HaDPop Flashcards
1
Q
What are the two approaches to the concept of causality?
A
Deterministic and Stochastic
2
Q
What does the deterministic approach measure?
A
NAME?
3
Q
How does the deterministic approach of causality validate the hypothesis?
A
By systematic observations to predict with certainty future events
4
Q
What does the stochastic approach measure?
A
NAME?
5
Q
How does the stochastic approach to causality assess the hypothesis?
A
By systematic observations to give the likelihood of future events
6
Q
Based on the stochastic approach, does a significant association mean causality exists?
A
No
7
Q
What is population-based risk?
A
How individuals infer their personal risk
8
Q
What do population-based observational studies do?
A
Investigate the causes of disease
9
Q
What is the purpose of population based interventions?
A
They treat and prevent disease
10
Q
What is the purpose of population based intervention trials?
A
They evaluate drugs and interventions
11
Q
Where is critical appraisal of evidence necessary?
A
To decide about causality
12
Q
How useful is laboratory bases evidence in determining causality?
A
It is contributory, but neither necessary not sufficient
13
Q
What can population based evidence give?
A
Association, but not causality
14
Q
Where are the ‘universal’ sources of information?
A
- Birth registration
- Death registration
- Population census
15
Q
How often is the population census done?
A
Every 10 years
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
17
Q
What does the census describe?
A
Both households and people
18
Q
Who runs the census?
A
The government
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
20
Q
What does the census cover?
A
A defined area at one time
21
Q
Who fills out the census?
A
Personal enumeration, or a person in each household completes the census form
22
Q
On what timescale is the census performed through a defined area?
A
Simultaneously
23
Q
What does the census provide?
A
Universal coverage
24
Q
What information can be obtained from the census?
A
NAME?
25
What can the population size be used for?
Measurements of rates
26
Why is it important to know the population structure?
To service needs
27
Give an example of population characteristics the government may need to know
Measures of deprivation
28
Give 5 measures of deprivation
- Unemployment
- Overcrowding
- Lone pensioners
- Single parents
- Lack of basic amenities
29
What influences a population size?
- Births
- Deaths
- Migration
30
Who provides birth notification?
An attendant at birth, usually the midwife
31
How quickly does a birth notification need to be submitted?
Within 36 hours
32
Where does a birth notification need to be submitted to?
The local Child Health Register
33
Why is birth notification important?
For relevant services such as immunisation
34
What is the incentive for carrying out birth registration?
It is required by law
35
Who registers a birth?
Parent
36
How soon does a birth need to be registered?
Within 42 days
37
Where should a birth be registered?
At a local Registrar for Births
38
What is the purpose of birth registration?
- Statistical purposes
| - Makes you identifiable
39
How does birth registration make you identifiable?
You get a birth certificate
40
What are the measures of fertility?
#NAME?
41
What is the CBR?
The number of live births per 1000 population, including men, women, children and old people
42
What is the GFR?
The number of live births per 1000 females ages 15-44
43
What is the TPFR?
The average number of children born to a hypothetical women in her life
44
What is TRFR not influenced by?
The size of population in different age groups
45
How is TPFR calculated?
∑(all current age-specific fertility rates)
46
What does a TPFR of 2 mean?
Replacement
47
What does a TPFR of >2 mean?
A growing population
48
What is GFR affected by?
Age specific birth rates (ADBR) and age distribution within the 15-44 year olds
49
What does TPRF give each age?
Equal weighting in it’s calculation
50
What are the determinants of fertility?
- Fecundity
| - Fertility
51
What is fecundity?
The physical ability to reproduce
52
What decreases fecundity?
Increase in sterilisation and hysterectomies
53
What is fertility?
Realisation of the ability to reproduce
54
What is fertility based on?
Humans, not biological
55
What increases fertility?
- Sexual activity
| - Good economic climate
56
What decreases fertility?
- Contraception
| - Abortion
57
What does conceptions equal?
Live births + miscarriages + abortions
58
What is the CBR used for?
Describing the impact of births on populations
59
What is the GFR used for?
Comparing the fertility of female populations
60
What is TPFR used for?
Comparing the fertility of females without being influenced by age-group structure
61
Whos statutory obligation is death certification?
The attending doctor
62
What can happen if a doctor doesn’t provide death certification?
They can go to prison
63
What is a doctor legally required to do on the death certificate?
Provide information on likely cause(s) of death
64
What must a doctor do if the cause of death is unusual or uncertain?
Notify the Coroner’s Officer
65
Who must perform death registration?
A qualified informant, usually a relative
66
How quickly does death registration need to be performed?
Within 5 days
67
What does death registration require?
A Death Certificate from a doctor
68
What are the measures of mortality?
#NAME?
69
What is the CDR?
The number of deaths per 1000 population
70
What is the ASDR?
The number of deaths per 1000 in an age group
71
What does the SMR do?
Compares the number of ‘observed’ deaths with the number of ‘expected’ deaths if the age-sex distribution of the populations were identical
72
What does SMR adjust for?
Age-sex distribution
73
What are the reasons for collecting mortality data?
#NAME?
74
What do population estimates do?
Apply what is known about births, deaths and migration to the present
75
What do population projections do?
Estimate the future populations
76
What additional assumptions are made in population estimates?
About births, deaths and migration in the future
77
What questions does identification of health and healthcare necessitate?
#NAME?
78
What does a trend involve?
The comparison of rates, which require a numerator and a denominator
79
What are rates often?
Per unit time
80
What does a trend imply?
A comparison over time
81
What can a trend be a comparison of, other that over time?
Comparison between places, across socio-economic groups etc., or a combination
82
What are the two types of errors that can occur in trend monitoring?
- Numerator errors
| - Denominator errors
83
What are some possible opportunities for numerator errors?
- Death certification
- Disease diagnosis
- Classification or coding errors
84
What are some possible opportunities for denominator errors?
- Population used
- Population definition
- Population count or estimate
85
What can trends be due to?
- Chance (random) variation
- Artefactual (systematic) reaosns
- Real phenomenon
- ‘Natural’ (epidemiological)
- Medical care effects
86
What should be done when there is a dramatic change in trends?
Consider artefactual reasons before considering real phenomenon
87
What are some contentious issues?
- Purpose
- Users
- Quality
- Comparability
- Relationship
- Publication
- Access
- Funding
88
What are the potential purposes of scientific studies?
#NAME?
89
Who are the possible users of information obtained from studies?
#NAME?
90
What is the competition in quality of data?
Real-time data vs validated data
91
What is comparability of data in competition with?
Comparable vs customised
92
What are the possible relationships in data found in studies?
Integral vs indepedant
93
Where could data from studies be published?
#NAME?
94
What is the conflict in access to data?
Data protection vs. freedom of information
95
What are the possible sources of funding for studies?
#NAME?
96
What concepts does the ‘amount’ of disease have?
- The number of new cases that occurred
| - The number of people affected by the disease
97
What does the concept of amount of new disease focus on?
New events
98
When is the concept of number of new cases that occur useful?
When monitoring epidemics
99
What does the concept of number of people affected count?
The number of people with the disease, counting both old and new cases
100
What does the concept of number of people affected by the disease describe?
The burden of disease
101
Where is the measure of number of people affected by a disease useful?
As a measure of need for services
102
How do you calculate incidence rate?
New events / (person * time(yrs))
103
What is the unit for incidence rate?
Events per persons per year
104
Is prevalence a rate?
No, it’s a proportion
105
What is the denominator for prevalence?
Persons (not persons per time)
106
What kind of study is use to determine prevalence?
Cross sectional
107
What does an increase in incidence lead to?
An increase in prevalence
108
What does a cure, or death of patients lead to?
Lower prevalence
109
What does a longer survival rate lead to?
Increased prevalence
110
How can prevalence be calculated?
- Incidence * length of disease
| - Cases / population
111
What is incidence?
The measure of the populations average risk of disease
112
What exists within a population regarding risk of disease?
Variations in risk of disease between groups of people
113
Why are systemic variations in risk between people of great interest?
Because it can give clues about the aetiology (cause) of a disease
114
How can variations in prevalence be used to determine aetiology?
Can compare levels of exposure in two groups of people and try to identify the causal factor for a disease
115
What may be done after identifying the causal factor for a disease?
Try and prevent exposure, thus reducing incidence of disease
116
What is the incidence rate ratio (IRR)?
A comparison of incidence rates between groups with different levels of exposure
117
How is the IRR calculated?
Rate B (Exposed) / Rate A (Unexposed)
118
What is implied if the incidence rate in group B is higher than that in group A?
The difference in exposures was associated with the differences in rates of disease
119
How can efficacy of treatments be measured?
Incidence rate ratios can be used to compare the effects of two treatments, and decide which one is best
120
Give two examples of nuisance variations in risk of disease?
#NAME?
121
What is the rate ratio for most diseases when comparing the rate old with rate young ?
>1.0
122
Why is knowing that there is variation based on age and sex not that useful for prevention?
Whilst it may be possible to target prevention at particular age-sex groups, age and sex are not modifiable factors
123
What can confounding factors explain?
All or part of an apparent association between an exposure and a disease
124
Give two ways of dealing with confounding by age
- Use age specific rate ratios
| - Use standardised mortality ratios
125
How can using age specific rate ratios help deal with confounding by age?
With narrow age bands, little confounding due to age occurs
126
What is the problem with using age specific rate ratios?
Results are difficult to interpret as you get too many answers, as there is one for each age band
127
What does the SMR look at?
The rate ratio for two populations if age-sex structure of the two populations was the same
128
What is indirect SMR comparing?
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
129
What does SMR account for?
Any age-sex confounding
130
How is SMR usually expressed?
As a %
131
What would a SMR of 100 mean?
There there is the same risk in the study population as in the standard reference population
132
What does a SMR of >100 mean?
A higher risk in the study population
133
How can SMRs be expressed if not a %?
Relative to 1.0
134
Essentially, what is the ‘observed’ value?
Our best estimate of the ‘true’ or ‘underlying’ tendency
135
What is a hypothesis?
A statement that an underlying tendency of scientific interest takes a particular quantitive value
136
What must be calculated in formal hypothesis testing?
The probability of getting an observation as extreme as, or more extreme as, the observed, assuming the stated null hypothesis is true
137
What happens if the probability of getting an observation as extreme as the observed is very small?
It is reasonable to conclude that the data and the stated null hypothesis are incompatible
138
What has happened if there is a very small probability that getting an observation as extreme as the one you observed?
- Something very unlikely has happened or
| - The stated hypothesis is wrong
139
What is the calculated probability of getting a value as extreme as the observed called?
P-value
140
When is an observation statistically significant?
When the p value ≤ 0.5
141
What does a p value of >0.05 not mean?
That they null hypothesis has been proven
142
What are the limitations of hypothesis testing?
- Rejecting a null hypothesis is not always useful
- Statistical significance depends on sample size
- Statistically significant doesn’t mean it’s clinically important
143
Why is rejecting a null hypothesis not always useful?
P ≤ 0.05 is arbitrary
144
What is meant by P ≤ 0.05 being arbitrary?
Nothing special happens between p=0.049 and p=0.051
145
What is it usual practice to hypothesis test again?
A null hypothesis
146
What is a null hypothesis?
A hypothesis assuming that two things are equal, or that there is no effect or difference
147
What information may be required by epidemiologists, and health service managers?
- Underlying tendencies
- What tendencies imply about the patterns of disease
- Health care need in the general population
148
What is the 95% confidence interval?
The range within which we can be 95% certain that the ‘true’ value of the underlying tendency really lies
149
What is the range of the 95% CI centred on?
The observed value
150
Why is the range of the 95% CI centred on the observed value?
Because it is always out best guess at the ‘true’ underlying value, so the observed value always lies between the 95% CI
151
What are values in the 95% CI said to be?
‘Consistent with the data’
152
What happens if the null hypothesis value is consistent with the observed data?
Any observed difference from the null hypothesis may be due to chance
153
How can you decide wether the finding is statistically significant?
Using the 95% CI
154
How do you calculate 95% CI?
- 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.
155
What happens as we get more data?
We get more sure about the ‘true’ underlying value
156
Why do we get more sure about the true underlying value as we get more data?
The e.f. gets smaller and the 95% CI gets narrower
157
What are the features of an ideal study?
- Basic scientific method comparing ‘like with like’
| - Two identical groups differing only in exposure of interest
158
What could be done if a study was ideal?
Differences can then reasonably be attributed to the exposure
159
Why can an ideal study not be achieved?
It’s impossible to get two identical groups of people differing only the exposure of interest, when exposure is linked to other factors
160
What can be done in an experiment?
Force all other factors to be identical
161
How can a study be randomised?
A randomised control trial
162
What can be done using a cohort study?
Measure and record any non-identical features
163
What is best, an experiment, randomisation or a cohort study?
An experiment, then randomisation
164
What must be counted in a cohort study?
Outcome events and person years, in exposed and unexposed groups
165
What are person-years?
The sum of the total time of everybody followed up in the study
166
Who must be recruited in a cohort study?
Outcome free individuals
167
What must the individuals recruited for a cohort study be classified into?
Exposed and unexposed categories
168
What are the advantages of cohort studies over routinely obtained data?
- 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
169
What do all cohort studies involve?
Prospective follow up
170
What is counted on the follow up of cohort studies?
Person-years (p-y) and d (developed)
171
When may data collection begin in a cohort study?
#NAME?
172
What is it called when data collection starts immediately or later in a cohort study?
Concurrent or prospective cohort study
173
What is it called when data is collected from the past in a cohort study?
Historical or retrospective study
174
How is a historical cohort study carried out?
Recruitment of outcome free individuals, classification of their exposure status and subsequent outcomes is done using historical data
175
How can comparisons be made in cohort studies?
Internally, or against external reference population
176
What does internal comparisons of cohort study data use?
IRR
177
What does external comparisons of cohort study data use?
SMR
178
Why is an SMR approach for a cohort study important?
Because cohort studies are usually conducted over long periods, often decades, so people age during the study
179
How is a ‘Lexis’ diagram produced?
- 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
180
How is the number of ‘expected’ cases or deaths for each age group in a time period calculated?
- 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
181
What additional classification variables can be added to a Lexis diagram?
Age-sex specific rates at each calendar time period
182
When is comparison with external reference population is useful?
When you cannot use sub-cohorts
183
What are the limitations of external comparisons in cohort studies?
- 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
184
Why may study and reference populations not be comparable?
Selection bias
185
Give an example of a form of selection bias
Healthy worker family
186
What is the result of the healthy worker effect?
Many occupational cohorts yield SMRs of well below 10%
187
What causes the healthy worker effect?
Since employment is often restricted to healthy individuals
188
What is the advantage of concurrent cohort studies?
Enables detailed and prospective assessment of exposure, outcomes and confounders
189
What are cohort studies better than case control studies at?
- Studying a range of different outcomes
- Studying rare exposure
- Establishing that exposure(s) precede outcome(s)
190
Which conditions are cohort studies better for?
Those that fluctuate with age, both randomly or systematically
191
What are the disadvantages of cohort studies?
- 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
Which kind of cohort studies are quicker?
Historical
193
What is produced when there are a high number of losses to follow up?
Survivor bias
194
What causes survivor bias?
When those who remain in the study differ from those who left
195
What is the result of cohort studies taking a long time?
Potentially ethical dilemmas, can become politically charged
196
Why are cohort studies not good for rare cases?
You would get too few cases
197
What must you do to conduct a case-control study?
- 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
Why do we need case-control studies?
- 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
Why are cohort studies not good for studying rare events?
Because they would need to be impossibly large
200
What is the rare disease assumption?
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
What does AD/CB always equate to under the rare disease assumption?
The odds ratio
202
What is the odds ratio a valid measure of?
Excess risk in cases compared with controls
203
How do calculate error factor?
Error factor = e 2*√(1/a)+(1/b)+(1/c)+(1/d)
204
What is the precision of odds ratio affected by?
The number of healthy people, as well as the number of cases
205
What is the result of the precision of an OR being affected by the number of cases?
It is worth increasing the number of controls up to a point
206
Up to which point is it worth increasing the number of controls?
4 to 6 as many times as many controls as there are cases
207
In what direction do cohort studies look?
Always forward in time
208
In what direction do case control studies look?
Backwards in time
209
What happens in a conventional case-control study?
Retrospective collection of data
210
How is data obtained in a conventional case control study?
From recall
211
What happens in a nested case-control study?
Collection of data from the evolving outcome and exposure database of a ‘concurrent’ and ‘prospective’ cohort study
212
Why is a nested case control study so named?
Because it’s a case control study ‘nested’ within a cohort study
213
What are the advantages of nested case control studies over conventional?
#NAME?
214
What are the advantages of conventional case control studies over nested?
Can collect more detailed information for a minority of participants
215
What are the key issues for case-control studies?
- Selection bias
- Information bias
- Confounding
216
What is the most difficult aspect of case-control studies to deal with?
Selection bias
217
What should cases selected be representative of?
All cases
218
What should controls selected be representative of?
The population from which the cases came
219
What can cause information bias?
#NAME?
220
Give an example of a non-differentiated misclassification
Randomly incorrect measurement
221
Give 3 examples of systematic misclassification
- Recall bias
- Assessor bias
- Data collection methods differ
222
How can confounding be minimised?
By matching important confounders
223
How can confounding be adjusted for?
Analysing with logistic regression
224
What does disease result from?
The interplay of host, environment and the agent
225
What is a cause?
An exposure or factor that increases probability of disease
226
To exposures have to be necessary or sufficient to be important causes?
No
227
What is the aim of the use of knowledge?
To remove, avoid or protect against harmful factors
228
What are the two observational study designs?
#NAME?
229
What are the two types of analytical studies?
#NAME?
230
What are possible explanations for correlation?
Systematic and random variation
231
What can cause systematic and random variation?
#NAME?
232
What is wrong with results due to confounding?
They are erroneous
233
What can confounding factors be?
- Known factors
- Possible factors
- Unknown factors
234
Give 2 examples of known confounding factors
#NAME?
235
Give an example of a possible confounding factor
Deprivation
236
What could act as an unknown confounding factor?
Genetics
237
What is wrong with results due to bias?
They are incorrect
238
Give two types of bias
#NAME?
239
What is the problem with selection bias?
- Unrepresentative of population being studied
| - Group comparison not ‘like with like’
240
What can cause information bias?
- Differential recall
- Differential observation
- Differential measurement
- Differential classification
241
What measures chance?
The p-value
242
What is reverse causality?
If you believe X → Y, but actually Y → X
243
When does a true causal association exist?
When X → Y
244
What is Bradford Hill’s viewpoints or criteria for inferring causality?
- 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
What is meant by strength of association?
A causal link is more likely with strong associations
246
How is the strength of associations commonly measured?
By a rate ratio or odds ratio
247
What are strong associations unlikely to be explained by?
Undetected confounding or bias
248
Can weak associations be causal?
Yes
249
What is meant by specificity of association?
A causal link is more likely when an outcome is associated with a specific factor, and vice-versa
250
What does specificity of association strengthen?
The case for a causal link
251
Does a lack of specificity weaken the case?
Not necessarily
252
Why does a lack of specificity not necessarily weaken the case?
Current models of disease causation are multi-factorial
253
What is meant by consistency of association?
A causal link is more likely if the association is observed in different studies and different sub-groups
254
What is consistency of association between studies or groups unlikely to be due to?
The same confounding or bias
255
Why may inconsistency exist?
- Because of differences in other causal factors
| - Features of study design
256
What is meant by temporal sequence?
A causal link is more likely if exposure to the putative factor has been shown to precede the outcome
257
Can a causal link exist if the outcome preceded exposure to the putative factor?
No
258
What are the optimal study designs?
- Randomised control trails
| - Prospective cohort studies
259
What are the weak study designs?
#NAME?
260
What is meant by reversibility?
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
What is the significance of reversibility?
The strongest evidence for causal relationship
262
Why is reversibility often difficult to demonstrate?
- 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
What is meant by coherence of theory?
A causal link is more likely if the observed association conforms with current knowledge
264
What forms of coherence can strengthen a case?
With current paradigms, constructs or theories
265
What is the problem with coherence of theory?
It can lead to inappropriate rejection of 'unfavored associations’
266
Does lack of coherence rule out a causal link?
No
267
What is meant by a dose response?
A causal link is more likely if different levels of exposure to the putative factor leads to different risk of acquiring the outcome
268
What is meant by biological plausibility?
A causal link is more likely if a biologically plausible mechanism is likely or demonstration
269
What limits biological plausibility?
Current knowledge
270
What is meant by analogy?
A causal link is more likely if an analogy exists with other diseases, species or settings
271
What is the advantage of an analogy over biological plausibility?
It is easier to infer
272
What is the problem with analogies?
They may be inappropriate
273
What is epidemiology?
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
What assumptions are made in epidemiology?
- Disease does not occur at random
| - Disease has causal and preventable factors that can be identified through systematic investigation
275
What has the evolution of the concept of causality lead to?
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
What does epidemiological reasoning involve?
- Hypothesis
- Analytical study
- Observed associations
- Cause-effect relationships
277
What is a hypothesis generated from?
Observations and/or theories
278
What is analytical study?
Systematic observations of comparisons
279
What are observed associations?
Possible explanations of non-causal associations
280
Give 3 examples of non-causal associations
#NAME?
281
What is a cause-effect based on?
Judgement of how the observed associations fits in with information from other sources
282
What is a clinical trail?
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
What does a clinical trial measure?
The outcome of the new treatment compared to the outcomes of the standard treatment
284
What is the purpose of a clinical trial?
To provide reliable evidence of treatment efficacy and safety
285
What is efficacy?
The ability of a health care intervention to improve the health of a define group under specific conditions
286
What is safety?
The ability of a health care intervention not to harm a defined group under specific conditions
287
What does a clinical trial need to be to be able to give a fair comparison of effect and safety?
- Reproducible in experimental conditions
- Controlled
- Fair
288
What are clinical trials subject to?
Random variation
289
What differences found in clinical trials are more prone to chance?
Those observed in small trials of
290
What happens in the preclinical phase of drug development and monitoring?
Laboratory studies
291
What is being tested in the preclinical phase of drug development and monitoring?
Pharmacology and animal toxicity
292
What is tested on in the preclinical phase of drug development and monitoring?
Cell cultures and animals
293
What happens in phase I of drug development and monitoring?
Volunteer studies
294
What is being tested in phase I of drug development and monitoring?
Pharmacodynamics, pharmacokinetics, and major side effects
295
Who is tested on in phase I of drug development and monitoring?
296
What happens in phase II of drug development and monitoring?
Treatment studies
297
What is tested in phase II of drug development and monitoring?
Effects, dosages, and common side effects
298
Who is tested on in phase II of drug development and monitoring?
299
What happens in phase III of drug development and monitoring?
Clinical trails
300
What is being tested in phase III of drug development and monitoring?
Comparison with other treatments
301
Who is tested on in phase III of drug development and monitoring?
302
What happens in phase IV of drug development and monitoring?
Post-marketing surveillance, monitoring for adverse reactions and looking for potential new uses
303
Who is tested on in phase IV of drug development and monitoring?
The whole population
304
What do non-randomised clinical trails involve?
The allocation of patients receiving a new treatment to compare with a group of patients receiving standard treatment
305
What is introduced in non-randomised clinical trials?
#NAME?
306
Who can introduce allocation bias in non-randomised clinical trials?
- Patient
- Clinician
- Investigator
307
What does comparison with historical cohorts involve?
The comparison of a group of patients who had the standard treatment with a group of patients receiving a new treatment
308
What is the problem with historical comparisons in clinical trails?
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
What needs to be defined in a randomised control trial (RCT)?
- 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
What must be done to conduct a RCT?
- 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
What are we comparing outcomes to determine?
#NAME?
312
What is the importance of the size of the difference between groups?
Determines if it’s clinically significant
313
What needs to be determined before the start of a clinical trial?
- Protocol for data collection
| - Agreed criteria for measurement and assessment of outcomes
314
Why must outcomes of a clinical trail be pre-defined?
To prevent data dredging and repeated analysis
315
What is preferable in clinical trails regarding outcomes?
That there is only one, primary outcome
316
What is the primary outcome used in?
Sample size calculations
317
What are secondary outcomes?
Other outcomes of interest
318
What do secondary outcomes often include?
Occurence of side effects
319
What are the types of outcome?
- Pathophysiological
- Clinically defined
- Patient focused
320
Give 3 examples of pathophysiological outcomes
- Tumour size
- Thyroxine levels
- ECG changes
321
Give 3 examples of clinically define outcomes
- Death
- Disease
- Disabilities
322
Give 4 examples of patient focused outcomes
- Quality of life
- Pathological well being
- Social well being
- Satisfaction
323
What are the features of an ideal outcome?
- Appropriate and relevant
- Valid and attributable
- Sensitive and specific
- Reliable and robust
- Simple and sustainable
- Cheap and timely
324
Who must an outcome be appropriate and relevant to?
Patient, clinician, society etc
325
What is meant by an outcome being valid and attributable?
That any observed effects can be reasonably linked to the treatments being compared
326
What is meant by an outcome being sensitive and specific?
The chosen method of measurement can detect changes accurately
327
What is meant by an outcome being reliable and robust?
That the outcome is measurable by different people in various settings with similar results
328
What is meant by an outcome being simple and sustainable?
That the method of measurement is measurement is carried out repeatedly
329
What is meant by an outcome being cheap and timely?
Not excessively expensive to measure, nor has a long lag time
330
When are measurements made?
- Baseline measurements
- Monitoring outcomes during the trial
- Final measurement of outcomes
331
What is the purpose of baseline measurements?
Monitoring for inadvertent differences in groups
332
What is being monitored for during the trial?
Possible effects and adverse effects
333
What is happening when the final measurements are being made?
Comparing final effects of treatments in trial
334
What is non-random allocation?
Allocation of participants to treatments based on on a personal, historical basis, geographical location, convenience, numerical order etc
335
What can result for non-random allocation
Allocation bias and confounding factors
336
What is the problem with non-random allocation?
It can unwittingly cause unidentified differences between treatment groups being compared
337
What is the advantage of random allocation?
It allocates participants to treatments fairly, and this minimises allocation bias and confounding
338
How does random allocation minimise allocation bias?
Randomisation gives each participant an equal chance of being allocated to each of the treatments in the trial
339
How does random allocation minimise confounding?
In the long run, randomisation leads to treatment groups that are more likely to be similar in size, and characterised by chance
340
What kind of confounding does random allocation minimise?
Both known and unknown
341
Give 3 methods of randomisation
- Toss a coin
- Random number tables
- Computer generated random number
342
What is it called when the treatment allocation is known?
Open label
343
What may knowledge of which participant is receiving which treatment lead to?
Bias of the result
344
Why may knowledge of who is receiving which treatment lead to bias?
- 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
What are the types of blinding?
- Single blind
- Double blind
- Triple blind
346
What happens in a single blind trial?
One of the patient, clinician or assessor (usually patient) doesn’t know treatment allocation
347
What happens in a double blind trial?
Two of the patient, clinician or assessor doesn’t know the treatment allocation (usually involved the patient not knowing)
348
What happens in a triple blind trial?
All do not know allocation
349
What must be done to blind a trial?
- 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
In what respects must a treatment be identical?
- Appearance
- Taste
- Texture
- Dosage
- Regime
- Warnings
351
Where can blinding be difficult?
- Surgical procedures
- Psychotherapy vs. anti-depressant
- Alternative medicine vs. Western medicine
- Lifestyle interventions
- Prevention programmes
352
What is the problem with controlling with no treatment?
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
What is the result of the placebo effect?
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
What is a placebo?
An inert substance made to appear identical in every way to the active formulation with which it is to be compared
355
What is the aim of a placebo?
To cancel out any placebo effect that may occur in the the active treatment
356
What are the ethical implications of a placebo?
Use of placebo is a form of deception
357
When should a placebo be used?
Only ben no standard treatment is available
358
What is ethically essential when using a placebo?
Patients in a placebo-controlled trial are informed that they may receive a placebo
359
Why may losses to follow up occur?
- Their clinical condition may necessitate their removal from the trial
- They may choose to withdraw from the trial
360
What must be done to minimise losses to follow up?
- Make follow up practical and minimise inconvenience
- Be honest about commitment required for participants
- Avoid coercion or inducements
- Maintain contact with participants
361
Why may non-compliance with treatment occur?
- 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
How can compliance to treatment be maximised?
- Simplify instructions
- Ask about compliance
- Ask about effects and side effects
- Monitor compliance
363
How can compliance be monitored?
- Tablet count
- Urine level
- Blood level
364
What is not possible in practice?
To have 100% follow up, and to guarantee than 100% compliance took place
365
What is the result of the impossible to obtain 100% follow up and compliance?
Any analysis of outcomes should take this issue into account
366
What are the two interpretations of wether a new treatment is better than a standard treatment?
#NAME?
367
What are the two types of analysis?
#NAME?
368
Who does an ‘as treated’ analysis look at?
Only those who completed follow up and complied with treatments
369
What does ‘as-treated’ analysis compare?
The physiological effects of treatment
370
What is the problem with ‘as-treated’ analysis?
Non-compliers are likely to be systematically different from compliers, and so introduces selection bias and confounding
371
What does an ‘intention-to-treat’ analyse according to?
The original allocation of treatment groups, regardless of wether they completed follow up or complied with treatment
372
What does an intention to treat analysis compare?
The likely effects of using the treatments in routine clinical practice
373
What is the advantage of an intention to treat analysis?
It preserves the effects of randomisation
374
What do as treated analyses test to give?
A larger size of effect
375
What do intention to treat analyses tend to give?
Smaller and more realistic sizes of effect
376
How should clinical trials normally be analysed?
On an intention to treat basis
377
What are the ethical principles for medical research involving human subjects?
- 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
What is a collective ethic?
That all patients should have treatments that are properly tested for efficacy and safety
379
What principles apply in the individual ethic?
- Beneficence
- Non-malifecence
- Autonomy
- Justice
380
What are RCTs for the benefit of?
Future patients
381
How does the collective ethic apply to RCTs?
They aim to properly test treatments for efficacy and safety
382
How does the individual ethic apply to RCTs?
- Do not guarantee benefit
- Could result in harm
- Allocate treatments by chance
- Place burdens and confer benefits
383
What issues should be considered for a clinical trial to be ethical?
- Clinically equipoise
- Scientifically robust
- Ethical recruitment
- Valid consent
- Voluntariness
384
What must be done for a trial to go ahead?
Approval by Research Ethics Committee
385
What is clinical equipoise?
When there is reasonable uncertainty or genuine ignorance about the better treatment or intervention (including the non intervention
386
What are the issues with clinical equipoise?
- 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
What features must a study have to be scientifically robust?
- 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
What must be true for a study to have an appropriate design and protocol?
It must address potential bias and confounding
389
Why must a study have the potential to reach sound conclusions?
To minimise inability to find a clinically important effect using a sample size calculation
390
Give 2 examples for provision of participant safety and well being monitoring
- Data monitoring
| - Patient monitoring
391
What are the two issues of ethical recruitment?
- 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
What are the features of valid consent?
- Knowledgable informant
- Appropriate information
- Informed participant
- Competent decision maker
- Legitimate authoriser
393
How should appropriate information be given?
Verbal and written
394
What should be given after receiving information?
- Cooling off period
| - Ability to opt out
395
What should be given as evidence of valid consent?
Signed consent form
396
Does a signed consent form equate to valid consent?
No
397
What is voluntariness a pre-requisite for?
Consent to be valid
398
What is meant by voluntariness?
The decision should be free from coercion or manipulation, or the perception that coercion or manipulation may take place
399
What is the result of perceived coercion or manipulation?
Invalidates consent as much as actual coercion or manipulation
400
What can coercion be?
Non-access to ‘best’ treatment, lower quality care, disinterest by clinician
401
What can manipulation be?
Exploitation of emotional state, distortion of information or financial inducements
402
What is the issue of voluntariness an issue of?
Autonomy
403
Why is the issue of voluntariness an issue of autonomy?
If undue influence is being exerted so that a potential participant acts uncharacteristically then influence is regarded as unethical
404
What are NHS Trusts / the PCD R&D Office concerned with
- Research governance
- Financial management
- Resource implications
405
What do the Research Ethics Committee concerned say?
‘The dignity, rights, safety and well being of participants must be the primary consideration in any research study’
406
What do the Research Ethics Committee focus particularly on?
- 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
What should healthcare services and interventions be based on?
The best available evidence
408
What should the best available evidence be based on?
Rigorously conduced research
409
What must be looked at in research into best available evidence?
- Primary research studies
- Literature review of studies
- Decision analyses
410
Give two types of literature reviews of studies
#NAME?
411
What are narrative reviews looking at?
Implicit assumptions, opaque methodology
412
What is the result of a study not being reproducible?
It is considered biases and subjective
413
What do systematic reviews look at?
Explicit assumptions, transparent methodology
414
What do decision analyses look at?
- Harms and benefits
| - Cost-effectiveness
415
What is required for systematic reviews require?
A clearly focused question
416
What are explicit statements made about in systematic reviews?
- Types of study
- Types of participants
- Types of interventions
- Types of outcome measures
417
What do systematic reviews involve?
- Systematic literature search
- Selection of materials
- Appraisal
- Synthesis (possibly including meta-analysis)
418
What is the advantage of a systematic review?
It is an extremely credible source of evidence
419
What are the key aspects of a systematic review?
- Explicit
- Transparent
- Reproducible
420
What is a systematic review an overview of?
Primary studies that used explicit and reproducible methods
421
What is a meta-analysis?
A quantitive synthesis of the results of two or more primary studies that addressed the same hypothesis in the same way
422
What is the purpose of meta-analyses?
- 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
What are the quality criteria of meta-analyses?
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
Does a systematic review always include a meta-analysis?
Not always
425
When may a systematic review not contain a meta-analysis?
When clinical heterogeneity is too great
426
How is a pooled estimate odds ratio for all studies calculated?
- 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
In a pooled estimate OR, what does a smaller e.f. mean?
A greater weight to results
428
How are forest plots interpreted?
- 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
What are the problems with meta-analyses?
- Heterogeneity between studies
- Variable quality of studies
- Publication bias in selection of studies
430
What must be done to determine heterogeneity between studies?
- Modelling for variation
| - Analysing the variation
431
How can variation be modelled for?
Fixed effect model vs random effects model
432
How can variation be analysed?
Sub-group analysis
433
Ideally, what should all studies in a meta-analysis be similar in terms of?
- Study design
- Participant profile
- Treatments or exposure
- Outcomes measured
- Statistical analysis used
434
What is the problem with finding identical studies for meta-analyses?
In practice, no two studies are identical
435
What are the two approaches to calculating the pooled estimate odds ratio and its 95% CI to model for variation?
#NAME?
436
What does a fixed effect model do?
Assumes studies are estimating exactly the same effect size
437
What does a random effects model do?
Assumes that the studies estimate similar, not same, effect size
438
How do the results of a fixed effect and random effect model differ?
#NAME?
439
What is the problem with hypothesis testing for heterogeneity using fixed effects and random effects models?
Low statistical power to detect heterogeneity
440
What is often used in hypothesis testing for heterogeneity using fixed effects and random effects models?
10% significance levels
441
What model is superior, fixed effect or random effects?
Much debate
442
What is true if, in a test for heterogeneity, the result is the null hypothesis?
There is no heterogeneity
443
What is true if, in a test for effect, the result is the null hypothesis?
There is no difference in the studies
444
What can random effects modelling account for?
Variation
445
Can random effects modelling explain the variation?
No
446
What can sub-group analysis do?
Can explain heterogeneity
447
What is the advantage of sub-group analysis being able to explain heterogeneity?
It can provide further insight into the effect of treatment of exposure
448
What are the two types of possible sub group analysis?
- Stratification by study characteristics
| - Stratification by participant profile
449
What happens in stratification by study characteristics?
Subsets of ‘whole’ studies are defined by characteristics
450
What characteristics can sub-sets of whole studies be characterised by?
- Study design
- Length of follow up
- Participant profile
- Recruitment criteria
451
What happens in stratification by participant profile?
Data is analysed by type of participants
452
What is the advantage of stratification by participant profile?
Has greater statistical power than for individual studies
453
What is the disadvantage of stratification by participant profile?
Data is often unreliable
454
What can variable study quality be due to?
- Poor study design
- Poor design protocol
- Poor protocol implementation
455
Order studies from least to most susceptible to bias and confounding?
Randomised control trials → Non-randomised control trials → Cohort studies → Case-control studies
456
What are the two main approaches to variable quality of studies?
- 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
Give an example of a meta-regression analysis
Weighted linear regression of effect size against quality
458
What are the main components for assessing the quality of RCTs?
- Allocation methods
- Blinding and outcome assessment
- Patient attrition
- Appropriate statistical analysis
459
Who assesses quality?
>1 assessor
460
What is the purpose of having >1 assessor?
To handle disagreement
461
What is the problem with assessors being blinded to results?
It’s sometimes difficult
462
Why does publication bias occur?
Studies with statistically significant or favourable results are more likely to be published than those studies with non-stastically significant or unfavourable results
463
Where does publication bias particularly occur?
To small studies
464
What does publication bias tend to lead to?
Biased selection in favour of studies in favour of demonstration of effects
465
How can publication bias be identified?
- 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
What do statistical tests for publication bias tend to be?
Weak
467
How is a funnel plot showing publication bias interpreted?
- 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
