PCM Flashcards
The study of the distribution and determinants of disease frequency in populations and the application of this study to control health problems.
epidemiology
A range of values on either side of the odds ratio or point estimate
CI confidence interval
Used to determine if the observed differences between groups (such as ill and not ill) are significant or due to chance
p-value
What is a statistically significant p-value?
a p-value of less than or equal to 0.05 is statistically significant. The result is not likely attributable to chance.
What is the possible range of a p-value?
p-values range from 0-1
What is a statistically significant CI? (Or, what is a CI that is not statistically significant)
A CI that includes 1 is not statistically significant
What is a 95% CI telling you?
We are 95% confident that the true value lies in this range.
This measures new cases developing over a period of time
incidence
This measures existing cases at a particular point in time or over a previous period of time
prevalence
(# of new problems during a given period of time)/(total population at risk)
incidence
(# of patients with the problem at a designated time)/(total population at that time)
prevalence
This is used to compare risk in two different groups of people, for example risk of heart disease in smokers and nonsmokers.
relative risk
risk of disease in exposed/risk of disease in unexposed
This is the risk of a group developing a disease over a period of time
absolute risk
risk of disease in exposed - risk of disease in unexposed
incidence rate 1/incidence rate 2
rate ratio
used to determine the probability of a certain event, e.g. crude birth rate
ad/bc
[same thing as (a/b)/(c/d)]
odds ratio
odds of developing the disease in exposed is X times the odds of developing the disease in unexposed
If a pregnancy test is 99% _______ and the test result is negative, you can be nearly certain they are not pregnant.
(sensitive, specific)
sensitive
If an HIV test is 99% _______ and the test result is positive, you can be nearly certain they actually have HIV.
(sensitive, specific)
specific
A very sensitive test rules ___ disease when the result is ________.
(in, out/positive, negative)
A very sensitive test rules out disease when the result is negative.
A very specific test rules ___ disease when the result is _______.
(in, out/positive, negative)
A very specific test rules in disease when the result is positive.
If you get a positive test result, the probability that the person really does have the disease
positive predictive value
What is the difference between effectiveness and efficacy?
An EFFECTIVE treatment provides positive results in a usual or routine clinical care condition that may not be controlled for research purposes.
An EFFICACIOUS treatment provides positive results in a controlled experimental research trial.
What is the ‘number to treat’?
the NNT is the average number of patients who need to be treated in order to prevent one additional bad outcome
What are the characteristics of an ideal screening test?
100% specific, 100% sensitive
- reasonable cost, safe to administer
- disease has a widely available treatment with a potential for cure that increases with early detection
- can detect high proportion of disease in its preclinical state
- disease is a public health problem (common condition, significant morbidity & mortality)
- will lead to improved health outcomes
- test is widely available
What is the difference between screening and diagnostic tests?
Screening: primary or secondary prevention when patients are asymptomatic but at risk
Diagnostic: test is done when patient is suspected of having a disease and test will confirm
What is the procedure for parallel screening tests?
Two screening tests are performed at the same time and the results are combined
What is the procedure for serial screening tests?
Second test is performed only if the first test was positive
What is the difference in effect on sensitivity and specificity for parallel and serial screening test strategies?
parallel: raises sensitivity, lowers specificity overall
serial: lowers sensitivity, raises specificity overall
What is the difference between background and foreground questions?
BACKGROUND questions ask for general knowledge about an illness, disease, condition, process or thing. These types of questions typically ask who, what, where, when, how & why about things like a disorder, test, or treatment, etc.
FOREGROUND questions ask for specific knowledge to inform clinical decisions. These questions typically concern a specific patient or particular population. Foreground questions tend to be more specific and complex compared to background questions. Quite often, foreground questions investigate comparisons, such as two drugs, two treatments, two diagnostic tests, etc. Foreground questions may be further categorized into one of 4 major types: treatment/therapy, diagnosis, prognosis, or etiology/harm.
What 3 factors are integrated in Evidence-based Medicine?
- best external evidence
- individual clinical expertise
- patient values & expectations
What is the PICO format for formulating foreground questions?
P: patient problem or population (who is the patient, what problem is being addressed)
I: intervention (what is the intervention or exposure)
C: comparison (what is the comparison group)
O: outcome (what is the outcome or endpoint)
What is the 2x2 table?
………………….disease yes….disease no
exposure yes………A………………B
exposure no……….C……………….D
What is internal validity?
Internal validity is the extent to which a causal conclusion based on a study is warranted. The study basics, did they minimize bias, were there confounding factors.
What is external validity?
External validity is the extent to which a study’s results can be applied to populations/situations/etc. different from those in the study. In other words, can you generalize the study findings from the research population to other groups/situations?
What is statistical power?
the probability that the test will reject the null hypothesis when the null hypothesis was false - the probability of not making an error…
(Error is either getting results that show an association between disease and exposure but there is not truly an association or getting results that show there is no association and there truly is one.)
This is an error in interpretation of results due to other unmeasured factors
confounding
What are four ways to minimize confounding?
- RESTRICT/STRATIFY the study subjects narrowly (e.g. narrow age range or women only)
- MATCH subjects on important potential confounders - assures the comparison groups are the same
- RANDOMIZE (intervention/RCT only) - this attempts to produce comparison groups that are similar on both known and unknown confounders
- MATH, aka regression techniques
What are three ways to minimize bias?
- randomize
- blinding
- double-blinding
What is bias?
systematic error that causes incorrect interpretation of results
What are two types of bias?
selection bias
information bias
What is the primary source of selection bias in case-control studies?
the manner in which cases, controls, or both are chosen
What is the primary source of selection bias in cohort studies and clinical trials?
loss to followup, withdrawal from study, or non-response
What is the primary source of selection bias in cross-sectional studies?
selective survival (one of the groups, exposed or unexposed, survives longer than the other)
In this type of study, a set of observations is collected from all subjects at a certain point in time…a “snapshot”
cross-sectional
In this type of study, subjects are chosen based on confirmed DISEASE and certain exposures are observed to see if there is a causal relationship
case-control
In this type of study, subjects are chosen based on their EXPOSURE and observed to see if they develop the disease in order to determine risk factors for a disease
cohort
In this type of study, an intervention (e.g. medication, device) is chosen and tested to see if it works. Gold standard of evidence.
clinical trial
What is a prospective study?
A prospective study watches for outcomes, such as the development of a disease, during the study period and relates this to other factors such as suspected risk or protection factor(s). The study usually involves taking a cohort of subjects and watching them over a long period.
What is a retrospective study?
A retrospective study looks backwards and examines exposures to suspected risk or protection factors in relation to an outcome that is established at the start of the study.
Looks at already-collected data as though it was happening in real time.
Study for odds-ratio
Case-control study
What is randomization and why is it important?
Subjects get randomly put into different arms of the study - it reduces bias.
Study for NNT
RCT/Clinical trial
Studies that can be used to calculate relative risk
Cohort, RCT/Clinical trial
What is information bias?
bias arising from measurement error
What is selection bias?
bias arising from the way the subjects are identified and selected for the study
What would make your CI narrower?
larger sample size
What are the 2 definitions of p-value?
- the probability that we make a type I error (falsely reject the null hypothesis)
- the probability that the difference we saw between the groups happened by chance alone
What is the formula for sensitivity?
True positive/(true positive + false negative)
What is the formula for specificity?
True negative/(false positive + true negative)
the proportion of people WITH THE DISEASE that the test correctly identified as positive
sensitivity
the proportion of people WITHOUT THE DISEASE that the test correctly identified as negative
specificity
Use this test for screening
highly sensitive test
Use this test for confirming a diagnosis
highly specific test
What is the formula for positive predictive value?
true positive/(true positive + false positive)
What is the formula for negative predictive value?
true negative/(true negative + false negative)
If you get a negative test result, the probability that the patient really doesn’t have the disease
negative predictive value
What is the difference between nominal and ordinal variables?
Nominal: has two or more categories, but there is no intrinsic ordering to the categories. For example, gender is a nominal variable having two categories (male and female) and there is no intrinsic ordering to the categories. Hair color is also a nominal variable having a number of categories (blonde, brown, brunette, red, etc.) and again, there is no agreed way to order these from highest to lowest.
Ordinal: there is a clear ordering of the variables. e.g. elementary school, junior high, high school; excellent, average, poor; etc.
What is an ecologic fallacy?
The ecological fallacy occurs when you make conclusions about individuals based only on analyses of group data. For instance, assume that you measured the math scores of a particular classroom and found that they had the highest average score in the district. Later (probably at the mall) you run into one of the kids from that class and you think to yourself “she must be a math whiz.” Aha! Fallacy! Just because she comes from the class with the highest average doesn’t mean that she is automatically a high-scorer in math. She could be the lowest math scorer in a class that otherwise consists of math geniuses!
