Epi Flashcards
(185 cards)
0
Q
Which study design controls all con founders?
A
RCT
1
Q
Stratification
A
Analyses patient subgroups separately and then weighted average
2
Q
Multivariable regression
A
Takes into account a number of confoundeds at the same time
3
Q
Single estimate of stratification
A
Mantel haenzel
4
Q
Ecological fallacy
A
Average characteristics of a population
5
Q
What can you measure in cross sectional?
A
Prevalence
NOT incidence
6
Q
What do we calculate with case control?
A
Odds ratio
7
Q
Bias in case control
A
Reverse causality
Selection bias
Measurement- recall and interviewer
8
Q
Bias in ecological
A
Selection
Measurement
Reverse causality
9
Q
Trend test
A
Statistical
Presence of a linear increase or decrease in risk associated with increase in exposure
Binary
10
Q
Trend test 2 effects
A
Dose response effect
Threshold effect
11
Q
Cohort bias
A
Reverse causality Selection Loss to follow up Recall Interviewer
12
Q
Inclusion or exclusion criteria in rct causes
A
Poor external validity
13
Q
Good chance of detecting a clinically significant effect
A
Power more than 80%
14
Q
Not achieving planned sample size
A
High risk of missing a clinically important effect
Can only be published if it proves evidence of an effect
15
Q
Internal validity
A
The intervention caused the outcome or an observed outcome
16
Q
Construct validity
A
If what you observed is what you wanted to observe
Or what you did is what you wanted to do.
17
Q
Minimum effect size
A
Should be big enough to detect the smallest effect that is clinically important
18
Q
The probability of correctly rejecting the null when the treatment has an effect
A
Power
19
Q
Outcome reporter bias
A
Form of publication
Only present things that support
20
Q
Contamination
A
Cluster rcts
21
Q
Interim analysis
A
If study over years
Data monitoring committee
22
Q
Disadvantages of interim analyses
A
Open to abuse
Over estimate treatment effect
Completed by confidential committee independent of study researchers
23
Q
Number needed to harm
A
Round down
24
Number needed to benefit
Round up
25
Bias in rct
Selection
Performance
Detection
Attribution
26
Concealment is not
Blinding
27
Attrition bias
Use an itt
Patients analyses to groups they originally allocated not on whether they completed
Only unbiased up confounded estimate of effectiveness
Reflects reality
Public health impact
28
Missing data can be assessed with
Sensitivity analysis
29
Sensitivity analysis
Primary analysis
Then repeated with missing data filled in (assumed)
If results same as analysis then they are robust
If different then must use caution
30
Itt minimizes
Attrition bias
31
Consort framework
Framework for reporting trials
32
Forest plot boxes
Draw attention to studies with greatest weight
33
Forest plot diamond
Overall summary estimate
34
Vertical unbroken line forest plot
Null wave
35
Data extraction done by
2+ independent observers
36
Prisma statement
Guidance on what to include in systematic review
38
Examples of fixed effect
Hanzel
39
Basics of fixed effect
Assumes one true effect weighted average
Any deviation is due to chance or sampling error
Only looks at variation within samples
40
Examples of randome effect
Dersimonian
41
Basics of random effects
Assumes heterogeneity
Within study variance and between studies
Wider range
42
Weighted average
Bigger weight to bigger studies
| Weights use the inverse of the variance of treatment effect
43
Between study variance
Tsquared
| Derived from q
44
Fixed effect weight
W=1/v
45
Random effects weight
Includes inter study variance
46
Random effect weights are
Smaller and closer to each other than fixed
47
Fixed effect
Assumes studies are all measuring same treatment effect
48
Time-trade-off
Respondents are asked to choose between remaining in a state of ill health for a period of time, or being restored to perfect health but having a shorter life expectancy.
49
Standard gamble
Respondents are asked to choose between remaining in a state of ill health for a period of time, or choosing a medical intervention which has a chance of either restoring them to perfect health, or killing them.
50
Visual analogue scale
Respondents are asked to rate a state of ill health on a scale from 0 to 100, with 0 representing being dead and 100 representing perfect health. This method has the advantage of being the easiest to ask, but is the most subjective.
51
the cost effectiveness plane
Cost on y and effective on x
52
Dominant
more effective and less costly (South-East)
53
Dominated
expensive and cheaper (North-West)
54
Incremental cost-effectiveness
difference in cost divited by difference in effectiveness.
| up to reader to decide cost-effective.
55
ICER can be misleading unless...
one intervention is more expensive and more effective.
56
Net monetary benefit
required to know how much NHS is able to pay per QALY
57
Statistical variability in economic evaluation
due to small sizes, high variability of costs and missing data
58
Cost effectiveness acceptability curve
a sensitivity analysis in economic evaluation
59
one way sensitivity analysis
estimates for each uncertainty varied one at a time to investigate the impact on the results.
60
scenario analysis
best case
| worst case
61
sensitivity
probability of a + test in people with the disease
62
specificity
probability of a - trest in people without the disease
63
SnNout
test has a high sensitivity-
| a neg result would rule out the disease
64
SpPin
test has high specificity-
| a pos result would rule disease in.
65
when 2 tests are equally costly and convenient we can use the
Likelihood ratio
66
NPV
probability of being disease free if test result is negative
67
spectrum bias
diagnostic test only finds barn door cases from the controls
68
work-up bias
gold standard is expensive, risky and unpleasant
| cases who test + have gold standard then we underestimate the false -ves and overestimate the true positives
69
likelihood ratio (+)
sensitivity/(1-spec)
70
likelihood ratio (-)
(1-sensitivity)/spec
71
likelihood ratios
the further away from the null (1) the more informative the test.
72
LR=1
equal to chance
73
LR=1.5
greater than chance
74
when 2 tests are equally costly and conveneient we can use the
Likelihood ratio
75
deductive
quantitative
76
inductive
qualitative
77
depth
qualitative
78
dependability
data reliability and dependability.
codes?
independent coding?
triangulation?
79
qualitative data collection methods
observation
interviews
focus groups
80
snowballing
qualitative
81
max variation sampling
sample for heterogeneity
| the researcher selects a small number of units or cases that maximize the diversity relevant to the research question.
82
negative/deviant case sampling
This involves searching for and discussing elements of the data that do not support or appear to contradict patterns or explanations that are emerging from data analysis.
Deviant case analysis is a process for refining an analysis until it can explain or account for a majority of cases.
83
saturation
now themes no longer arise
84
QALY less than 0?
Worse than death
85
credibility
plausible and trustworthy
| been analysed? and grouped.
86
reflexivity
awareness of researchers contribution to the construction of meaning throughout the research
(can't remain 'outside' when conducting qualitative)
87
dependability
data reliability and dependability.
codes?
independent coding?
triangulation?
88
CASP criteria
to help appraise research
qualitative and quantitative
Critical Appraisal Skills Programme assessment criteria
89
DIE CIDRE
```
Do nothing
Inform
Enable choice
Change default policy
Incentives
Disincentives
Restrict choice
Eliminate choice
```
90
QALY questionairres
EuroQoi
HUI
SF6D
91
CPSPC
```
Concieved
Performed
Submitted.
Published
Cited
```
92
QALY 0
Dead
93
QALY less than 0?
Worse than death
94
Discounting leads to
down-weighting the cost/benefit in future years
95
Compound discount per year?
3.5%
96
Positive time preference
good things now
97
Technical efficiency
increases survival now
| questionable effect on quality of life
98
Allocative efficiency
Which is better? A or B?
99
Small study effect
Small studies show bigger effects than larger
(due to pub/reporting bias)
type of heterogeneity
100
CPSPC
```
Concieved
Performed
Submitted.
Published
Cited
```
101
Sensitivity analysis for heterogeneity
get rid of low quality ones
102
subgroup analysis for heterogeneity
does the effect differ across the sub groups?
103
Measure of heterogeneity
Q
| evidence for heterogeneity
104
What does the Q mean?
Nothing on its own
Need the P value.
p will disprove the null hypothesis that there is no heterogeneity
105
I^2 illustrates
the MAGNITUDE of the heterogeneity
106
Examples of fixed effect
Manetl
Peto
Inverse variance
107
Examples of random effect
Dersimionian L.
108
Culmulative effects life course
As you age you get more risks
109
gender inequality
NOT explained by inherent physiological changes
110
RII
assumes linear relationship between poverty and mortality
111
RII=
magnitude of the inequality
112
SII=
absolute difference
113
RII=1
no RELATIVE difference
114
SII=0
no ABSOLUTE difference
115
Deprivation indicator
small geographical areas
ecological measure
based on census- derived variables.
116
4 inequalities
gender
SEP
ethnicity
geography
117
Population strategy
treat everyone and protect those that are low risk
118
High risk strategy
only treat those at high risk
| might miss some who present slowly.
119
Prevention paradox
contradictory situation where the majority of cases of a disease come from a population at low or moderate risk of that disease, and only a minority of cases come from the high risk population (of the same disease)
120
Rule of rescue
an ethical imperative to save individual lives even when money might be more efficiently spent to prevent deaths in the larger population
121
ICER rejected over
30K per QALY
122
20-30K per QALY?
Only innovative, Proven benefit
123
Shadow price
threshold which you will pay under
124
League table
rank everything and most cost effective on top
125
Order of priority setting
```
NICE
Regional
Local commissioning boards
PCT
Hospitals
```
Done annually
126
Explicit priority setting
tell the patient about ALL options even unavailable
127
Implicit priority setting
only talk about the ones that are available.
128
3 aims of public health
Protection
Improvement
Service
(PIS easy)
129
Bradford Hill criteria
```
Temporal
Strength of association
Consistency
Biological gradient
Reversibility
Specificity
```
130
Ecological fallacy
the average person is not equal to all individuals
131
error type 1
incorrect rejection of the null
132
error type 2
failure to reject a false null.
133
non-differential selection bias
non-generalizable
134
differential selection bias
over or under estimation
135
Performance bias
unequal care because dr. knows
136
Detection bias
The doctor's views affect the measurements
137
NNTB round
up
138
NNTH round
down
139
selection bias not possible in
cohort
140
stratification in confounding
estimates association between exposure and disease.
| different subgroups then sweighted average.
141
Multivariable models
a number of confounders at once.
142
correlation
positive or negative.
| correlation coefficient is the gradient of the line.
143
Regression
mathematical y=mx+c
144
PH outcome framework
improve determinants of health
improve health
protect health
health care ph and preventing premature mortality.
145
Joint strategic Needs assessment
demographic changes (Population now)
services appropriately tailored (Provisions now)
any unmet needs? (Shortages now)
pressure for future? (Future)
146
Power
the strength of the results to be against the null
| dependent on sample size
147
Concealment
allocation sequence
148
Basic reproduction rate
R0
the larger the value, the more difficult to control
(secondary cases from primary)
149
Effective reproduction number
Ro x proportion susceptible
150
Control:
reduce transmission
151
Eliminate
get transmission near 0
152
Eradicate
transmission=0
153
DALYs have reduced with all infections except
HIV and malaria
154
CIC for an outbreak
control
investigate
communicate
155
mucosal vaccines are:
live
156
vaccine adjuvant
enhance response
157
preservatives
protect from bacteria/fungi
158
additives
stabilize from heat
159
Egg vaccines
flu and fever
160
MMR reaction
febrile convulsion
161
Hypotonic hyporesponsive episode
whooping cough
162
herd immunity is when
transmission less than 1 per case
163
polio transmission
oral- replicates in GI tract
lymph nodes- blood- meninges
replicates in mn and affects muscles.
164
Measles complications
```
Pneumonia
Otitis media
SSPE (fatal)
Encephalitis
Diarrhoea
```
165
Mumps complications
```
Pancreatitis
Oophritis
Orchitis
Neuro- deaf
Nephritis
```
166
standardised mortality ratio
indirect SMR=observed deaths/expected*100
167
killed immunization
DTaP
168
conjucated vaccine
HiB
Men C
13PVC
169
cost effectiveness analysis
money differences/ health benefits measured by primary outcome
170
cost utility analysis
money differences/ health benefits measured in QALYs
171
cost benefit analysis
money differences/ health benefits valued in money
172
cost consequences study
money differences/outcomes *benefit or not
173
accuracy
how representative the sample is of the population (you are near the true value)
174
precision
amount of variation between samples.
| high precision means low variation
175
familiar aggregation
the tendency for a disease to more common in probands than the public.
176
Power
Calculated from type 2 error
177
Non inferiority trial
To be able to do a superiority trial or to get on the market
178
Equivalence trial
Set delta margins
| Margins fall within margins of other drug
179
Standard deviations
1- 68.3
2. 95.4
3. 99.7
180
Work up bias
Gold standard is painful expensive
| Only likely to do on worse cases
181
Consort
22 principles for rcts
182
Quorma
Meta analysis
183
Absolute risk reduction
__
184
Interval properties
To do with qaly
185
heritability
Proportion of total phenotypic variance attributable to genetic effects (h2);
for phenotypes arising from a large number of genetic loci.
h2= additive genetic variance / total variance
Often expressed as a %.
Can be estimated from extended pedigrees, nuclear families siblings, twins or adoptees.
Only applies to measured population; cannot be used to explain differences between populations
