4. Cohort studies
Summary
TLDRThis video module focuses on critical appraisal of cohort studies, emphasizing their importance in healthcare research. It explains why observational studies are necessary when RCTs are not feasible or ethical. The module introduces the concept of risk ratio, illustrates its calculation with an example, and discusses how to interpret it. It also guides viewers on how to appraise cohort studies using a checklist, applying it to a study on lithium treatment and dementia risk. The video concludes with a quiz for viewers to test their understanding.
Takeaways
- π This video module focuses on the critical appraisal of cohort studies using the CASP approach.
- π€ Observational studies are necessary when RCTs are not feasible, unethical, or impractical for rare outcomes.
- π₯ Cohort studies involve identifying participants without an outcome of interest, classifying them by exposure status, and following them over time.
- π¬ An example given is a cohort study on smoking and lung cancer, where researchers follow participants to see lung cancer development.
- π The risk ratio is a common measure used in cohort studies to express the difference in risk between exposed and unexposed groups.
- π’ A risk ratio greater than one indicates an increased risk of disease due to exposure, while less than one suggests a protective effect.
- π The CASP checklist is introduced for critically appraising cohort studies, focusing on validity, results' trustworthiness, and relevance.
- π The study by Gerhardt et al. (2015) on lithium treatment and dementia risk is used as an example to apply the CASP checklist.
- π§ Selection bias, measurement bias, and confounding are key issues to consider when critically appraising cohort studies.
- π Statistical models can adjust for confounders to provide a clearer understanding of the relationship between exposure and outcome.
- β± The duration of the follow-up period in cohort studies is crucial to allow the outcome to manifest and to maintain a representative sample.
Q & A
What is the main focus of the fourth video in the critical appraisal series?
-The main focus of the fourth video is the critical appraisal of cohort studies using the CASP approach.
Why are observational studies necessary in healthcare research?
-Observational studies are necessary because sometimes it's not possible or ethical to conduct randomized controlled trials (RCTs), especially when studying rare outcomes or potentially harmful interventions.
What is the difference between experimental studies and observational studies in terms of researcher involvement?
-In experimental studies, researchers manipulate exposures to observe outcomes, whereas in observational studies, they do not manipulate exposures but simply observe what occurs.
What is a cohort study and how does it relate to risk factors and outcomes?
-A cohort study is a type of observational study where researchers identify participants without the outcome of interest, classify them by exposure status, and follow them over time to observe the development of the outcome.
How is the risk ratio calculated in cohort studies?
-The risk ratio is calculated by dividing the risk of developing the outcome in the exposed group by the risk of developing the outcome in the unexposed group.
What does a risk ratio greater than one indicate in a cohort study?
-A risk ratio greater than one indicates that the exposure increases the risk of disease.
What is the purpose of the CASP checklist for critically appraising cohort studies?
-The CASP checklist helps assess the validity, trustworthiness of results, and value of relevance in cohort studies.
What is the importance of considering confounding factors in cohort studies?
-Confounding factors can distort the relationship between exposure and outcome, either hiding a true relationship or creating a false one. Statistically adjusting for confounders can help estimate their impact.
How does the length of the follow-up period in a cohort study affect the results?
-The follow-up period should be long enough for the outcome to manifest. Insufficient follow-up can lead to incorrect measurements of the exposure-outcome relationship.
What does a hazard ratio represent in cohort studies and how does it differ from a risk ratio?
-A hazard ratio represents the rate at which an event occurs over time, taking into account the duration of exposure. Unlike the risk ratio, it accounts for the timing of events.
How can the precision of results in cohort studies be assessed?
-The precision of results can be assessed by examining the confidence intervals. Narrower intervals indicate higher precision.
What is the role of the CASP checklist in evaluating the believability of results in cohort studies?
-The CASP checklist helps evaluate the believability of results by considering factors such as bias, confounding, and the wider body of research.
Outlines
π Introduction to Cohort Studies
This paragraph introduces the critical appraisal of cohort studies within the context of healthcare research. It explains why observational studies are necessary when randomized controlled trials (RCTs) are not feasible or ethical. The paragraph outlines the purpose of cohort studies, which is to observe risk factors, exposures, and outcomes without manipulating exposures. It also introduces the concept of risk ratio as a measure to quantify risk in cohort studies and provides an example of a cohort study investigating the link between smoking and lung cancer. The risk ratio is calculated by dividing the incidence of disease in the exposed group by the incidence in the unexposed group, indicating the strength of the association between exposure and outcome.
π Understanding Risk Ratio and Cohort Study Appraisal
This section delves into how to calculate and interpret the risk ratio in cohort studies. It uses a fictional dataset to demonstrate the calculation process, emphasizing that a risk ratio greater than one indicates an increased risk of disease due to exposure, while a ratio less than one suggests a protective effect. The paragraph also discusses the importance of critically appraising cohort studies using a checklist to assess their validity, reliability, and relevance. An example of a cohort study by Gerhardt et al. (2015) on lithium treatment and dementia risk is presented to illustrate how the checklist is applied in practice.
π§ Critical Appraisal Checklist Application
The paragraph discusses the application of the critical appraisal checklist to a specific cohort study. It covers various aspects such as selection bias, measurement bias, confounding, and the duration of the study's follow-up period. The study's exposure and outcome measurements are examined for reliability, and potential confounders are identified and discussed. The importance of a long enough follow-up period to observe the outcome and the impact of dropout rates on the study's validity are highlighted. The paragraph also touches on the use of statistical models to adjust for confounding factors and the interpretation of the hazard ratio, which is similar to the risk ratio but accounts for the time at which events occur.
π Hazard Ratio and Study Results Precision
This final paragraph focuses on the precision of study results as represented by confidence intervals and the believability of these results. It explains how confidence intervals quantify the range within which the true value is likely to lie, with narrower intervals indicating higher precision. The paragraph also discusses factors affecting the believability of results, such as bias, confounding, and the biological plausibility of the findings. It concludes by mentioning the upcoming module on case-control studies and encourages viewers to test their knowledge through an online quiz. The video series is credited to the Cochrane Common Mental Disorders Group at the University of York, with support from various NHS trusts and the Economic and Social Research Council.
Mindmap
Keywords
π‘Cohort Studies
π‘Critical Appraisal
π‘Risk Ratio
π‘Observational Studies
π‘Selection Bias
π‘Measurement Bias
π‘Confounding
π‘Follow-up Period
π‘Hazard Ratio
π‘Confidence Intervals
π‘Biological Plausibility
Highlights
Focus on critical appraisal of cohort studies using the CASP approach.
Why observational studies are necessary despite the strength of RCTs.
Definition and importance of cohort studies in healthcare research.
Explanation of risk ratio and its calculation in cohort studies.
Example of calculating relative risk with fictional data.
Cohort studies as the strongest design among observational studies.
Description of how cohort studies express risk differences.
Importance of critically appraising cohort studies for quality assessment.
Introduction to the CASP checklist for cohort studies.
Application of the checklist to a sample cohort study on lithium treatment and dementia risk.
Consideration of a clearly focused question in cohort studies.
Assessment of selection bias in cohort recruitment.
Measurement bias considerations in exposure and outcome assessment.
Confounding factors and their impact on study results.
Importance of adequate follow-up time in cohort studies.
Use of hazard ratio to express the association between exposure and outcome.
Precision of results represented by confidence intervals.
Assessing the believability of results in cohort studies.
Consideration of the potential local applicability of study results.
Introduction to the next module on case-control studies.
Acknowledgment of the development team and supporting organizations.
Transcripts
welcome to the fourth video in this
series of critical appraisal modules in
this module we will be focusing on the
critical appraisal of cohort studies
using the critical appraisal skills
program our cusp approach in the
previous module we spoke to you about
our cities and their importance in
healthcare particularly in terms have
been able to tribute causality you may
ask why do we need observational studies
if the RCT design is so strong in terms
of attributing and causality but
sometimes it isn't possible to test some
hypotheses and trials it's also
sometimes unethical to undertake a trial
of an agent we believe could be harmful
and it is not feasible to study some
very rare outcomes and trials for this
reason observational studies do have an
important place in healthcare generally
in observational studies in health
researchers are interested in risk
factors our exposures and outcomes often
diseases
unlike in experimental studies
researchers do not manipulate exposures
and observational studies they simply
observe what is occurring and then they
can calculate measures to quantify the
extent of the risk for the learning
outcomes we will introduce you to cohort
studies and describe their purpose and
value in the context of healthcare
research and show you how we can
critically appraise one using the class
checklist we will also talk about the
risk ratio how to calculate these and
how to interpret them in cohort studies
finally there will be a link to a short
quiz at the end of this video which will
give you the opportunity to test your
knowledge and concepts we will have
discussed using multiple
questions and answers a cohort study is
the strongest research design of the
observational studies it generally
involves the researcher identifying
research participants who do not have
the outcome of interest the researcher
then classifies participants according
to their exposure status and follows the
participants over time to see whether or
not they develop the outcome in question
to take a simple example
if a researcher is interested in whether
or not smoking causes lung cancer the
research you would identify a group of
people you do not have lung cancer and
then classify them according to whether
or not they are smokers the researcher
would then follow up the participants
over time to compare rates of lung
cancer between the groups in the cohort
according to their smoking status so how
do you express the different rate in
risk between exposed and unexposed
members of the cohort the most common
method of doing this is the risk ratio
the risk ratio is the ratio of the
incidence of disease in the exposed
group to the incidence of disease in the
unexposed group incidence refers to new
cases of a disease relative risk can
quantify the strength of an association
between exposures and outcomes if the
relative risk is greater than one it
means that the exposure increases the
risk of disease the higher the number
the greater the risk if the relative
risk is less than one it means that the
exposure decreases the risk of disease
the lower the number the more the factor
is protective if a risk ratio is exactly
then it means there is no difference in
risk between exposed and unexposed
individuals so let's take an example in
which we'll calculate the relative risk
together
we'll look at some fictional data
imagine that we're still thinking about
the relationship between smoking and
lung cancer we might have conducted a
cohort study and obtained the following
results we can calculate the risk ratio
by first calculating the risk of
developing lung cancer in the exposed
group then by calculating the risk of
developing lung cancer in the unexposed
group and then by dividing the risk in
the exposed group to the risk in the
unexposed group
I've given key sections of the table the
letters a b c and d as this is a common
convention to calculate the risk of
developing lung cancer in the exposed
group it's a divided by a plus b which
gives not point 8 5 to calculate the
risk of developing lung cancer in the
unexposed group it's C divided by C plus
T which gives not point naught 5 to
express the risk of developing lung
cancer in the exposed to the unexposed
group it's not point 8 5 divided by
naught point naught 5 which gives 17 so
that means that people who smoke are 17
times more likely to develop lung cancer
than non-smokers according to this
fictional data cohort studies are an
extremely useful study design for
quantifying the strength of association
between an exposure and an outcome
however like on research that
and healthcare their quality can vary so
it is important that readers of cohort
studies critically appraise the policy
of the research surely the caste program
has produced a checklist for critically
appraising cohort studies which you can
access by following the link below this
video let's have a look at this
checklist and then we'll apply its use
to a sample cohort study we can see that
because cohort studies checklist again
separates the three key principles of
critical appraisal of validity
trustworthiness of results and value of
relevance into three sections a B and C
respectively let's see how they can be
addressed with an example the study will
use to work through this checklist is by
Gerhardt's at al 2015 on lithium
treatment and risk for dementia in
adults with bipolar disorder
population-based cohort study which you
can also access by selecting the link
below this video the first question in
the checklist is to consider whether the
cohort study examined a clearly focused
question the answer for this study would
appear to be yes as the study considered
the association between lithium and
dementia risk the research question is
contextualized against the biological
background of lithium inhibiting
glycogen synthase kinase 3 and enzyme
implicated in the etiology of dementia
the second question looks at whether the
cohort was recruited in an acceptable
way this question is mainly about
selection bias bias is a systematic
error in a research study which results
in incorrect measurement of the
relationship between exposure our
intervention
and outcome selection bias refers to
bias in terms of the way participants
were selected as research participants
ie when the research participants truly
representative of the research
population are are the participants in
some way and typical this study's
participants of people aged over 50 with
a diagnosis of bipolar disorder from 8
large US states and Medicaid insured
u.s. population Medicaid is a social
health care program for Americans with
disabilities are lower incomes
the third question considers a different
type of bias namely measurement bias
this refers to bias in terms of the way
exposure and our outcome a measured
which could lead to an incorrect
estimate of the relationship between
exposure and outcome it is important to
consider factors such as whether or not
exposures were assessed via self-report
as this may be affected by social
desirability bias are the fal ability of
memory the exposure in this study was
lithium use and it was assessed by a
health administrative data so it is more
likely that the measurement of the
exposure and outcome are more reliable
than self-report measurements this
question relates to a session for
possible measurement bias in measuring
outcome which in this case was
development of dementia things to
consider in this criteria relate to
whether or not the outcome was measured
subjectively or objectively with
objective measures of outcome been
generally more reliable and to consider
whether or not Assessors were blind to
exposure status this means whether or
not to assess
knew whether or not a person had or have
not been exposed as if they know this it
might affect their assessment of outcome
particularly in more subjective outcome
measurements sometimes however the fact
of whether or not Assessors are blind is
not so essential if the outcome is
clear-cut for example this studies
outcome is more of a factual objective
outcome less likely to be affected by
Assessors knowledge of exposure status
and the use of health administrative
data lessens the likelihood that the
results of the study have been
compromised by measurement bias in
assessing the outcome this question
relates confounding a confounder is a
factor which is independently associated
with an exposure and an outcome and
which can either hide a true
relationship between an exposure and
outcome or make it seem like there is a
relationship between exposure and
outcome when in facts there is no
relationship possible confounders can
often relate to age gender or health
related behaviors such as dietary
factors or whether or not people
exercise it is possible to estimate the
impact which confounders may have on a
research study by statistically
adjusting for them when analyzing the
relationship between exposure and
outcome in this study the Astor's
present an adjusted statistical model a
model which adjusted for gender age and
ethnicity all of which are common
confounders and a statistical model
which suggested for age gender and
ethnicity as well as other factors which
are potential confounders the authors do
note that Nassim treated patients were
found to have a lower risk of developing
dementia in their study but also that
lycium treated patients a lower rates of
baseline cerebrovascular
disease and diabetes most of which are
actually risk factors for dementia and
therefore factors which could be
confounders this question relates the
time spent and following up for the
cohort cohort studies are generally
undertaken over several years and it is
important that the study follow-up
period is long enough for the outcome to
manifest itself it's also important that
the study tries to collect data from as
many people who started in the cohort as
possible and not to allow people to drop
out as the people who do drop out may
not be typical of the ones remain in the
study and this again could lead to an
incorrect measurement of the
relationship between exposure and
outcome the maximum follow-up time
period in this study was three years and
judgment is required as to whether or
not this outcome period is long enough
to allow development of the outcome
versus the outcome will be occurring in
this study the authors found that 301 to
365 days of lithium exposure was
associated with reduced dementia risk
but that no association was found for
shorter duration of exposure to lithium
the measurement used to express the
association between lissome exposure and
dementia risk is the hazard ratio which
is similar to the risk ratio we looked
at earlier but the hazard ratio accounts
for the rate or time period at which
event to happen and instead of just
looking at whether or not an event
happened the hazard ratio for 301 to 365
days of lithium exposure was naught
point seven seven meaning that lithium
exposure is protective because the
hazard ratio is less than one like risk
ratios if a hazard ratio is under 1 then
this means that an exposure is
protective whereas if a hazard ratio is
higher than one then this means that an
exposure raises the
of an outcome occurring the precision of
results are represented by confidence
intervals confidence intervals relate to
the range in which the true value lies a
research study generally involves a
sample rather than everyone in the
research population and even in a
robustly conducted study there will
always be some error in the sample
compared to the population a confidence
interval quantifies this by
acknowledging that while the sample
produced a certain value the true value
in the population is likely to be within
a certain range a narrower confidence
interval indicates higher precision of
results so a confidence interval of
three to far around the risk ratio of
three point five would be more precise
than a confidence interval of t27 around
the same risk ratio three point five the
believability of results can be assessed
by considering the factors we have
previously discussed such as confirmed
in our bias it's also important to
consider whether the results may have
been affected by chance assessing the
believability of results also requires
judgment and consideration of factors
such as the biological plausibility of
the relationship between exposure and
outcome and the contextualization of the
cohort study in the wider body of
research in the field questions 10 11
and 12 of the cusp checklist follow on
from this theme and require judgment to
consider the potential local
applicability of the results the fifth
module in this series will look at case
control studies and we will be following
a similar format as we used in this
video to appraise an example of a recent
study thank you for listening these
training videos have been developed by
the Cochran common mental
Dada's group at the University of York
with support from TSS can wear valleys
NHS foundation trust Northumberland Tyne
and Wear NHS Foundation Trust and the
Economic and Social Research Council if
you would like to test your knowledge on
the topics introduced in this module
please follow the link below which will
take you to a short online quiz
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