4. Cohort studies

Summary

This 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

• 🔍 This video module focuses on the critical appraisal of cohort studies using the CASP approach.
• 🤔 Observational studies are necessary when RCTs are not feasible, unethical, or impractical for rare outcomes.
• 👥 Cohort studies involve identifying participants without an outcome of interest, classifying them by exposure status, and following them over time.
• 🚬 An example given is a cohort study on smoking and lung cancer, where researchers follow participants to see lung cancer development.
• 📊 The risk ratio is a common measure used in cohort studies to express the difference in risk between exposed and unexposed groups.
• 🔢 A risk ratio greater than one indicates an increased risk of disease due to exposure, while less than one suggests a protective effect.
• 📚 The CASP checklist is introduced for critically appraising cohort studies, focusing on validity, results' trustworthiness, and relevance.
• 📝 The study by Gerhardt et al. (2015) on lithium treatment and dementia risk is used as an example to apply the CASP checklist.
• 🧐 Selection bias, measurement bias, and confounding are key issues to consider when critically appraising cohort studies.
• 📈 Statistical models can adjust for confounders to provide a clearer understanding of the relationship between exposure and outcome.
• ⏱ 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

00:00

🔎 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.

05:01

📊 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.

10:01

🧐 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.

15:02

📉 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.

Keywords

💡Cohort Studies

Cohort studies are a type of observational study where researchers select a group of participants who have not yet developed the outcome of interest and follow them over time to observe the development of outcomes related to exposure status. In the context of the video, cohort studies are highlighted as a crucial research design in healthcare, particularly when randomized controlled trials are not feasible or ethical. The video discusses how to critically appraise cohort studies using the CASP checklist, emphasizing their importance in understanding risk factors for diseases.

💡Critical Appraisal

Critical appraisal is the process of systematically evaluating research evidence for its validity, results' trustworthiness, and relevance to a specific context. The video focuses on teaching viewers how to critically appraise cohort studies using the CASP approach, which involves assessing the study's methodology, potential biases, and the strength of the association between exposure and outcome.

💡Risk Ratio

The risk ratio is a statistical measure used in cohort studies to express the ratio of the incidence of disease in the exposed group to the incidence in the unexposed group. It quantifies the strength of the association between an exposure and an outcome. In the video, the risk ratio is used to illustrate how smoking is associated with a significantly higher risk of lung cancer, with smokers being 17 times more likely to develop lung cancer than non-smokers.

💡Observational Studies

Observational studies are a type of research where researchers observe and analyze natural occurrences without manipulating any variables. These studies are contrasted with experimental studies in the video, where researchers actively intervene. Observational studies are emphasized for their importance in healthcare research when trials are not possible or ethical, and they are used to study rare outcomes or when testing potentially harmful agents.

💡Selection Bias

Selection bias refers to a systematic error in research studies that results from the way participants are chosen, which can lead to incorrect measurements of the relationship between exposure and outcome. The video discusses selection bias in the context of how participants are recruited for cohort studies, stressing the importance of ensuring that the sample is representative of the population to avoid biased results.

💡Measurement Bias

Measurement bias occurs when there is bias in the way exposures and outcomes are measured, which can lead to incorrect estimates of the relationship between them. The video explains measurement bias in relation to how exposure to lithium was assessed through health administrative data, suggesting that this method is more reliable than self-report, thus reducing the likelihood of measurement bias.

💡Confounding

A confounder is a factor that is independently associated with both the exposure and the outcome, and can either mask a true relationship or create a false one. The video discusses confounding in the context of adjusting for factors like age, gender, and ethnicity in statistical models to account for their potential influence on the relationship between lithium treatment and dementia risk.

💡Follow-up Period

The follow-up period in a cohort study refers to the duration of time during which participants are monitored to observe the development of the outcome. The video emphasizes the importance of having a sufficiently long follow-up period to allow the outcome to manifest and to minimize dropout rates, which could introduce bias. In the example study discussed, the maximum follow-up time was three years.

💡Hazard Ratio

The hazard ratio is a measure used in cohort studies that accounts for the rate at which an event occurs over a specific time period. It is similar to the risk ratio but adjusts for the timing of events. The video uses the hazard ratio to discuss the protective effect of lithium exposure on dementia risk, with a hazard ratio less than one indicating a reduced risk.

💡Confidence Intervals

Confidence intervals provide a range within which the true value of a population parameter is likely to fall, based on sample data. They indicate the precision of the results, with narrower intervals suggesting higher precision. The video discusses how confidence intervals can be used to assess the believability of results, taking into account factors like potential biases and the sample size.

💡Biological Plausibility

Biological plausibility refers to the extent to which a research finding is consistent with current biological understanding and the laws of nature. The video mentions considering biological plausibility when assessing the believability of results, ensuring that the relationship between exposure and outcome is not only statistically significant but also makes sense in the context of existing knowledge.

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