Epi Midterm Review Flashcards
1
Q
Objectives of Epi
A
Distribution -frequencies -patterns Determinants -risk factors
2
Q
John Snow
A
Father of Epi
3
Q
3 Assumptions made by Epi
A
- Disease not random
- Investigation can lead to association, causes and prevention
- Making comparisons is cornerstone
4
Q
6 Core Functions
A
Public Health surveillance Field investigation Analytic studies Evaluation Linkages Policy development
5
Q
Population vs. Sample
A
Population is all ind making up common group from which a sample can be obtained
6
Q
Generalizability
A
Inferential statistics transposed from sample to full population
7
Q
Inferential Stats
A
Inferences made about random data relative to a sample
8
Q
Epidemic
A
Occurrence of disease clearly in excess of normal expectance
9
Q
Outbreak
A
AKA upsurge/cluster
An epidemic linked to a localized increase in occurrence of disease
10
Q
Pandemic
A
Epidemic occurring over very wide area, large number of people
11
Q
Endemic
A
Constant presence of a disease within given area or population in excess of normal levels in other areas
12
Q
Cluster
A
AKA outbreak
13
Q
2 Main stages of disease prevention
A
Primary - preventing disease
Secondary - Interrupts disease process
14
Q
MeSH
A
Medical Subject Headings
15
Q
Boolean terms
A
AND, OR, NOT
16
Q
CONSORT
A
Clinical trial checklist
17
Q
STROBE
A
Observational trial checklist
cohort, case-control, cross-sectional
18
Q
STARD
A
Diagnostic study checklist
19
Q
PRISMA
A
Systematic reviews/Meta-analyses checklist
20
Q
3 Characteristics of data
A
- Magnitude
- Interval
- Rational Zero
21
Q
Magnitude
A
Bigger is more, lower is less
22
Q
Interval
A
Equal, even spacing
Ex. time
23
Q
Nominal Data
A
No magnitude, No interval
Non-ranked categories
Ex. Sex, race, handed-ness
24
Q
Ordinal Data
A
Magnitude, No interval
Categories, ranking something
Ex. Pain scale
25
Interval Data
Magnitude and Interval
| Ex. height, weight, age, income, days until surgery
26
Mean
Average
27
Median
Value that divides group values into half
28
Mode
Most frequently occurring value
29
Variation
Difference between max and min
30
Spread or dispersion of data
```
Variance
Standard Deviation (square root of variance)
```
31
Graph Types
```
Pyramid
Stacked
Pie
Line Graph - trend
Scatter plot
Box plot
```
32
Null Hypothesis
H0
| Study hypothesis that states no true difference between groups being compared
33
Alternative Hypothesis
H1
| Hypothesis states there IS a true difference
34
P Score
Want less than 0.05 (5%) so it is a statistically significant result. NOT by chance
35
P < .05
Statistically significant, result is not by chance
| Reject null hypothesis
36
Type 1 Error
(alpha)
Rejecting null hypothesis when it is actually true
False positive
37
Type 2 Error
(beta)
| NOT rejecting null hypothesis when it is actually false. There is a real diff but you don't reject H0
38
Power
Ability of a study to find difference in study if it was there
39
Sample size
Larger increases power. More likely to find a difference if it is there
40
Sensitivity
Box A
| Proportion of time that a test is positive in pt that does have disease
41
Specificity
Box D
| How well test can detect absence of disease when in fact disease is absent
42
Diagnostic Accuracy
Proportion of time a pt is correctly identified as either having a disease or not having disease
43
Positive Likelihood Ratio
LR+
Probability of positive test in presence of disease
Sensitivity/1-Specificity
44
PPV
How accurately a positive test predicts presence of disease
45
Validity
Ability to accurately discern between those that have disease and those that don't
46
Internal validity
Extent to which results accurately reflect the true situation of study population
47
External validity
Extent results are applicable to other, non studied populations
48
Reliability
=Reproducibility
49
3 factors necessary to compare dz frequencies in diff popultions
number of people affected by disease
Size of the source population
Length of time population followed
50
Ratios
Division of 2 unrelated numbers
51
Risk
AKA : Attack rate, incidence, cumulative incidence
52
Common measure of disease frequency
```
Mortality rate
Death rate
Survival rate
Live birth rate
Fertility rate
```
53
Absolute Difference
Subtracting differences
54
ARR
How much is difference in risk attributed to your exposure
55
Observational
designs considered natural
Observe outcomes
Useful for unethical study designs
56
Experimental
Intervention
Can demonstrate causation
Investigator selects interventions
57
Advantages of Clinical
Cause precedes effect - shows causation
| Only design used by FDA for new drug/device
58
Disadvantages of Clinical
Cost
Time
Ethical
Generalizability
59
Simple study design
Subjects randomized once
| Usually to test one hypothesis
60
Factorial study design
Randomized at least twice
Multiple hypotheses
Disadv: risk of drop out, restricts generalizability
61
Parallel Study design
groups concurrently and parallel
| NOT cross-over
62
Cross-over study design
Groups serve as own control
1 person multiple data pts
Wash out period to reset to normal
63
Direct Endpoints
Most clinically relevant, publishable
| Ex death, stroke, hospitalization
64
Surrogate Markers
Number that is associated with bad outcome VS direct endpts
| Ex. cholesterol, BP
65
Blocked randomization
Make sure group is equal
1:1, 2:1, etc
ensures balance within each group
66
Stratified randomization
Ensures balance by known confounding variable
| ex. age, gender, disease severity
67
Placebo/Dummy
Inert treatments
| 30-50%
68
Hawthorne Effect
Desire of study subject to please investigator
69
Double Dummy
more than one placebo
70
Run in/Lead in phase
ALL study subjects given one or more placebos for initial therapy to determine baseline of disease
71
4 Principles of Bioethics
1. Autonomy
2. Beneficience
3. Justice
4. Nonmaleficence
72
Autonomy
self rule/determination
| ex. not in place is mental capacity, age
73
Beneficiance
Benefit/do good for patient
74
Justice
Equal fair treatment regardless of pt characteristics
75
Nonmaleficence
Do no harm
- withhold info
- lie
76
Consent
Agree to participate
| Legal age
77
Assent
Not able to consent, legal guardian must consent
78
Belmont Report
1978
1. Respect for persons
2. Beneficiene
3. Justice
79
IRB
Protect human subjects before study
OHRD is law above IRB, could mean jail
80
DSMB
Data safety and Monitoring Board
Assess for undue risk or benefit AFTER study starts
Can stop study early
81
Equipoise
Genuine confidence that an intervention may be worthwhile in order to use it in humans
-principal people who argue against placebo use
82
Full Board IRB
ALL drug trials
| Interventional trials with more than minimal/no risk to pts
83
Expedited IRB
Minimal risk and no pt identifiers
84
Exempt IRB
No pt identifiers, low/no risk, enviro, use of existing data/specimens
85
Kappa Statistic
Agreement between evaluators
+1 perfectly agree
-1 exactly opposite
86
Kappa Interpretation
.8-1 excellent
.6-.8 good
.4-.6 fair
0-.4 poor
87
Positive Post Hoc
If sub groups are pre-defined and NOT fishing
88
3 Factors for Sample Size
1. Anticipated difference between groups
2. Background rate of outcome
3. Alpha and Beta (power)
89
Ways to Handle Drop outs
1. Include them anyway
2. Ignore them
3. Treat them as "as treated" - move subject
90
Improving Adherence
Frequent follow ups
Treatment reminders
Med blister packs, dosage containers
