Week 2 Flashcards
(38 cards)
1
Q
What are cohort studies?
A
- Target population
- Those without a disease or condition or factor of interest
- Follow people through time
After a year or two years, you can divide the people you have been following in 2 groups, those who have been exposed to a certain factor e.g. smoking, and those who got sick and didn’t get sick
2
Q
What is a cohort study?
A
- Following a group of people through time
- Systematic data collection
- You’re looking for risk factors
- Who gets sick and who doesn’t e.g. Framingham Heart Study: What causes cardiovascular disease. Every year people in the village would get health questionnaires. Aimed to follow people through time, know what they have done throughout their life.
- What are risk factors e.g. for people to readmitted into hospital
- Strong and robust research
Florence nightingale: Founder of epidemiology (what soldiers got infections, what soldiers didn’t), resulted in better hygiene in hospital
3
Q
Example of a longitudinal study in speech pathology
A
- 7% of 4 year old Aussies are affected by impaired language
- Research on prevalence and natural history of language impairment is sketchy
- Only a prospective longitudinal study using a large sample size can quantify risk and protective factors
- Find what causes language development
Study design: - Families of infants living in Melbourne were recruited when their children were 8 months old
- Collected: Communication, socio-emotional development, family background, history, general health and wellbeing etc
- Measurements: 8, 12 months. 2, 3, 4 years
Assessment tools: 2 years: MacArthur Bates communicative development inventories. 4 years Clinical evaluation of Language Fundamentals Preschool Second Edition (CELF-P-2) Australian Adaptation
4
Q
Examples of cohort studies
A
- Prospective: People with Laryngectomees were interviewed at the beginning of rehabilitation and 1 year after. Speech intelligibility was measured with a standardized test and patients self-assessed their own motivation shortly after the surgery. Head and Neck cancer
- Retrospective: The study included 194 patients who underwent total laryngectomy. Multiple logistic regression methods were used to evaluate early risk factors for an enlarged TEP
- Identify natural cause of disease
5
Q
What is regression and regression analysis/statistical tests
A
- Regression analysis is a statistical process for estimating the relationships among variables
- It includes many techniques for modelling and analysing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables
Regression analysis helps one understand how the typical value of the dependent variable (or criterion variable) changes when any one of the independent variables is varied, while the other independent variables are held fixed
- It includes many techniques for modelling and analysing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables
6
Q
What is an example of regression analysis?
A
- Langmore et al. Patients with swallowing disorders who get pneumonia. Outcome was in 189 patients she followed through time who gets pneumonia. Through logistic regression, people dependant for feeding have a factor of 90.9 have 20x more chance of getting sick and pneumonia than those who are not dependant for feeding (dependant for oral care/feeding). Doing something wrong with oral care in health professions
- Show through time, patients get sick, some are healthy but you can see risk factors
Higher the odds ratio, the higher the risk and the more concerned we will be
- Show through time, patients get sick, some are healthy but you can see risk factors
7
Q
Disadvantages of cohort studies
A
- Lengthy and expensive
- May require very large samples
- Not suitable for rare diseases
- Not suitable for diseases with long-latency
- Unexpected environmental changes may influence the association
- Non-response, migration and loss-to-follow-up
- Sampling, ascertainment and observer biases are still possible
8
Q
Advantages of cohort studies
A
- Can establish population-based incidence
- Accurate relative risk (risk ratio) estimation
- Can examine rare exposures (asbestos > lung cancer)
- Temporal relationships can be inferred (prospective design)
- Time-to-event analysis is possible
- Can be used where randomization is not possible
- Magnitude of a risk factor’s effect can be quantified
- Selection and information biases are decreased
Multiple outcomes can be studied
9
Q
Types of bias: Loss of follow up
A
Arises when there is a substantial difference in follow-up between those who are exposed and who are not exposed
10
Q
Types of bias: Selection
A
Differences in the way which the exposed participants and the non-exposed participants are chosen (more so in case-control studies). May arise and compromise generalisability of findings if the cohort is not sufficiently representative of a defined population
11
Q
Types of bias: Classification
A
This bias can arise when members of the cohort are mis-classified in terms of their exposure to the factor of interest and/or in terms of their having the outcome of interest
12
Q
Types of bias: Measurement
A
If there are inaccuracies in the measurement of exposure, or outcome or both. This form can also arise if there is a difference between the exposed and the non-exposed groups, in the way in which either exposure and/or outcome is measured
13
Q
Types of bias: Recall
A
only for retrospective studies where there may be differences in the accuracy and/or completeness of recall
14
Q
What is confounding?
A
A factor that is a risk for the health outcome being studied and is associated with the exposure being studied, but is not part of the causal pathway
15
Q
What are potential confounders and what they must be
A
Potential confounders:
- Age
- Income
- Gender
- Ethnicity
Confounders must be:
- Associated with exposure of interest
- Be associated with the outcome of interest
- Not be a result of or caused by the exposure of interest
16
Q
Strengths of cohort studies
A
- Cohort studies are especially useful for investigating rare exposures, and diseases with long induction and latent periods.
- Cohort studies can investigate multiple effects of an exposure.
- Cohort studies allow direct measurement of the health outcome of interest in the exposed and not exposed groups.
- Prospective cohort studies:
-can provide insight into the temporal relationship between the exposure and the health outcome of interest.
-give good information on exposures.
-are less susceptible to bias than are retrospective cohort studies.
17
Q
Weaknesses of cohort studies
A
- Cohort studies are limited in capacity for investigating rare health outcomes.
- Findings are often greatly influenced by loss to follow up.
- If prospective, cohort studies can be very expensive and time-consuming.
If the cohort study is retrospective, there may be poor quality information on exposures and health outcomes.
18
Q
Analysis of data in cohort studies
A
Degree of exposure and outcome can be quantified in a number of ways, however is usually quantified as the relative risk RR
19
Q
What is Relative Risk/Risk Ratio
A
- Likelihood or the risk of occurrence of the outcome of interest for the exposed group, compared with the likelihood or risk of occurrence of the outcome of the non-exposed group
- Corresponds to the difference in the likelihood or risk of the outcome for the exposed group and the likelihood or rusk of the outcome for the non-exposed group
- As cohort studies follow over time, it is possible to calculate incidence rates (the number of new cases of the disease or other health conditions that appear during the time period of the study)
- For a cohort study, the relative risk involves a comparison of the incidence rate (for the disease or other health condition) in the exposed group with the incidence rate in the not exposed group
RR = Incidence in the exposed (Ie)/Incidence in the not exposed (lo)
20
Q
How do you interpret RR of an outcome?
A
- If the RR equals 1.0 then the rate of the outcome of interest is the same in the exposed and not exposed groups. That is, participants in the two groups are equally likely to develop the outcome of interest.
- If the RR is greater than 1.0, then participants in the exposed group are more likely to develop the outcome of interest than are participants in the not exposed group.
- If the RR is less than 1.0, then participants in the exposed group are less likely to develop the outcome of interest, than are participants in the not exposed group
- If the RR is greater or less than 1, then there is a degree of association between exposure and outcome of interest
21
Q
Confidence intervals and Risk Ratios
A
- CI enables the determination of a lower limit and an upper limit within which the real or true value (RR) for a population is most likely to lie
- All of the possible values that the population value can have, between these two limits
- The value for a sample (RR) provides an estimate of the value for the population from which the sample was taken
- Constructing CI around the value for the sample, it can be established, in terms of a range of values, what the corresponding value for the population is likely to be
- If a 95% confidence interval is used, we can be 95% sure that the population value lies somewhere within this interval
95% certainty that the population value lies between the lower and upper limits specified by the confidence interval is considered sufficient to allow conclusions to be generalised from samples to populations
22
Q
What is confidence interval
A
- If relative risk is 1, then there is no difference in the likelihood of the outcome for the exposed and non-exposed groups
- If it is greater or less than 1 then there is a degree of association
- If the range of the CI contains 1.0, then (in the population) the rate of the outcome of interest could be the same for both the exposed and not exposed groups, and the study result (the association between outcome and exposure for the sample) is deemed to be not statistically significant.
- If the range of the CI does not contain 1.0, and lies above 1.0, then the study result is deemed to be statistically significant. That is, there is an association (in the population) between exposure and outcome, such that those who are exposed are more likely to develop the outcome of interest, than are those who are not exposed.
If the range of the CI does not include 1.0, and lies below 1.0, then the study result is deemed to be statistically significant. That is, there is an association (in the population) between exposure and outcome, such that those who are exposed are less likely to develop the outcome of interest, than are those who are not exposed.
23
Q
What is Odds Ratio
A
- The degree of association between exposure and outcome
- The odds of an event occurring in one group compared with the odds of the event occurring in the other group
- For a cohort study, the odds ratio is the odds of developing the outcome of interest for the exposed group compared with the odds of developing this outcome for the not exposed group
- If the OR is 1, then the odds are the same and there is no association
- If the OR is more or less than 1, then there is a degree of association between exposure outcome
- If the OR is greater than 1, then the outcome of interest is more common in the exposed group than in the unexposed group
- If the OR is less than 1, then the outcome of interest is less common in the exposed group than the unexposed group
The confidence interval around the odds ratio can be used to determine statistical significance, in the same manner as was described above with regards to the relative risk
24
Q
What is logistic regression
A
- Enables factors of interest (predictors, presence or absence of disease)to be put in a model to determine their association or relationship with the outcome of interest
- Produces statistics that are referred to as adjusted odds ratios
Logistic regression can only be used when the outcome is dichotomous (where there are only two possible outcomes e.g. Disease/no disease)
25
What are nested studies
- Side study taking place during the time period of the cohort study
- Prospective cohort studies may have retrospective cohort studies within them
- Results of studies that are nested within cohort studies are usually reported separately from the findings of the cohort itself
- Reports of studies associated with a cohort study may have the words 'prospective cohort study' in their title and also in the description. They do not make it clear that what is being reported in the paper is a side study associated with the main cohort study
Common in cross-sectional studies that are conducted in parallel with a prospective cohort study
26
What are cross-sectional studies
- Main one: Where the exposure and the outcome are simultaneously present and are both measured at one point in time
- e.g. exposure of tobacco smoking and pulmonary disease, it could be done to measure blood cholesterol levels for the smoking and non-smoking groups
27
Selection of the cohort
- Two groups in the cohort at the point in time that is coincident with the commencement of the study (where the exposure has already occurred but the outcome is yet to occur), a primary requirement for the selection of the cohort is that the exposed group should be as similar as possible to the not exposed group
The choice of a cohort to be studied depends on;
- The research question under investigation
- The frequency of the exposure
- The length of time required for a follow up
- For common exposures, the exposed group can come from a wide variety of populations
If a rare exposure is being investigated, it is appropriate to select group members from amongst those who have been exposed
28
Measures of Exposure
- Dichotomous: Where there are only two alternatives e.g. exposure Y/N
- Continuous: Where what is being measured can have any possible value within a specified range (e.g. body weight)
The source of outcome data for both the exposed and not exposed participants should be the same in every way and can come from a variety of sources: Hospital records, death certificates, registers of notifiable diseases, medical examinations, questionnaires
29
What is prognosis and aetiology
- Prognosis: what happens over time to people with a specific conditions, making predictions about the future e.g. if I have this treatment when can I expect to be back at work
- Aetiology: Causes of disease, or what makes it more likely. What risk factors are for developing a disease, once identified research can explore whether targeting those risk factors changes the outcome
- A prospective cohort study is the best research design about prognosis and aetiology
RCT is the best research for answering questions about intervention and effectiveness
30
Level of evidence for questions about prognosis
Level of Evidence
Questions about Prognosis
Level I
Systematic Review of Level II studies
Level II
Prospective Cohort Study
Level III-1
All or None*
Level III-2
Analysis of prognostic factors amongst persons in a single arm of an RCT
Level III-3
Retrospective Cohort Study
Level III-4
Case series or cohort study of persons at different stages of the disease
31
Level of evidence for questions about Aetiology
Questions about Aetiology
Systematic Review of Level II studies
Prospective Cohort Study
All or None*
Retrospective Cohort Study
Case-Control Study
Cross-Sectional Study or Case Series
32
What are cohort studies
- Prospective cohort studies are longitudinal observational studies that examine associations between exposures and outcomes
- Cohort studies that seek to answer questions about aetiology are interested in associations between an exposure (risk factor) and an outcome they are theory driven
- Interested in the what and why and try to control confounding variables
33
Aetiology cohort studies may examine:
- A cohort of healthy people to identify variables that cause disease
- A cohort of people with a disease/condition to identify variables that cause specified problem or sequalae
Cohort studies that answer questions about prognosis are interested in associations between predictor variables and outcome variables. They seek to identify variables that predict a specified outcome and are data driven
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34
Prognosis cohort studies may examine
- A cohort of healthy people to identify variables that predict who will develop a disease
A cohort of people with a disease/condition to identify variables that predict who will develop a specified outcome
35
What is the difference between prospective and retrospective studies?
- Prospective: Follows a group of people forward in time, collecting data on exposures before the outcome of interest occurs
Retrospective: Looks back in time at existing data to examine relationships between an exposure and outcome that has already happened
36
3 Main components of critical appraisal
- Validity: Are the results trustworthy? Are the study's results credible and free from bias. This involves examining the study design, methodology and execution to ensure the findings accurately represent the truth
- Impact: Are the results significant? Determine the magnitude of effect and its clinical relevance in order to understand the practical implications of the result
Applicability: Are the results relevant to your practice? This involves assessing if the study population, interventions and outcomes align with your clinical setting or patient
37
Why is critical appraisal important to allied health
As future practitioners, the use of the best research evidence is vitally important in order to give our patients the best health outcomes. For allied health, critical appraisal is important so we know which research has been adequately conducted and which research is the best to use in practice. It allows us to see which studies are trustworthy compared to untrustworthy or possibly predatory research.
