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ESA 1- HaDPop > HaDPop > Flashcards

HaDPop Flashcards

1
Q

What are the two approaches to the concept of causality?

A

Deterministic and Stochastic

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2
Q

What does the deterministic approach measure?

A

NAME?

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3
Q

How does the deterministic approach of causality validate the hypothesis?

A

By systematic observations to predict with certainty future events

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4
Q

What does the stochastic approach measure?

A

NAME?

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5
Q

How does the stochastic approach to causality assess the hypothesis?

A

By systematic observations to give the likelihood of future events

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6
Q

Based on the stochastic approach, does a significant association mean causality exists?

A

No

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7
Q

What is population-based risk?

A

How individuals infer their personal risk

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8
Q

What do population-based observational studies do?

A

Investigate the causes of disease

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9
Q

What is the purpose of population based interventions?

A

They treat and prevent disease

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10
Q

What is the purpose of population based intervention trials?

A

They evaluate drugs and interventions

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11
Q

Where is critical appraisal of evidence necessary?

A

To decide about causality

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12
Q

How useful is laboratory bases evidence in determining causality?

A

It is contributory, but neither necessary not sufficient

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13
Q

What can population based evidence give?

A

Association, but not causality

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14
Q

Where are the ‘universal’ sources of information?

A
  • Birth registration
  • Death registration
  • Population census
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15
Q

How often is the population census done?

A

Every 10 years

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16
Q

What is a census?

A

The simultaneous recording of demographic data by the government at a particular time, pertaining to all the persons who live in a particular territory

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17
Q

What does the census describe?

A

Both households and people

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18
Q

Who runs the census?

A

The government

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19
Q

What is the incentive to complete the census?

A

It is mandatory by law, and failure to complete is punishable by fine or imprisonment

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20
Q

What does the census cover?

A

A defined area at one time

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21
Q

Who fills out the census?

A

Personal enumeration, or a person in each household completes the census form

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22
Q

On what timescale is the census performed through a defined area?

A

Simultaneously

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23
Q

What does the census provide?

A

Universal coverage

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24
Q

What information can be obtained from the census?

A

NAME?

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25
Q

What can the population size be used for?

A

Measurements of rates

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26
Q

Why is it important to know the population structure?

A

To service needs

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27
Q

Give an example of population characteristics the government may need to know

A

Measures of deprivation

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28
Q

Give 5 measures of deprivation

A
  • Unemployment
  • Overcrowding
  • Lone pensioners
  • Single parents
  • Lack of basic amenities
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29
Q

What influences a population size?

A
  • Births
  • Deaths
  • Migration
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30
Q

Who provides birth notification?

A

An attendant at birth, usually the midwife

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31
Q

How quickly does a birth notification need to be submitted?

A

Within 36 hours

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32
Q

Where does a birth notification need to be submitted to?

A

The local Child Health Register

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33
Q

Why is birth notification important?

A

For relevant services such as immunisation

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34
Q

What is the incentive for carrying out birth registration?

A

It is required by law

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35
Q

Who registers a birth?

A

Parent

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36
Q

How soon does a birth need to be registered?

A

Within 42 days

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37
Q

Where should a birth be registered?

A

At a local Registrar for Births

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38
Q

What is the purpose of birth registration?

A
  • Statistical purposes

- Makes you identifiable

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39
Q

How does birth registration make you identifiable?

A

You get a birth certificate

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40
Q

What are the measures of fertility?

A

NAME?

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41
Q

What is the CBR?

A

The number of live births per 1000 population, including men, women, children and old people

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42
Q

What is the GFR?

A

The number of live births per 1000 females ages 15-44

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43
Q

What is the TPFR?

A

The average number of children born to a hypothetical women in her life

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44
Q

What is TRFR not influenced by?

A

The size of population in different age groups

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45
Q

How is TPFR calculated?

A

∑(all current age-specific fertility rates)

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46
Q

What does a TPFR of 2 mean?

A

Replacement

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47
Q

What does a TPFR of >2 mean?

A

A growing population

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48
Q

What is GFR affected by?

A

Age specific birth rates (ADBR) and age distribution within the 15-44 year olds

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49
Q

What does TPRF give each age?

A

Equal weighting in it’s calculation

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50
Q

What are the determinants of fertility?

A
  • Fecundity

- Fertility

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51
Q

What is fecundity?

A

The physical ability to reproduce

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52
Q

What decreases fecundity?

A

Increase in sterilisation and hysterectomies

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53
Q

What is fertility?

A

Realisation of the ability to reproduce

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54
Q

What is fertility based on?

A

Humans, not biological

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55
Q

What increases fertility?

A
  • Sexual activity

- Good economic climate

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56
Q

What decreases fertility?

A
  • Contraception

- Abortion

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57
Q

What does conceptions equal?

A

Live births + miscarriages + abortions

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58
Q

What is the CBR used for?

A

Describing the impact of births on populations

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59
Q

What is the GFR used for?

A

Comparing the fertility of female populations

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60
Q

What is TPFR used for?

A

Comparing the fertility of females without being influenced by age-group structure

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61
Q

Whos statutory obligation is death certification?

A

The attending doctor

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62
Q

What can happen if a doctor doesn’t provide death certification?

A

They can go to prison

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63
Q

What is a doctor legally required to do on the death certificate?

A

Provide information on likely cause(s) of death

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64
Q

What must a doctor do if the cause of death is unusual or uncertain?

A

Notify the Coroner’s Officer

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65
Q

Who must perform death registration?

A

A qualified informant, usually a relative

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66
Q

How quickly does death registration need to be performed?

A

Within 5 days

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67
Q

What does death registration require?

A

A Death Certificate from a doctor

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68
Q

What are the measures of mortality?

A

NAME?

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69
Q

What is the CDR?

A

The number of deaths per 1000 population

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70
Q

What is the ASDR?

A

The number of deaths per 1000 in an age group

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71
Q

What does the SMR do?

A

Compares the number of ‘observed’ deaths with the number of ‘expected’ deaths if the age-sex distribution of the populations were identical

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72
Q

What does SMR adjust for?

A

Age-sex distribution

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73
Q

What are the reasons for collecting mortality data?

A

NAME?

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74
Q

What do population estimates do?

A

Apply what is known about births, deaths and migration to the present

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75
Q

What do population projections do?

A

Estimate the future populations

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76
Q

What additional assumptions are made in population estimates?

A

About births, deaths and migration in the future

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77
Q

What questions does identification of health and healthcare necessitate?

A

NAME?

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78
Q

What does a trend involve?

A

The comparison of rates, which require a numerator and a denominator

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79
Q

What are rates often?

A

Per unit time

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80
Q

What does a trend imply?

A

A comparison over time

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81
Q

What can a trend be a comparison of, other that over time?

A

Comparison between places, across socio-economic groups etc., or a combination

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82
Q

What are the two types of errors that can occur in trend monitoring?

A
  • Numerator errors

- Denominator errors

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83
Q

What are some possible opportunities for numerator errors?

A
  • Death certification
  • Disease diagnosis
  • Classification or coding errors
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84
Q

What are some possible opportunities for denominator errors?

A
  • Population used
  • Population definition
  • Population count or estimate
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85
Q

What can trends be due to?

A
  • Chance (random) variation
  • Artefactual (systematic) reaosns
  • Real phenomenon
  • ‘Natural’ (epidemiological)
  • Medical care effects
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86
Q

What should be done when there is a dramatic change in trends?

A

Consider artefactual reasons before considering real phenomenon

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87
Q

What are some contentious issues?

A
  • Purpose
  • Users
  • Quality
  • Comparability
  • Relationship
  • Publication
  • Access
  • Funding
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88
Q

What are the potential purposes of scientific studies?

A

NAME?

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89
Q

Who are the possible users of information obtained from studies?

A

NAME?

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90
Q

What is the competition in quality of data?

A

Real-time data vs validated data

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91
Q

What is comparability of data in competition with?

A

Comparable vs customised

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92
Q

What are the possible relationships in data found in studies?

A

Integral vs indepedant

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93
Q

Where could data from studies be published?

A

NAME?

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94
Q

What is the conflict in access to data?

A

Data protection vs. freedom of information

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95
Q

What are the possible sources of funding for studies?

A

NAME?

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96
Q

What concepts does the ‘amount’ of disease have?

A
  • The number of new cases that occurred

- The number of people affected by the disease

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97
Q

What does the concept of amount of new disease focus on?

A

New events

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98
Q

When is the concept of number of new cases that occur useful?

A

When monitoring epidemics

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99
Q

What does the concept of number of people affected count?

A

The number of people with the disease, counting both old and new cases

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100
Q

What does the concept of number of people affected by the disease describe?

A

The burden of disease

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101
Q

Where is the measure of number of people affected by a disease useful?

A

As a measure of need for services

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102
Q

How do you calculate incidence rate?

A

New events / (person * time(yrs))

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103
Q

What is the unit for incidence rate?

A

Events per persons per year

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104
Q

Is prevalence a rate?

A

No, it’s a proportion

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105
Q

What is the denominator for prevalence?

A

Persons (not persons per time)

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106
Q

What kind of study is use to determine prevalence?

A

Cross sectional

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107
Q

What does an increase in incidence lead to?

A

An increase in prevalence

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108
Q

What does a cure, or death of patients lead to?

A

Lower prevalence

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109
Q

What does a longer survival rate lead to?

A

Increased prevalence

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110
Q

How can prevalence be calculated?

A
  • Incidence * length of disease

- Cases / population

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111
Q

What is incidence?

A

The measure of the populations average risk of disease

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112
Q

What exists within a population regarding risk of disease?

A

Variations in risk of disease between groups of people

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113
Q

Why are systemic variations in risk between people of great interest?

A

Because it can give clues about the aetiology (cause) of a disease

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114
Q

How can variations in prevalence be used to determine aetiology?

A

Can compare levels of exposure in two groups of people and try to identify the causal factor for a disease

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115
Q

What may be done after identifying the causal factor for a disease?

A

Try and prevent exposure, thus reducing incidence of disease

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116
Q

What is the incidence rate ratio (IRR)?

A

A comparison of incidence rates between groups with different levels of exposure

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117
Q

How is the IRR calculated?

A

Rate B (Exposed) / Rate A (Unexposed)

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118
Q

What is implied if the incidence rate in group B is higher than that in group A?

A

The difference in exposures was associated with the differences in rates of disease

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119
Q

How can efficacy of treatments be measured?

A

Incidence rate ratios can be used to compare the effects of two treatments, and decide which one is best

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120
Q

Give two examples of nuisance variations in risk of disease?

A

NAME?

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121
Q

What is the rate ratio for most diseases when comparing the rate old with rate young ?

A

> 1.0

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122
Q

Why is knowing that there is variation based on age and sex not that useful for prevention?

A

Whilst it may be possible to target prevention at particular age-sex groups, age and sex are not modifiable factors

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123
Q

What can confounding factors explain?

A

All or part of an apparent association between an exposure and a disease

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124
Q

Give two ways of dealing with confounding by age

A
  • Use age specific rate ratios

- Use standardised mortality ratios

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125
Q

How can using age specific rate ratios help deal with confounding by age?

A

With narrow age bands, little confounding due to age occurs

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126
Q

What is the problem with using age specific rate ratios?

A

Results are difficult to interpret as you get too many answers, as there is one for each age band

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127
Q

What does the SMR look at?

A

The rate ratio for two populations if age-sex structure of the two populations was the same

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128
Q

What is indirect SMR comparing?

A

The levels of mortality observed in a study population with the level of mortality expected if a standard reference populations age-sex specific ratios were applied to the study population age-sex groups

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129
Q

What does SMR account for?

A

Any age-sex confounding

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130
Q

How is SMR usually expressed?

A

As a %

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131
Q

What would a SMR of 100 mean?

A

There there is the same risk in the study population as in the standard reference population

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132
Q

What does a SMR of >100 mean?

A

A higher risk in the study population

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133
Q

How can SMRs be expressed if not a %?

A

Relative to 1.0

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134
Q

Essentially, what is the ‘observed’ value?

A

Our best estimate of the ‘true’ or ‘underlying’ tendency

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135
Q

What is a hypothesis?

A

A statement that an underlying tendency of scientific interest takes a particular quantitive value

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136
Q

What must be calculated in formal hypothesis testing?

A

The probability of getting an observation as extreme as, or more extreme as, the observed, assuming the stated null hypothesis is true

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137
Q

What happens if the probability of getting an observation as extreme as the observed is very small?

A

It is reasonable to conclude that the data and the stated null hypothesis are incompatible

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138
Q

What has happened if there is a very small probability that getting an observation as extreme as the one you observed?

A
  • Something very unlikely has happened or

- The stated hypothesis is wrong

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139
Q

What is the calculated probability of getting a value as extreme as the observed called?

A

P-value

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140
Q

When is an observation statistically significant?

A

When the p value≤ 0.5

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141
Q

What does a p value of >0.05 not mean?

A

That they null hypothesis has been proven

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142
Q

What are the limitations of hypothesis testing?

A
  • Rejecting a null hypothesis is not always useful
  • Statistical significance depends on sample size
  • Statistically significant doesn’t mean it’s clinically important
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143
Q

Why is rejecting a null hypothesis not always useful?

A

P≤ 0.05 is arbitrary

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144
Q

What is meant by P≤ 0.05 being arbitrary?

A

Nothing special happens between p=0.049 and p=0.051

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145
Q

What is it usual practice to hypothesis test again?

A

A null hypothesis

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146
Q

What is a null hypothesis?

A

A hypothesis assuming that two things are equal, or that there is no effect or difference

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147
Q

What information may be required by epidemiologists, and health service managers?

A
  • Underlying tendencies
  • What tendencies imply about the patterns of disease
  • Health care need in the general population
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148
Q

What is the 95% confidence interval?

A

The range within which we can be 95% certain that the ‘true’ value of the underlying tendency really lies

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149
Q

What is the range of the 95% CI centred on?

A

The observed value

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150
Q

Why is the range of the 95% CI centred on the observed value?

A

Because it is always out best guess at the ‘true’ underlying value, so the observed value always lies between the 95% CI

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151
Q

What are values in the 95% CI said to be?

A

‘Consistent with the data’

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152
Q

What happens if the null hypothesis value is consistent with the observed data?

A

Any observed difference from the null hypothesis may be due to chance

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153
Q

How can you decide wether the finding is statistically significant?

A

Using the 95% CI

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154
Q

How do you calculate 95% CI?

A
  • Calculate observed value of whatever you’re interested in
  • Calculate error factor
  • Lower 95% confidence limit = observed value / e.f.
  • Upper 95% confidence limit = observed value * e.f.
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155
Q

What happens as we get more data?

A

We get more sure about the ‘true’ underlying value

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156
Q

Why do we get more sure about the true underlying value as we get more data?

A

The e.f. gets smaller and the 95% CI gets narrower

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157
Q

What are the features of an ideal study?

A
  • Basic scientific method comparing ‘like with like’

- Two identical groups differing only in exposure of interest

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158
Q

What could be done if a study was ideal?

A

Differences can then reasonably be attributed to the exposure

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159
Q

Why can an ideal study not be achieved?

A

It’s impossible to get two identical groups of people differing only the exposure of interest, when exposure is linked to other factors

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160
Q

What can be done in an experiment?

A

Force all other factors to be identical

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161
Q

How can a study be randomised?

A

A randomised control trial

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162
Q

What can be done using a cohort study?

A

Measure and record any non-identical features

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163
Q

What is best, an experiment, randomisation or a cohort study?

A

An experiment, then randomisation

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164
Q

What must be counted in a cohort study?

A

Outcome events and person years, in exposed and unexposed groups

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165
Q

What are person-years?

A

The sum of the total time of everybody followed up in the study

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166
Q

Who must be recruited in a cohort study?

A

Outcome free individuals

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167
Q

What must the individuals recruited for a cohort study be classified into?

A

Exposed and unexposed categories

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168
Q

What are the advantages of cohort studies over routinely obtained data?

A
  • You can study exposures and personal characteristics that are not routinely collected
  • You can obtain more detailed information on outcomes or exposures
  • You can collect additional data on potentially confounding factors
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169
Q

What do all cohort studies involve?

A

Prospective follow up

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170
Q

What is counted on the follow up of cohort studies?

A

Person-years (p-y) and d (developed)

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171
Q

When may data collection begin in a cohort study?

A

NAME?

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172
Q

What is it called when data collection starts immediately or later in a cohort study?

A

Concurrent or prospective cohort study

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173
Q

What is it called when data is collected from the past in a cohort study?

A

Historical or retrospective study

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174
Q

How is a historical cohort study carried out?

A

Recruitment of outcome free individuals, classification of their exposure status and subsequent outcomes is done using historical data

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175
Q

How can comparisons be made in cohort studies?

A

Internally, or against external reference population

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176
Q

What does internal comparisons of cohort study data use?

A

IRR

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177
Q

What does external comparisons of cohort study data use?

A

SMR

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178
Q

Why is an SMR approach for a cohort study important?

A

Because cohort studies are usually conducted over long periods, often decades, so people age during the study

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179
Q

How is a ‘Lexis’ diagram produced?

A
  • Calculate separately the number of ‘expected’ cases or deaths for each calendar time period
  • The expected number of cases or deaths in each cell then summer over all the cells, i.e. over all age groups and for all calendar time periods, to give total number of expected cases or deaths
  • Can also add additional classification variables, but you are limited to the variables recorded by routine data sources
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180
Q

How is the number of ‘expected’ cases or deaths for each age group in a time period calculated?

A
  • Obtain reference populations age-specific rates for each calendar time period from routine data sources
  • Multiply these rates by appropriate cells’ person-years to estimate the expected number of cases and deaths in each cell
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181
Q

What additional classification variables can be added to a Lexis diagram?

A

Age-sex specific rates at each calendar time period

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182
Q

When is comparison with external reference population is useful?

A

When you cannot use sub-cohorts

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183
Q

What are the limitations of external comparisons in cohort studies?

A
  • Often limited data available for reference population
  • Often no incidence data
  • Usually have to make do with mortality data
  • Study and reference populations may not be comparable
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184
Q

Why may study and reference populations not be comparable?

A

Selection bias

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185
Q

Give an example of a form of selection bias

A

Healthy worker family

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186
Q

What is the result of the healthy worker effect?

A

Many occupational cohorts yield SMRs of well below 10%

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187
Q

What causes the healthy worker effect?

A

Since employment is often restricted to healthy individuals

188
Q

What is the advantage of concurrent cohort studies?

A

Enables detailed and prospective assessment of exposure, outcomes and confounders

189
Q

What are cohort studies better than case control studies at?

A
  • Studying a range of different outcomes
  • Studying rare exposure
  • Establishing that exposure(s) precede outcome(s)
190
Q

Which conditions are cohort studies better for?

A

Those that fluctuate with age, both randomly or systematically

191
Q

What are the disadvantages of cohort studies?

A
  • Usually large and resource intensive
  • Take long time
  • Rigorous definitions of outcome and exposure can require expensive and sometimes intensive/invasive investigation
  • Risk high number of losses to follow up
  • Results take a long time
  • Not good for rare outcomes
  • Difficulty with confounding, especially unknown confounders
192
Q

Which kind of cohort studies are quicker?

A

Historical

193
Q

What is produced when there are a high number of losses to follow up?

A

Survivor bias

194
Q

What causes survivor bias?

A

When those who remain in the study differ from those who left

195
Q

What is the result of cohort studies taking a long time?

A

Potentially ethical dilemmas, can become politically charged

196
Q

Why are cohort studies not good for rare cases?

A

You would get too few cases

197
Q

What must you do to conduct a case-control study?

A
  • Identify a group of cases
  • Identify a suitable group of non-cases (controls)
  • Ascertain previous exposure status of everyone
  • Compare level of exposure in cases and controls
198
Q

Why do we need case-control studies?

A
  • Conventional cohort studies take a long time
  • Cohort studies are expensive, especially if you need detailed information
  • Cohort studies are not good for studying rare events
199
Q

Why are cohort studies not good for studying rare events?

A

Because they would need to be impossibly large

200
Q

What is the rare disease assumption?

A

IRR = AD/CB

When A= disease in exposed (person-years), B= no disease in exposed (person-years), C= disease in unexposed (person-years) and D= no disease in exposed (person-years)

201
Q

What does AD/CB always equate to under the rare disease assumption?

A

The odds ratio

202
Q

What is the odds ratio a valid measure of?

A

Excess risk in cases compared with controls

203
Q

How do calculate error factor?

A

Error factor = e 2*√(1/a)+(1/b)+(1/c)+(1/d)

204
Q

What is the precision of odds ratio affected by?

A

The number of healthy people, as well as the number of cases

205
Q

What is the result of the precision of an OR being affected by the number of cases?

A

It is worth increasing the number of controls up to a point

206
Q

Up to which point is it worth increasing the number of controls?

A

4 to 6 as many times as many controls as there are cases

207
Q

In what direction do cohort studies look?

A

Always forward in time

208
Q

In what direction do case control studies look?

A

Backwards in time

209
Q

What happens in a conventional case-control study?

A

Retrospective collection of data

210
Q

How is data obtained in a conventional case control study?

A

From recall

211
Q

What happens in a nested case-control study?

A

Collection of data from the evolving outcome and exposure database of a ‘concurrent’ and ‘prospective’ cohort study

212
Q

Why is a nested case control study so named?

A

Because it’s a case control study ‘nested’ within a cohort study

213
Q

What are the advantages of nested case control studies over conventional?

A

NAME?

214
Q

What are the advantages of conventional case control studies over nested?

A

Can collect more detailed information for a minority of participants

215
Q

What are the key issues for case-control studies?

A
  • Selection bias
  • Information bias
  • Confounding
216
Q

What is the most difficult aspect of case-control studies to deal with?

A

Selection bias

217
Q

What should cases selected be representative of?

A

All cases

218
Q

What should controls selected be representative of?

A

The population from which the cases came

219
Q

What can cause information bias?

A

NAME?

220
Q

Give an example of a non-differentiated misclassification

A

Randomly incorrect measurement

221
Q

Give 3 examples of systematic misclassification

A
  • Recall bias
  • Assessor bias
  • Data collection methods differ
222
Q

How can confounding be minimised?

A

By matching important confounders

223
Q

How can confounding be adjusted for?

A

Analysing with logistic regression

224
Q

What does disease result from?

A

The interplay of host, environment and the agent

225
Q

What is a cause?

A

An exposure or factor that increases probability of disease

226
Q

To exposures have to be necessary or sufficient to be important causes?

A

No

227
Q

What is the aim of the use of knowledge?

A

To remove, avoid or protect against harmful factors

228
Q

What are the two observational study designs?

A

NAME?

229
Q

What are the two types of analytical studies?

A

NAME?

230
Q

What are possible explanations for correlation?

A

Systematic and random variation

231
Q

What can cause systematic and random variation?

A

NAME?

232
Q

What is wrong with results due to confounding?

A

They are erroneous

233
Q

What can confounding factors be?

A
  • Known factors
  • Possible factors
  • Unknown factors
234
Q

Give 2 examples of known confounding factors

A

NAME?

235
Q

Give an example of a possible confounding factor

A

Deprivation

236
Q

What could act as an unknown confounding factor?

A

Genetics

237
Q

What is wrong with results due to bias?

A

They are incorrect

238
Q

Give two types of bias

A

NAME?

239
Q

What is the problem with selection bias?

A
  • Unrepresentative of population being studied

- Group comparison not ‘like with like’

240
Q

What can cause information bias?

A
  • Differential recall
  • Differential observation
  • Differential measurement
  • Differential classification
241
Q

What measures chance?

A

The p-value

242
Q

What is reverse causality?

A

If you believe X → Y, but actually Y → X

243
Q

When does a true causal association exist?

A

When X → Y

244
Q

What is Bradford Hill’s viewpoints or criteria for inferring causality?

A
  • Association features
  • Strength of association
  • Specificity of association
  • Consistency of association
  • Exposure/outcomes
  • Temporal sequence
  • Dose response
  • Reversibility
  • Other evidence
  • Coherence of theory
  • Biological plausibility
  • Analogy
245
Q

What is meant by strength of association?

A

A causal link is more likely with strong associations

246
Q

How is the strength of associations commonly measured?

A

By a rate ratio or odds ratio

247
Q

What are strong associations unlikely to be explained by?

A

Undetected confounding or bias

248
Q

Can weak associations be causal?

A

Yes

249
Q

What is meant by specificity of association?

A

A causal link is more likely when an outcome is associated with a specific factor, and vice-versa

250
Q

What does specificity of association strengthen?

A

The case for a causal link

251
Q

Does a lack of specificity weaken the case?

A

Not necessarily

252
Q

Why does a lack of specificity not necessarily weaken the case?

A

Current models of disease causation are multi-factorial

253
Q

What is meant by consistency of association?

A

A causal link is more likely if the association is observed in different studies and different sub-groups

254
Q

What is consistency of association between studies or groups unlikely to be due to?

A

The same confounding or bias

255
Q

Why may inconsistency exist?

A
  • Because of differences in other causal factors

- Features of study design

256
Q

What is meant by temporal sequence?

A

A causal link is more likely if exposure to the putative factor has been shown to precede the outcome

257
Q

Can a causal link exist if the outcome preceded exposure to the putative factor?

A

No

258
Q

What are the optimal study designs?

A
  • Randomised control trails

- Prospective cohort studies

259
Q

What are the weak study designs?

A

NAME?

260
Q

What is meant by reversibility?

A

A causal link is very likely if removal or prevention of the putative factor leads to a reduced or non-existent risk of acquiring the outcome

261
Q

What is the significance of reversibility?

A

The strongest evidence for causal relationship

262
Q

Why is reversibility often difficult to demonstrate?

A
  • Many diseases have long time lags
  • Ethical issues for a RCT of a prevention programme
  • A public health programme to remove or prevent an exposure often requires action by society
263
Q

What is meant by coherence of theory?

A

A causal link is more likely if the observed association conforms with current knowledge

264
Q

What forms of coherence can strengthen a case?

A

With current paradigms, constructs or theories

265
Q

What is the problem with coherence of theory?

A

It can lead to inappropriate rejection of ‘unfavored associations’

266
Q

Does lack of coherence rule out a causal link?

A

No

267
Q

What is meant by a dose response?

A

A causal link is more likely if different levels of exposure to the putative factor leads to different risk of acquiring the outcome

268
Q

What is meant by biological plausibility?

A

A causal link is more likely if a biologically plausible mechanism is likely or demonstration

269
Q

What limits biological plausibility?

A

Current knowledge

270
Q

What is meant by analogy?

A

A causal link is more likely if an analogy exists with other diseases, species or settings

271
Q

What is the advantage of an analogy over biological plausibility?

A

It is easier to infer

272
Q

What is the problem with analogies?

A

They may be inappropriate

273
Q

What is epidemiology?

A

The study of distribution and determinants of health-related states, or events in specified populations, and the application of this study to the control of health problems

274
Q

What assumptions are made in epidemiology?

A
  • Disease does not occur at random

- Disease has causal and preventable factors that can be identified through systematic investigation

275
Q

What has the evolution of the concept of causality lead to?

A

The adaptation of the probabilistic approach to considering causality based on assessment of likelihood or risk of disease occurring, as now thought that multi-factorial web of factors causes disease

276
Q

What does epidemiological reasoning involve?

A
  • Hypothesis
  • Analytical study
  • Observed associations
  • Cause-effect relationships
277
Q

What is a hypothesis generated from?

A

Observations and/or theories

278
Q

What is analytical study?

A

Systematic observations of comparisons

279
Q

What are observed associations?

A

Possible explanations of non-causal associations

280
Q

Give 3 examples of non-causal associations

A

NAME?

281
Q

What is a cause-effect based on?

A

Judgement of how the observed associations fits in with information from other sources

282
Q

What is a clinical trail?

A

Any form of planned experiment which involves patients and is designed to elucidate the most appropriate method of treatment of future patients with a given medical condition

283
Q

What does a clinical trial measure?

A

The outcome of the new treatment compared to the outcomes of the standard treatment

284
Q

What is the purpose of a clinical trial?

A

To provide reliable evidence of treatment efficacy and safety

285
Q

What is efficacy?

A

The ability of a health care intervention to improve the health of a define group under specific conditions

286
Q

What is safety?

A

The ability of a health care intervention not to harm a defined group under specific conditions

287
Q

What does a clinical trial need to be to be able to give a fair comparison of effect and safety?

A
  • Reproducible in experimental conditions
  • Controlled
  • Fair
288
Q

What are clinical trials subject to?

A

Random variation

289
Q

What differences found in clinical trials are more prone to chance?

A

Those observed in small trials of

290
Q

What happens in the preclinical phase of drug development and monitoring?

A

Laboratory studies

291
Q

What is being tested in the preclinical phaseof drug development and monitoring?

A

Pharmacology and animal toxicity

292
Q

What is tested on in the preclinical phase of drug development and monitoring?

A

Cell cultures and animals

293
Q

What happens in phase I of drug development and monitoring?

A

Volunteer studies

294
Q

What is being tested in phase Iof drug development and monitoring?

A

Pharmacodynamics, pharmacokinetics, and major side effects

295
Q

Who is tested on in phase Iof drug development and monitoring?

A
296
Q

What happens in phase IIof drug development and monitoring?

A

Treatment studies

297
Q

What is tested in phase IIof drug development and monitoring?

A

Effects, dosages, and common side effects

298
Q

Who is tested on in phase IIof drug development and monitoring?

A
299
Q

What happens in phase IIIof drug development and monitoring?

A

Clinical trails

300
Q

What is being tested in phase IIIof drug development and monitoring?

A

Comparison with other treatments

301
Q

Who is tested on in phase IIIof drug development and monitoring?

A
302
Q

What happens in phase IVof drug development and monitoring?

A

Post-marketing surveillance, monitoring for adverse reactions and looking for potential new uses

303
Q

Who is tested on in phase IVof drug development and monitoring?

A

The whole population

304
Q

What do non-randomised clinical trails involve?

A

The allocation of patients receiving a new treatment to compare with a group of patients receiving standard treatment

305
Q

What is introduced in non-randomised clinical trials?

A

NAME?

306
Q

Who can introduce allocation bias in non-randomised clinical trials?

A
  • Patient
  • Clinician
  • Investigator
307
Q

What does comparison with historical cohorts involve?

A

The comparison of a group of patients who had the standard treatment with a group of patients receiving a new treatment

308
Q

What is the problem with historical comparisons in clinical trails?

A

For the standard treatment group,

  • selection often less well defined, and less rigorous
  • treated differently from new treatment group
  • less information about potential bias/confounding
  • unable to control for confounders
309
Q

What needs to be defined in a randomised control trial (RCT)?

A
  • The disease of interest
  • The treatments to be compared
  • The outcomes to be measured
  • Possible bias and confounders
  • The patients eligible for the trial
  • The patients to be excluded from the trial
310
Q

What must be done to conduct a RCT?

A
  • Identify a source of eligible patients
  • Invite eligible patients to be in the trial
  • Consent patients willing to be in the trial
  • Allocate participants to the treatments fairly, without bias and confounding
  • Follow-up participants in identical ways
  • Minimise losses to follow up
  • Maximise compliance with treatments
311
Q

What are we comparing outcomes to determine?

A

NAME?

312
Q

What is the importance of the size of the difference between groups?

A

Determines if it’s clinically significant

313
Q

What needs to be determined before the start of a clinical trial?

A
  • Protocol for data collection

- Agreed criteria for measurement and assessment of outcomes

314
Q

Why must outcomes of a clinical trail be pre-defined?

A

To prevent data dredging and repeated analysis

315
Q

What is preferable in clinical trails regarding outcomes?

A

That there is only one, primary outcome

316
Q

What is the primary outcome used in?

A

Sample size calculations

317
Q

What are secondary outcomes?

A

Other outcomes of interest

318
Q

What do secondary outcomes often include?

A

Occurence of side effects

319
Q

What are the types of outcome?

A
  • Pathophysiological
  • Clinically defined
  • Patient focused
320
Q

Give 3 examples of pathophysiological outcomes

A
  • Tumour size
  • Thyroxine levels
  • ECG changes
321
Q

Give 3 examples of clinically define outcomes

A
  • Death
  • Disease
  • Disabilities
322
Q

Give 4 examples of patient focused outcomes

A
  • Quality of life
  • Pathological well being
  • Social well being
  • Satisfaction
323
Q

What are the features of an ideal outcome?

A
  • Appropriate and relevant
  • Valid and attributable
  • Sensitive and specific
  • Reliable and robust
  • Simple and sustainable
  • Cheap and timely
324
Q

Who must an outcome be appropriate and relevant to?

A

Patient, clinician, society etc

325
Q

What is meant by an outcome being valid and attributable?

A

That any observed effects can be reasonably linked to the treatments being compared

326
Q

What is meant by an outcome being sensitive and specific?

A

The chosen method of measurement can detect changes accurately

327
Q

What is meant by an outcome being reliable and robust?

A

That the outcome is measurable by different people in various settings with similar results

328
Q

What is meant by an outcome being simple and sustainable?

A

That the method of measurement is measurement is carried out repeatedly

329
Q

What is meant by an outcome being cheap and timely?

A

Not excessively expensive to measure, nor has a long lag time

330
Q

When are measurements made?

A
  • Baseline measurements
  • Monitoring outcomes during the trial
  • Final measurement of outcomes
331
Q

What is the purpose of baseline measurements?

A

Monitoring for inadvertent differences in groups

332
Q

What is being monitored for during the trial?

A

Possible effects and adverse effects

333
Q

What is happening when the final measurements are being made?

A

Comparing final effects of treatments in trial

334
Q

What is non-random allocation?

A

Allocation of participants to treatments based on on a personal, historical basis, geographical location, convenience, numerical order etc

335
Q

What can result for non-random allocation

A

Allocation bias and confounding factors

336
Q

What is the problem with non-random allocation?

A

It can unwittingly cause unidentified differences between treatment groups being compared

337
Q

What is the advantage of random allocation?

A

It allocates participants to treatments fairly, and this minimises allocation bias and confounding

338
Q

How does random allocation minimise allocation bias?

A

Randomisation gives each participant an equal chance of being allocated to each of the treatments in the trial

339
Q

How does random allocation minimise confounding?

A

In the long run, randomisation leads to treatment groups that are more likely to be similar in size, and characterised by chance

340
Q

What kind of confounding does random allocation minimise?

A

Both known and unknown

341
Q

Give 3 methods of randomisation

A
  • Toss a coin
  • Random number tables
  • Computer generated random number
342
Q

What is it called when the treatment allocation is known?

A

Open label

343
Q

What may knowledge of which participant is receiving which treatment lead to?

A

Bias of the result

344
Q

Why may knowledge of who is receiving which treatment lead to bias?

A
  • Patients may alter their behaviour, other treatment or expectation of the outcome
  • Clinician may alter their treatment, care and interest in the patient
  • Investigator may alter their approach when making measurements and assessing outcomes
345
Q

What are the types of blinding?

A
  • Single blind
  • Double blind
  • Triple blind
346
Q

What happens in a single blind trial?

A

One of the patient, clinician or assessor (usually patient) doesn’t know treatment allocation

347
Q

What happens in a double blind trial?

A

Two of the patient, clinician or assessor doesn’t know the treatment allocation (usually involved the patient not knowing)

348
Q

What happens in a triple blind trial?

A

All do not know allocation

349
Q

What must be done to blind a trial?

A
  • Aim to make treatments identical in every way
  • Use a designated pharmacy to label identical containers for the treatments with code numbers, and have code sheet detailing which code number corresponds to which treatment
350
Q

In what respects must a treatment be identical?

A
  • Appearance
  • Taste
  • Texture
  • Dosage
  • Regime
  • Warnings
351
Q

Where can blinding be difficult?

A
  • Surgical procedures
  • Psychotherapy vs. anti-depressant
  • Alternative medicine vs. Western medicine
  • Lifestyle interventions
  • Prevention programmes
352
Q

What is the problem with controlling with no treatment?

A

The effect of comparing ‘new’ treatment group with a group receiving no treatment is to leave one unsure as to whether any observed difference was due to the new treatment, or just to that group receiving care

353
Q

What is the result of the placebo effect?

A

Even if the therapy is irrelevant to the patients condition, the patients attitude to their illness, and indeed the illness itself, may be improved by thinking something is being done about it

354
Q

What is a placebo?

A

An inert substance made to appear identical in every way to the active formulation with which it is to be compared

355
Q

What is the aim of a placebo?

A

To cancel out any placebo effect that may occur in the the active treatment

356
Q

What are the ethical implications of a placebo?

A

Use of placebo is a form of deception

357
Q

When should a placebo be used?

A

Only ben no standard treatment is available

358
Q

What is ethically essential when using a placebo?

A

Patients in a placebo-controlled trial are informed that they may receive a placebo

359
Q

Why may losses to follow up occur?

A
  • Their clinical condition may necessitate their removal from the trial
  • They may choose to withdraw from the trial
360
Q

What must be done to minimise losses to follow up?

A
  • Make follow up practical and minimise inconvenience
  • Be honest about commitment required for participants
  • Avoid coercion or inducements
  • Maintain contact with participants
361
Q

Why may non-compliance with treatment occur?

A
  • May have misunderstood instructions
  • May not like taking their treatment
  • May think that their treatment is not working
  • May prefer to take another treatment
  • Can’t be bothered to take their treatment
362
Q

How can compliance to treatment be maximised?

A
  • Simplify instructions
  • Ask about compliance
  • Ask about effects and side effects
  • Monitor compliance
363
Q

How can compliance be monitored?

A
  • Tablet count
  • Urine level
  • Blood level
364
Q

What is not possible in practice?

A

To have 100% follow up, and to guarantee than 100% compliance took place

365
Q

What is the result of the impossible to obtain 100% follow up and compliance?

A

Any analysis of outcomes should take this issue into account

366
Q

What are the two interpretations of wether a new treatment is better than a standard treatment?

A

NAME?

367
Q

What are the two types of analysis?

A

NAME?

368
Q

Who does an ‘as treated’ analysis look at?

A

Only those who completed follow up and complied with treatments

369
Q

What does ‘as-treated’ analysis compare?

A

The physiological effects of treatment

370
Q

What is the problem with ‘as-treated’ analysis?

A

Non-compliers are likely to be systematically different from compliers, and so introduces selection bias and confounding

371
Q

What does an ‘intention-to-treat’ analyse according to?

A

The original allocation of treatment groups, regardless of wether they completed follow up or complied with treatment

372
Q

What does an intention to treat analysis compare?

A

The likely effects of using the treatments in routine clinical practice

373
Q

What is the advantage of an intention to treat analysis?

A

It preserves the effects of randomisation

374
Q

What do as treated analyses test to give?

A

A larger size of effect

375
Q

What do intention to treat analyses tend to give?

A

Smaller and more realistic sizes of effect

376
Q

How should clinical trials normally be analysed?

A

On an intention to treat basis

377
Q

What are the ethical principles for medical research involving human subjects?

A
  • The health of the patient must be the physicians first consideration
  • A physician shall act only in the patients interest when providing medical care which may have the effect of weakening the mental or physical condition of the patient
378
Q

What is a collective ethic?

A

That all patients should have treatments that are properly tested for efficacy and safety

379
Q

What principles apply in the individual ethic?

A
  • Beneficence
  • Non-malifecence
  • Autonomy
  • Justice
380
Q

What are RCTs for the benefit of?

A

Future patients

381
Q

How does the collective ethic apply to RCTs?

A

They aim to properly test treatments for efficacy and safety

382
Q

How does the individual ethic apply to RCTs?

A
  • Do not guarantee benefit
  • Could result in harm
  • Allocate treatments by chance
  • Place burdens and confer benefits
383
Q

What issues should be considered for a clinical trial to be ethical?

A
  • Clinically equipoise
  • Scientifically robust
  • Ethical recruitment
  • Valid consent
  • Voluntariness
384
Q

What must be done for a trial to go ahead?

A

Approval by Research Ethics Committee

385
Q

What is clinical equipoise?

A

When there is reasonable uncertainty or genuine ignorance about the better treatment or intervention (including the non intervention

386
Q

What are the issues with clinical equipoise?

A
  • Is the ‘uncertainty or ignorance’ by the individual clinician, or for the scientific community as a whole?
  • What constitutes ‘reasonable uncertainty’
  • How is ‘better’ defined for the individual patient or for society as a whole
387
Q

What features must a study have to be scientifically robust?

A
  • Addresses a relevant or important issue
  • Asks a valid question
  • Has an appropriate study design and protocol
  • Has the potential to reach sound conclusions
  • Can justify use of comparator treatment or placebo
  • Has acceptable risks of possible harm compared to anticipated benefits
  • Has provision for monitoring the safety and well being of participants in trial
  • Has arrangements for appropriate reporting and publication
388
Q

What must be true for a study to have an appropriate design and protocol?

A

It must address potential bias and confounding

389
Q

Why must a study have the potential to reach sound conclusions?

A

To minimise inability to find a clinically important effect using a sample size calculation

390
Q

Give 2 examples for provision of participant safety and well being monitoring

A
  • Data monitoring

- Patient monitoring

391
Q

What are the two issues of ethical recruitment?

A
  • Inappropriate inclusion of;
  • participants for communities that are unlikely to benefit
  • participants with high risk of harm with respect to potential benefit
  • participants likely to be excluded from analysis
  • Inappropriate inclusion of;
  • people who differ from an ideal homogenous group
  • people who it is difficult to get valid consent for
392
Q

What are the features of valid consent?

A
  • Knowledgable informant
  • Appropriate information
  • Informed participant
  • Competent decision maker
  • Legitimate authoriser
393
Q

How should appropriate information be given?

A

Verbal and written

394
Q

What should be given after receiving information?

A
  • Cooling off period

- Ability to opt out

395
Q

What should be given as evidence of valid consent?

A

Signed consent form

396
Q

Does a signed consent form equate to valid consent?

A

No

397
Q

What is voluntariness a pre-requisite for?

A

Consent to be valid

398
Q

What is meant by voluntariness?

A

The decision should be free from coercion or manipulation, or the perception that coercion or manipulation may take place

399
Q

What is the result of perceived coercion or manipulation?

A

Invalidates consent as much as actual coercion or manipulation

400
Q

What can coercion be?

A

Non-access to ‘best’ treatment, lower quality care, disinterest by clinician

401
Q

What can manipulation be?

A

Exploitation of emotional state, distortion of information or financial inducements

402
Q

What is the issue of voluntariness an issue of?

A

Autonomy

403
Q

Why is the issue of voluntariness an issue of autonomy?

A

If undue influence is being exerted so that a potential participant acts uncharacteristically then influence is regarded as unethical

404
Q

What are NHS Trusts / the PCD R&D Office concerned with

A
  • Research governance
  • Financial management
  • Resource implications
405
Q

What do the Research Ethics Committee concerned say?

A

‘The dignity, rights, safety and well being of participants must be the primary consideration in any research study’

406
Q

What do the Research Ethics Committee focus particularly on?

A
  • Scientific design and conduct of study
  • Recruitment of research participants
  • Care and protection of research participants
  • Protection of research participants confidentiality
  • Informed consent process
  • Community considerations
407
Q

What should healthcare services and interventions be based on?

A

The best available evidence

408
Q

What should the best available evidence be based on?

A

Rigorously conduced research

409
Q

What must be looked at in research into best available evidence?

A
  • Primary research studies
  • Literature review of studies
  • Decision analyses
410
Q

Give two types of literature reviews of studies

A

NAME?

411
Q

What are narrative reviews looking at?

A

Implicit assumptions, opaque methodology

412
Q

What is the result of a study not being reproducible?

A

It is considered biases and subjective

413
Q

What do systematic reviews look at?

A

Explicit assumptions, transparent methodology

414
Q

What do decision analyses look at?

A
  • Harms and benefits

- Cost-effectiveness

415
Q

What is required for systematic reviews require?

A

A clearly focused question

416
Q

What are explicit statements made about in systematic reviews?

A
  • Types of study
  • Types of participants
  • Types of interventions
  • Types of outcome measures
417
Q

What do systematic reviews involve?

A
  • Systematic literature search
  • Selection of materials
  • Appraisal
  • Synthesis (possibly including meta-analysis)
418
Q

What is the advantage of a systematic review?

A

It is an extremely credible source of evidence

419
Q

What are the key aspects of a systematic review?

A
  • Explicit
  • Transparent
  • Reproducible
420
Q

What is a systematic review an overview of?

A

Primary studies that used explicit and reproducible methods

421
Q

What is a meta-analysis?

A

A quantitive synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way

422
Q

What is the purpose of meta-analyses?

A
  • To facilitate the synthesis of large number of study results
  • To systematically cellate study results
  • To reduce problems of interpretation due to variations in sampling
  • To quantify effect sizes and their uncertainty as a pooled estimate
423
Q

What are the quality criteria of meta-analyses?

A

They should have a formal protocol specifying;

  • Compilation of complete set of studies
  • Identification of common variable or category definition
  • Standardised data extraction
  • Analysis allowing sources of variation
424
Q

Does a systematic review always include a meta-analysis?

A

Not always

425
Q

When may a systematic review not contain a meta-analysis?

A

When clinical heterogeneity is too great

426
Q

How is a pooled estimate odds ratio for all studies calculated?

A
  • OR and their 95% CIs are calculated for all studies in meta-analysis
  • These are combined to give pooled estimate odds ratio using a statistical computer program
  • Studies weighted according to their size and uncertainty of their odds ratio
427
Q

In a pooled estimate OR, what does a smaller e.f. mean?

A

A greater weight to results

428
Q

How are forest plots interpreted?

A
  • Individual odds ratios are squares, with their 95% CIs being displayed as lines
  • The size of each square is proportional to the weight given to the study
  • The diamond is a pooled estimate with the centre indicating the pooled odds ratio (dotted line), and the width representing the pooled 95% CI
  • The solid line is the null hypothesis CI
429
Q

What are the problems with meta-analyses?

A
  • Heterogeneity between studies
  • Variable quality of studies
  • Publication bias in selection of studies
430
Q

What must be done to determine heterogeneity between studies?

A
  • Modelling for variation

- Analysing the variation

431
Q

How can variation be modelled for?

A

Fixed effect model vs random effects model

432
Q

How can variation be analysed?

A

Sub-group analysis

433
Q

Ideally, what should all studies in a meta-analysis be similar in terms of?

A
  • Study design
  • Participant profile
  • Treatments or exposure
  • Outcomes measured
  • Statistical analysis used
434
Q

What is the problem with finding identical studies for meta-analyses?

A

In practice, no two studies are identical

435
Q

What are the two approaches to calculating the pooled estimate odds ratio and its 95% CI to model for variation?

A

NAME?

436
Q

What does a fixed effect model do?

A

Assumes studies are estimating exactly the same effect size

437
Q

What does a random effects model do?

A

Assumes that the studies estimate similar, not same, effect size

438
Q

How do the results of a fixed effect and random effect model differ?

A

NAME?

439
Q

What is the problem with hypothesis testing for heterogeneity using fixed effects and random effects models?

A

Low statistical power to detect heterogeneity

440
Q

What is often used in hypothesis testing for heterogeneity using fixed effects and random effects models?

A

10% significance levels

441
Q

What model is superior, fixed effect or random effects?

A

Much debate

442
Q

What is true if, in a test for heterogeneity, the result is the null hypothesis?

A

There is no heterogeneity

443
Q

What is true if, in a test for effect, the result is the null hypothesis?

A

There is no difference in the studies

444
Q

What can random effects modelling account for?

A

Variation

445
Q

Can random effects modelling explain the variation?

A

No

446
Q

What can sub-group analysis do?

A

Can explain heterogeneity

447
Q

What is the advantage of sub-group analysis being able to explain heterogeneity?

A

It can provide further insight into the effect of treatment of exposure

448
Q

What are the two types of possible sub group analysis?

A
  • Stratification by study characteristics

- Stratification by participant profile

449
Q

What happens in stratification by study characteristics?

A

Subsets of ‘whole’ studies are defined by characteristics

450
Q

What characteristics can sub-sets of whole studies be characterised by?

A
  • Study design
  • Length of follow up
  • Participant profile
  • Recruitment criteria
451
Q

What happens in stratification by participant profile?

A

Data is analysed by type of participants

452
Q

What is the advantage of stratification by participant profile?

A

Has greater statistical power than for individual studies

453
Q

What is the disadvantage of stratification by participant profile?

A

Data is often unreliable

454
Q

What can variable study quality be due to?

A
  • Poor study design
  • Poor design protocol
  • Poor protocol implementation
455
Q

Order studies from least to most susceptible to bias and confounding?

A

Randomised control trials → Non-randomised control trials → Cohort studies → Case-control studies

456
Q

What are the two main approaches to variable quality of studies?

A
  • Define basic quality standard, and only include studies satisfying these criteria
  • Score each study for its quality, then
  • incorporate quality score into weighting allocated to each study during the modelling, so that higher quality studies have greater influence on the pooled analysis
  • use sub-group analyses to explore differences
  • meta-regression analysis
457
Q

Give an example of a meta-regression analysis

A

Weighted linear regression of effect size against quality

458
Q

What are the main components for assessing the quality of RCTs?

A
  • Allocation methods
  • Blinding and outcome assessment
  • Patient attrition
  • Appropriate statistical analysis
459
Q

Who assesses quality?

A

> 1 assessor

460
Q

What is the purpose of having >1 assessor?

A

To handle disagreement

461
Q

What is the problem with assessors being blinded to results?

A

It’s sometimes difficult

462
Q

Why does publication bias occur?

A

Studies with statistically significant or favourable results are more likely to be published than those studies with non-stastically significant or unfavourable results

463
Q

Where does publication bias particularly occur?

A

To small studies

464
Q

What does publication bias tend to lead to?

A

Biased selection in favour of studies in favour of demonstration of effects

465
Q

How can publication bias be identified?

A
  • Check meta-analysis protocol for identification of studies- it should include searching and identification of unpublished studies
  • Plot results of identified studies against a measure of their size
  • Use a statistical test for publication bias
466
Q

What do statistical tests for publication bias tend to be?

A

Weak

467
Q

How is a funnel plot showing publication bias interpreted?

A
  • A plot of measure of study size against measure of effect
  • If no publication bias, then the plot will be a ‘balanced’ funnel
  • Smaller studies can be expected to vary further from ‘control’ effect size
  • Publication bias likely to exist if there are few small studies with results indicating small or ‘negative’ measure of effect

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