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epidemiology > Revision powerpoint - everything we need to know > Flashcards

Revision powerpoint - everything we need to know Flashcards

1
Q

describe the epidemiological transition

A

changes in level and causes of mortality
decline in total mortality
reduction in infectious disease
increases relative role of chronic non-communicable disease - cancer, CVS, chronic resp disease, diabetes

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2
Q

dynamic nature of the epidemiological transiotion

A

result of demographic, socioeconomic, technological, cultural , env and biological changes
small pox disappear, AIDS appear, TB denge re-emerge
decline in stomach cancer, rise and fall of lung cancer
shift from stroke to heart disease

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3
Q

most commonly diagnosed cancer

A

lung, breast, colorectal

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4
Q

most common cause of cancer death

A

lung liver and stomach

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5
Q

burden of non-communicable disease

A

1/3 cancers likely to be preventable through small number of lifestyle and environmental approaches
smoking largest preventable casue of cancer worls wide
burden shift to less developed countries
incidence caries between populations

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6
Q

cancer

A

major problem
>25% deaths world woide
in 2010 15.1% deaths - 8million died
canvcer rates in migrants converge to local rates
modifyable risk factors
take up to 20 years to appear
current rates affected by changes and exposure that took place in the past

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7
Q

cancer risk factors

A 
smoking 
low intake fruit/veg 
alcohol
unsafe sex
obesity
physical inactivity 
contaminated injections 
urban air pollution 
indoor smoke from household solid food use
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8
Q

cancer from infections

A 
hepititus - liver 
H pylori - gastric HPV - cervical 
EBV - hodgkins lymphoma, stomach cancer 
HIV - AIDS defining malignancies, Kaposi sarcoma, non-Hodgkin lymphoma, cervical cancer 
schistosomes - bladder cancer
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9
Q

CVD

A

CHD and stroke 1st and 2nd cause specific mortality ww
29.5% all deaths - 15.6 million
more in developing world
low in japan
high and rising rates in formally socialist economies - Europe and middle east
rates higher in men than women - gap shrinking
trends declining in many countries recently
patterns suggest environment rather than genetics

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10
Q

risk factors for CVD

A

high bp
tabacco smoking
cholesterol level

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11
Q

commonest non-infectious cause of world mortality

A

ischemic heart disease

cerebrovascular disease

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12
Q

where are infectious disease the leading cause of death

A

sub sarharan Africa

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13
Q

6 commonest infectious cause of world mortality and some underlying high incidence

A 
lower respiratory infections - 3.9m 
HIV 2.8m 
diarrheal disease - 1.8m 
TB - 1.6m 
malaria 1.2m 
measles 0.6m
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14
Q

why is there a change in mortality and incidence of infectious disease

A 
treatment 
exposure 
diagnosis 
screening 
treat and diagnose early - mortality decrease but incidence increase
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15
Q

case

A

Person who has the disease, health disorder or suffers the event of interest

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16
Q

incidence

A

Number of new cases of a disease within a specified time interval - probability or risk of developing a disease in a specific time period

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17
Q

prevalence

A

Frequency of a disease in a population at a point in time (point prevalence) - proportion and measures status, for planning, compare burden between populations

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18
Q

mortality

A

Number of deaths attributed to a specific condition in a given time period - number deaths per 1000 individuals per year

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19
Q

morbidity

A

Number of cases of ill health, complications, side effects attributed to a specific condition over a particular time period.
- state of being unhealthy or diseased

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20
Q

drivers of aids epidemic, success and challenges of the response

A

access to anti-retroviral therapy
effective HIV prevention methods - safe sex
decline in prevalence in pregnant women
to reduce incidence further need a vaccine
incident increase because of better diagnosis and better treatment - incidence increase and mortality decrease

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21
Q

HIV infection - prevalence and mortality

A

incidence rising
mortaklity reduced because of HAART
duration of disease increasing
steep increase in prevalence

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22
Q

routine data

A

data routinely collected

recorded in ongoing systematic way - for administrative or statuary purposes without specific research questions

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23
Q

examples of routine data

A

deaths, hospital admissions, screening, immunisation uptakes, census counst, GP consultation data

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24
Q

major sources routine data in UK

A

2001 Census
Health Survey for England
NHS Inpatient Survey on patient experience

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25
Q

advantages of routine data

A 
Relatively cheap 
Already collected and available 
Standardised collection procedures 
Relatively comprehensive – population coverage, large numbers 
Wide range of recorded items 
Available for past years
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26
Q

disadvantages

A 
not answer qn 
incomplete ascertainment 
variable quality 
validity variable 
disease labling vary 
need careful interpretation
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27
Q

SMR

A

ratio between observed number of deaths in a study population and number of deaths would be expected - accounting for age and sex

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28
Q

SMR =

A

no observed deaths/no expected deaths if same age specific rates as standard population

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29
Q

age standardised death rates

A

measure how many people die each year and why they have dies assess effectiveness of a country’s health system
along with assessing how injuries and diseases affect the living - determine if focussing on the right thing that will prevent reducable deaths and disease

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30
Q

main approaches of intervention to improve health

A

clinical intervention - biomedical, prevention
health education
healthy public policy eg smoking
community development

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31
Q

primordial prevention

A

prevention of factors which promote emergence of lifestyles, behaviours, exposure patterns which contribute to the risk of disease

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32
Q

primary prevention

A

prevent the onset of disease - limit exposure of risk factor by individual behaviour change and actions in the community
health promotion and specific protection

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33
Q

secondary prevention

A

halt progression once illness is established - prompt effective treatment
special consideration for asymptomatic

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34
Q

tertiary prevention

A

rehab of people with established disease to minimise residual disabiliyu and complications
QOL

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35
Q

sample

A

group of people, objects or items taken from a larger population for measurement

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36
Q

variation

A

variation of observations in a single sample

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37
Q

what can you get from a sample

A

estimates of true underlying risks

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38
Q

problem with sample

A

risk that association is die to chance

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39
Q

p value

A

probability that the null hypothesis is tru

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40
Q

null hypothesis

A

hypothesis that there is no significance

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41
Q

attributable risk

A

difference in rate of a condition between exposed and unexposed population - guantifies the risk - fact

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42
Q

relative risk

A

ratio of the probability of an event occurring in exposed group to probability of event occurring in comparison in a non-exposed group
estimates magnitude of association

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43
Q

attributable risk =

A

incidence in exposed- incidence in unexposed

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44
Q

relative risk =

A

incidence in exposed/incidence in unexpoded

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45
Q

odds ratio

A

likelihood of having exposure if you have disease relative to having exposure if no disease

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46
Q

OR =

A

odds of exposure in cases/odds off exposure in controls

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47
Q

confounding

A

mixing of effects between exposure, the disease and a 3rd factor

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48
Q

dealing with confounding at desighn

A

randomisation - RCT

restriction/matching - case control

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49
Q

dealing with confounding in analysis

A

stratification - split analysis by age group
standardisation
regression - build statistical model

50
Q

EBM

A

based on critical appraisal
dr should use critically appraised information in clinical practice for optimal care
developed over 30 years

51
Q

why EBM matters to clinicians

A 
Patient 
Medical Knowledge 
Practice-Based Learning and Improvement 
Interpersonal and Communication skills 
Professionalism
52
Q

association

A

Association refers to the statistical dependence between two variables. Consider chance, bias, confounding, cause (CBCC)

53
Q

chance

A

from samples not whole pop

54
Q

bias

A

systematic - measurement/selection

55
Q

casual effect

A

A simple way to remember the meaning ofcausal effectis: B happened because of A, and the outcome of B is strong or weak depending how much of or how well A worked.
Cause-effect relationship
Judgement is based on a chain of logic that addresses two main areas:
-Observed association between an exposure and a disease is valid
-Totality of evidence taken from a number of sources supports a judgement of causality

56
Q

power calculations

A

to calculate minimum sample size for acceptable outcome

57
Q

responder bias

A

prevented by single blinding

58
Q

ecological studies

A

measure prevalence and incidence of disease, particularly when disease is rare.
- observationalstudydefined by the level at which data are analysed, namely at the population or group level, rather than individual level.

59
Q

case report

A

follow up of an individual patient

60
Q

descriptive/cross sectional

A

: Observationalstudythat analyzes data collected from a population, or a representative subset, at a specific point in time

61
Q

strength

A

Measured by the magnitude of relative risk. Strong association is more likely to be causal and a weak association could be more easily the result of confounding or bias

62
Q

consistency

A

similar results in similar studies

63
Q

specificity - Bradford hill

A

particular exposure increasing the risk of a certain disease but not the risk of other diseases

64
Q

temporal relationship

A

For a putative risk factor to be the cause of a disease, it has to precede the disease.

65
Q

dose response relationship

A

Increasing levels of exposure lead to increasing risks of disease shows evidence of a causal effect.

66
Q

plausibility

A

consistant with other studies

67
Q

coherence

A

cause and effect doesn’t conflict with what is known with the natural history

68
Q

experimental evidence

A

On humans (rarely available) or animals

69
Q

analogy

A

Provides a source of more elaborate hypotheses about the association in question. Absence only reflects lack of imagination or experience.

70
Q

clinical trial

A

A planned experiment in humans designed to measure the effectiveness of an intervention (usually a drug but can be surgical procedures, vaccine, complementary therapy etc)

71
Q

features of a clinical trial

A

Define your intervention
Define your comparator • Placebo • Alternative treatment • Standard of care
Define your inclusion criteria
Define your exclusion criteria
Experimental study
Must contain a control group- to be sure why the outcome has occurred (could be due to the effectiveness of the new treatment or happened anyway)
Prospective: participants are followed through time
Patients are enrolled, treated and followed over the same period of time
Patients should be randomised –to eliminate allocation bias

72
Q

block randomisation

A

assign people to group A or B randomly

73
Q

stratification

A

by important characteristic

74
Q

minimisation

A

adaptive stratification - calculates imbalance and allocates to maintain balance

75
Q

biases in clinical trials and how to avoid them

A

allocation bias - randomisation
measurement bias - blinding
reporting bias - selective reporting

76
Q

consort

A

consolidated standards of reporting trials - ensures papers about trials incude all relevant info

77
Q

outcomes of a clinical trial

A

The outcomes are presented in terms of efficacy (the true biological effect of a treatment) or effectiveness (effect of a treatment when actually used in “normal” practice).

78
Q

experimental event rate

A

incidence in intervention arm

79
Q

control event rate

A

incidence in control arm

80
Q

relative risk

A

eer/cer

81
Q

relative reduction

A

cer-eer/cer

82
Q

absolute risk reduction (ARR)

A

cer-eer

83
Q

number needed to treat

A

1/ARR

84
Q

what is included in a summary of information from a paper

A 
Why did they do it?
What did they do?
What did they find?
What did they conclude?
In your opinion, was the study conducted well?
85
Q

critical appraisal cchecklist

A 
Question – Relevant? Hypothesis?
Design – appropriate?
Population – sample size?
Methods – measure? Appropriate? 
Analysis – appropriate statistical tests?
Confounders
Bias – measurement, selection
Ethics – ethical? Consent?
Interpretation – casual inference (Bradford Hill
86
Q

guidelines for different studies

A

RCT - consort
observational studies - STROBE
systematic reviews - PRISMA/MOOSE

87
Q

all or non-case series

A

when all patients died before a new therapy was introduced, yet following its introduction, all patients receiving the treatment survived

88
Q

why conduct a systematic review

A

high volume of data that needs to be considered

single studies are inefficient

89
Q

meta analysis

A

combine the published estimates of effects from each study to generate a pooled risk estimate

90
Q

what is a systematic review

A

review of a clearly formulated question that uses systematic and explicit methods to identify, select and critically appraise relevant research and analyse data from studies that are collected in the review

91
Q

stages of systematic review

A

1 - planning
2 - identify research, select studies, study quaaltity assessment
3 - report and dissemination, study details abstracted and details tabulated to show summary of findings - estimate overall effect using a meta analysis

92
Q

meta analysis

A

combine the published estimates of effects from each study to generate a pooled risk estimate
if too heterogenous might be inappropriate to pool

93
Q

why do a meta analysis

A

more reliable and precise estimate of effect
difference between studies identified and explored
get pooled weighted average

94
Q

presenting a meta analysis

A

forest plot
each study represented with a box and line
size of box = weight given to the study
line = 95% confidence interval
overall estimate is the diamond
centre of diamond and line - summary effect estimate
width of the diamond = CI around estimate

95
Q

bias and limitation of systematic review

A

publication bias
inconsistency
low study quality
heterogeneity

96
Q

publication biasd

A

cause data to be over or under estimated

explored with funnel plots - show if link between study size/precision and the effect of the estimate

97
Q

what is screening

A

investigating apparently healthy individuals to detect unrecognised disease or its precursers so measures can be taken to prevent or delay the development of disease or improve prognosis

98
Q

why screen

A

when early diagnosis = better prognosis
high risk - intervention = better prognosis
identification of those posing risk to others - eg infectious disease eg Hep B

99
Q

mass screening programs in the UK

A 
cervical cancer
breast cancer 
bowel cancer 
abdominal aortic aneurysm 
diabetic eye screening
100
Q

cervical screening

A

every 3yrs 25-49

5yrs - 50-64

101
Q

breast screening

A

3yrds 50-70

>70 can self refer

102
Q

bowel screening

A

2yrs men and women 60-74

103
Q

abdominal aortic aneurysm

A

men 65th year

104
Q

diabetic eye screening

A

people with T1/T2 DM >12

105
Q

validity of screening test

A

ability to distinguish between those with the condition and those without

106
Q

gold standard

A

a recognised way of determining who has the disease

107
Q

sensitivity

A

ability of test to correctly identify people with the disease (true positives)

108
Q

specificity

A

Ability of the test to correctly identify people without the disease (ability to exclude true negatives)

109
Q

predictive value

A

Proportion of test results that are correct

dependent on the sensitivity and specificity and the prevalence of the condition in the population

110
Q

+ve predictive value

A

likelihood that a patient with a positive test result will actually have the disease

111
Q

-ve predictive value

A

likelihood that a patient with a negative test result will not have the disease

112
Q

receiver operator characteristics curves

A

are used to determine a cut-off value for a diagnostic or screening test. Y axis- sensitivity vs 1-specificty (x-asis)

113
Q

how do you choose cut off value

A

is informed by the attempt to maximise sensitivity and specificity

114
Q

criteria for screening

A 
feasibility 
effective
selection bias
lead time bias 
length time bias 
cost 
ethics
115
Q

ethics

A
  • May harm as well as benefit the individual
  • Risks of the test
  • Risks of subsequent diagnostic tests
  • Risks of subsequent treatment
  • False positive result causes unnecessary anxiety
  • False negative result will give false reassurance
116
Q

feasibity

A

easy to get attendance
acceptable
facilities for diagnostic tests

117
Q

effectiveness

A

extent it affects subsequent outcomes

118
Q

selection bias

A

people who participate are different to those that don’t

119
Q

lead tiem bias

A

improvement really due to earlier date of diagnosis

120
Q

length time bias

A

some conditions slower in developing to a health threatening phase - more likely to be detected at a stage that has favourable prognosis - false conclusion that screening is beneficial

121
Q

cost

A

includes the diagnostic test and treatment in comparison to costs of treatment of more advanced disease

epidemiology (40 decks)

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