Kaplan High-Yield Behavioral

28 Pages·00.488 MB·English

by  Sam Asgarian

Lecture Objectives
Epidemiology
Sam Asgarian, M4
Tulane University
BBEE0011-- !1"
Epidemiology advice
Epidemiology advice
•  Easy section = easy to overlook
•  Points here can add up: make sure to prep as you do for any
Step 1 section and do not cram ! get all these points on Test
Day!
•  Become more ingrained in the test
FA 2012: n/a • FA 2011: n/a • FA 2010: n/a BE01- 2
Incidence
Incidence
Incidence rate: the rate at which new events occur in a population.The
numerator is the number of NEW events that occur in a defined period; the
denominator is the population at risk of experiencing this new event during the
same period.
# of new events in a specific period of time
Incidence =
# “at risk” of having a new event in the specific time period

a.  Attack rate: a type of incidence rate in which the denominator is further
reduced for some known exposure
b.  Focus on acute conditions
FA 2012: 54.1 • FA 2011: 52.1 • FA 2010: 54 • BE01- 3
ME 3e: 34
Prevalence
Prevalence
Prevalence rate: all persons who experience an event in a population. The
numerator is ALL individuals who have an attribute or disease at a particular
point in time (or during a particular period of time); the denominator is the
population at risk of having the attribute or disease at this point in time or
midway through the period.

# of individuals with disease/attribute
Prevalence =
Total population at risk

•  Point prevalence: prevalence at a specified point in time
•  Period prevalence: prevalence during a specified period or span
of time
•  Focus on chronic conditions

FA 2012: 54.1 • FA 2011: 52.1 • FA 2010: 54 • BE01- 4
ME 3e: 34
Clinical Trials
Clinical Trials
•  Clinical Trials
1.  Control group: subjects who do not receive the intervention under
study; used as a source of comparison to be certain that the
experiment group is being affected by the intervention and not by
other factors. In clinical trials, this is most often a placebo group.
2.  For Food and Drug Administration (FDA) approval, three phases of
clinical trials must be passed.
a.  Phase One: testing safety in healthy volunteers
b.  Phase Two: testing protocol and dose levels in a small group
of patient volunteers
c.  Phase Three: testing efficacy and occurrence of side effects in
a larger group of patient volunteers. Phase III is considered
the definitive test.
d.  Post-marketing Survey: collecting reports of drug side effects
when out in common usage (post-FDA approval)
FA 2012: 52.2 • FA 2011: 50.2 • FA 2010: 52 BE01- 5
Case-control and Cross-sectional studies
Case-control and Cross-sectional studies
•  STUDIES:
•  Case-control study: identifies a group of people with the disease and
compares them with a suitable comparison group without the disease.
Almost always retrospective (e.g., comparing cases of treatment-resistant TB
with cases of nonresistant TB)
a.  Cannot assess incidence or prevalence of disease
b.  Can help determine causal relationships
c.  Very useful for studying conditions with very low incidence or prevalence

•  Cross-sectional study: the presence or absence of disease and other
variables are determined in each member of the study population or in a
representative sample at a particular time. The co-occurrence of a variable
and the disease can be examined.
a.  Disease prevalence rather than incidence is recorded
b.  The temporal sequence of cause and effect cannot usually be determined in a
cross-sectional study
c.  Example: who in the community now has treatment-resistant TB
FA 2012: 52.1 • FA 2011: 50.1 • FA 2010: 52 • BE01- 6
ME 3e: 35
Cohort Study
Cohort Study
Cohort study: population group of those who have been exposed to risk factor
is identified and followed over time and compared with a group not exposed to
the risk factor. Outcome is disease incidence in each group (e.g., following a
group of individuals forward in time and comparing the development of lung
cancer in those who smoke and in those who don’t smoke).

•  Prospective; subjects tracked forward in time
•  Can determine incidence and causal relationships
•  Must follow population long enough for incidence to appear
FA 2012: 52.1 • FA 2011: 50.1 • FA 2010: 52 • BE01- 7
ME 3e: 34
Difference between studies by time
Difference between studies by time
Differentiating Study Types by Time
FA 2012: 52.1 • FA 2011: 50.1 • FA 2010: 52 • BE01- 8
ME 3e: 35
Twin and Adoption Studies
Twin and Adoption Studies
•  Measuring inheritance of a genetic disease/disorder:
•  Twins: monozygotic and dizygotic
•  Adoption: nature vs. nurture

FA 2012: 52.1 • FA 2011: 50.1 • FA 2010: 52 BE01- 9
Diagnostic Tests
Diagnostic Tests
Diagnostic Tests
–  Will be covered on the exam
–  Pregnancy test example (don’t want false positive, but really don’t want a
false negative ! will take risks, etc)
–  Know this table (Table 1-4):
FA 2012: 53.1 • FA 2011: 51.1 • FA 2010: 53 BE01- 10
Sensitivity
Sensitivity
Sensitivity: the probability of correctly identifying a case of disease. Sensitivity
is the proportion of truly diseased persons in the screened population
who are identified as diseased by the screening test. This is also known
as the “true positive rate.”
TP
Sensitivity =
TP+FN

true positives/(true positives + false negatives)
–  Measures only the distribution of persons with disease
–  Uses data from the left column (Table 1-4)
–  Note: 1-sensitivity = false negative rate
FA 2012: 53.1 • FA 2011: 51.1 • FA 2010: 53 • BE01- 11
ME 3e: 34
Specificity
Specificity
Specificity: the probability of correctly identifying disease-free persons.
Specificity is the proportion of truly nondiseased persons who are identified as
nondiseased by the screening test. This is also known as the “true negative
rate.”
TN
Specificity =
TN+FP

true negatives/(true negatives + false positives)
–  Measures only the distribution of persons who are disease-free
–  Uses data from the right column (Table 1-4)
–  Note: 1-specificity = false positive rate
FA 2012: 53.1 • FA 2011: 51.1 • FA 2010: 53 • BE01- 12
ME 3e: 34
Positive Predictive Value
Positive Predictive Value
Positive predictive value: the probability of disease in a person who receives a
positive test result. The probability that a person with a positive test is a true
positive. (i.e., has the disease) is referred to as the “predictive value of a
positive test.”
TP
Positive predictive value =
TP+FP

true positives/(true positives + false positives)
–  Measures only the distribution of persons who receive a positive test
result
–  Uses data from the top row of the (Table 1-4)
FA 2012: 53.1 • FA 2011: 51.1 • FA 2010: 53 • BE01- 13
ME 3e: 34
Negative Predictive Value
Negative Predictive Value
Negative predictive value: the probability of no disease in a person who
receives a negative test result. The probability that a person with a negative
test is a true negative (i.e., does not have the disease) is referred to as the
“predictive value of a negative test.”
TN
Negative predictive value =
TN+FN

true negatives/(true negatives + false negatives)
–  Measures only the distribution of persons who receive a negative test
result
–  Uses data from the bottom row (Table 1-4)
FA 2012: 53.1 • FA 2011: 51.1 • FA 2010: 53 • BE01- 14
ME 3e: 34
Meta-analysis
Meta-analysis
•  Meta-analysis:
a.  A statistical way of combining the results of many studies to
produce one overall conclusion
b.  A mathematic literature review
–  Highest level of clinical evidence used to make an argument for
or against something
FA 2012: 58.2 • FA 2011: 50.3 • FA 2010: 52 BE01- 15
Accuracy and Precision
Accuracy and Precision
Accuracy: total percentage correctly selected; the degree to which a
measurement, or an estimate based on measurements, represents the true
value of the attribute that is being measured.
TP + TN
Accuracy =
TP + FP + TN + FN

(true positives + true negatives)/total screened patients

Precision: ability of a test to measure something consistently, either across
testing situations (test-retest reliability), within a test (split-half reliability), or
across judges (inter-rater reliability)
–  Reliability: think of the clustering of rifle shots at a target
FA 2012: 55.1 • FA 2011: 52.3 • FA 2010: 54 • BE01- 16
ME 3e: 34
Odds Ratio
Odds Ratio
Odds ratio: looks at the increased odds of getting a disease with exposure to a
risk factor versus nonexposure to that factor

Disease Present Disease Absent
(+) (-)

Exposed group (risk factor +) A B

Nonexposed group (risk factor -, control) C D

A/B AD
Odds Ratio = =
C/D BC

–  Odds of having disease in exposed group divided by odds of having
disease in nonexposed group
–  The odds that a person with lung cancer was a smoker versus the odds
that a person without lung cancer was a smoker
–  Odds ratio does not so much predict disease as estimate the strength of a
risk factor
FA 2012: 54.2 • FA 2011: 52.2 • FA 2010: 54 • BE01- 17
ME 3e: 35
Relative Risk
Relative Risk
Relative risk (RR): comparative probability asking “How much more likely?”

Disease Present Disease Absent
(+) (-)

Exposed group (risk factor +) A B

Nonexpos ed group (risk factor -, control) C D

A/(A+B)
Relative risk (RR) =
C/(C+D)

–  Incidence rate of exposed group divided by the incidence rate of the
unexposed group
–  How much greater chance does one group have of contracting the
disease compared with the other group?
–  For statistical analysis, yields a p-value
FA 2012: 54.2 • FA 2011: 52.2 • FA 2010: 54 • BE01- 18
ME 3e: 35
Attributable Risk
Attributable Risk
Attributable risk (AR): comparative probability asking “How many more cases in
one group?”
Disease Present Disease Absent
(+) (-)
Exposed g roup (risk factor +) A B
Nonexpos ed group (risk factor -, control) C D

A C
Attributable risk (AR) = !
A+B C+D

–  Incidence rate of exposed group minus the incidence rate of the
unexposed group
–  Note that both relative risk and attributable risk tell us if there are
differences, but do not tell us why those differences exist.
FA 2012: 54.2 • FA 2011: 52.2 • FA 2010: 54 • BE01- 19
ME 3e: 35
Types of Bias in Research
Types of Bias in Research
FA 2012: 56.1 • FA 2011: 53.1 • FA 2010: 55 • BE01- 20
ME 3e: 35