Flashcards in Unit 2 Deck (102):
What are the two types of study designs?
Intended to describe a disease condition - signs, lesions, outcomes, occurrence of microbes, etc.
Seeks to identify causes. Has a hypothesis, has controls. Used to investigate a treatment, intervention, or risk factor, in hopes of providing causal evidence.
Explanatory (or causal) study
List the two main types of explanatory studies:
experimental, observational (epidemiologic)
List the three types of observational studies:
Planned comparison between 2 groups - one receiving one treatment, another receiving a different tx for a naturally disease - researcher has some control
Experimental - Clinical trials
Researcher has the greatest control and involves the use of experimental animals. This type of study is the best design to prove cause or demonstrate efficacy
Experimental - laboratory
Sometimes called "natural studies" as they occur freely in nature.
Why are observational studies under the category of "explanatory type" studies?
the goal is to assess cause
What is the difference between observational and experimental studies?
Which animals go to treatment groups is not under control of the researcher for observational
Observational studies contribute to the body of evidence implicating a ______ as a cause. They often do not provide sufficient ________, in one study, to establish a cause.
a group sharing a defining characteristic
Type of observational study that is prospective in time:
What are the two types of cohorts featured in a study?
1. one exposed to a factor
2. one NOT exposed to a factor
Subjects are followed in time, and incidence of one or more diseases are compared between the two groups:
For a cohort study, what does a relative risk >1 indicate?
an increased risk in exposed, compared to unexposed
For a cohort study, what does a relative risk =1 indicate?
that the risk in exposed is the same as the risk in the unexposed
For a cohort study, what does a relative risk <1 indicate?
that the disease in the exposed is less than the unexposed
A relative risk < 1 for a cohort study indicates that exposure has a "sparing effect". What does this mean?
a reduction in risk associated with exposure
What kind of exposures might give a sparing effect?
Measure of the strength of association between a factor and a disease:
Relative risk can ONLY be calculated in what 2 studies?
cohort and cross-sectional
Cannot be estimated in a case-control study:
What is the equation for relative risk?
(proportion with disease in exposed)/(proportion with disease in unexposed)
Well suited for studying disease and exposures that occur relatively commonly:
Well suited to study the effect of multiple outcomes following a single exposure:
What are two benefits of cohort studies?
1. researcher has control over data quality (recorded in real time)
2. time sequence of "cause" and disease is clear
Factor A occurs before disease X
Factor A is present very often in cases, and not in controls:
strength of association
The more factor A you have, the greater the disease chance
Based on what is known, Factor A could cause disease X
The relationship between Factor A and disease X is seen repeatedly, time and again
Consistency of multiple studies
Other causes are not likely or impossible
rule out other possible causes
Removal of Factor A results in diminished disease
A selected group within the population is sampled once and exposure and disease are simultaneously measured:
cross sectional (prevalence) study
How are cross sectional studies not like cohort studies?
animals are NOT followed in time to establish disease incidence
What are the advantages of cross-sectional studies?
- short, fast, inexpensive
- can gather data on multiple diseases/exposures
- provides preliminary evidence for further study
Cohort studies are usually conducted in a:
Animals with a disease
Animals without disease:
Study in which animals with a disease are compared with one more controls:
Can be used to study rare (infrequent) disease:
Why are case-controls considered retrospective studies?
look into the past and compare the frequency of occurrence of risk factors for cases vs. controls
Odds of exposure in cases compared to odds of exposure in non-cases
What two measurements assess the strength of association between exposure and disease (but in slightly different ways)?
1. relative risk (cohort)
2. odds ratio (case-control)
The probability of an event occurring to the probability of the event not occurring:
Which measure of association can be used in case-control AND cohort studies?
odds ratio (RR is easier for cohort though)
When are OR and RR pretty close?
when the disease is rare (<10%)
How to calculate OR =
An odds ratio > 1 indicates:
an increased risk
An odds ratio = 1 indicates:
there is no increased risk
An odds ratio < 1 indicates:
a "sparing" effect
estimates risk of exposure in cases, compared to exposure in controls:
estimates risk of disease in exposed, compared to risk of disease in non-exposed:
A population of animals is sampled at a specific point in time:
How is each animal classified in a cross sectional study?
according to status of outcome and risk factor, simultaneously, at the time of the snapshot
Can be used to assess absolute risks in the population
Typically refers to the assessment of serum antibody concentration:
The point at which we have diluted a serum sample and measured until there is no longer a reaction:
"end point titer"
What is the idea behind testing serology?
you can determine the last dilution at which an Ag:Ab reaction occurs (end point titer)
What does seropositivity depend on for each titer?
You must be over the critical titer to be classified as:
A 2 fold increase (or 1 dilution) between week 1 and week 4 is considered:
A four fold increase (or 2 diluations) between week 1 and week 4 is considered:
to be greater than lab error, reflecting active Ig production
Why do we often use the Log2 transformation when talking titers?
much easier to work with when they assume a normal distribution
Ability to correctly classify (detect) disease animals. Expressed as a proportion:
The test that is used to determine if a disease is truly present or not. Other tests are compared to it to determine their "accuracy"
Of those truly D+, the proportion correctly classified by Test Z
Ability of a test to correctly detect (classify) non-diseased animals.
The ability to measure the correct substance (i.e. not measuring particles or molecules other than the target):
how close a test result is to the truth
What may be different if comparing populations in early vs. late stages of disease?
Properties of the test that allow for comparison between tests (i.e. 2 test for detection of FeLV):
Higher sensitivity improves _____ and helps identify the disease. It rules ____ disease.
NPV; OUT (SnOUT)
How does lower specificity alter PPV?
Lower specificity =
more false positives
A more sensitive test reduces _______ ________ and increases NPV.
helps rule out disease
A more specific test reduces _____ __________ and improves PPV.
rules in disease
By altering the cutpoint, you alter:
sensitivity and specificity
Increased sensitivity results in:
lower specificity, fewer false negatives, more false positives
When is it advantageous to alter the cut-off point in a test?
if you want to rule in/out a disease
Two or more tests are conducted sequentially based on the results of a previous test:
In serial testing, only animals that test ________ to the first test are tested again.
In serial testing, only animals that are positive on __________ are considered positive.
Used for diagnosis when time is not crucial or if diagnosing a patient when disease positive has a grave outcome.
Conduction two or more tests on a patient at the same time:
If any one test is positive, the animal is categorized as sick:
When is parallel testing used?
rapid assessment/medical emergencies
Increased sensitivity -->
fewer false negatives
decreased specificity -->
more false positives
Because sensitivity is reduced, you will allow more diseased animals to remain in the herd:
Relatively small number of positive tests. The pool of positive tests is nearly all “Sick”. But not all sick are in the test + pool.
Positive test identifies animal at high probability of Illness,
Confidence in Positives SpIN
More positive tests. Positive pool captures almost all ill, but includes many non-ill too.
The negative test pool ID's "well" animals. Confidence in Negatives SnOUT
single numbers (points) derived from a sample
represents our best estimate of the true value of the population parameter:
a range of values that the point estimate could reasonably take
The probability of obtaining the observed value (or more extreme value) when the null hypothesis is TRUE