experimental group
ABI / CER
o Numbers needed to treat (NNT):
the number (rounded to the nearest whole) of patients who need to be treated to prevent one bad outcome or produce one good outcome
1 / ABI
How precise was the treatment effect?
* We usually use the –% CI
95
o You can consider the 95% CI as defining the range that, assuming the study has low risk of bias, includes the true treatment effect 95% of the time
- Clinical significance has little to do with statistics and is a matter of —
judgement
- Clinical significance often depends on the
magnitude of the effect being studied and answers the question
- Studies can be statistically significant yet
clinically insignificant
Once we have determined the risk of bias and interpreted the results, we can ask how we will apply the results to patient care
* We ask..
(3)
o Were the study patients similar to my population of interest?
o Were all clinically important outcomes considered?
o Are the likely treatment benefits worth the potential harms and costs?
