Cohort Studies Hanna E. Bloomfield, MD, MPH Professor of Medicine Associate Chief of Staff, Research...

Cohort StudiesCohort Studies

Hanna E. Bloomfield, MD, MPHHanna E. Bloomfield, MD, MPHProfessor of MedicineProfessor of Medicine

Associate Chief of Staff, ResearchAssociate Chief of Staff, Research

Minneapolis VA Medical CenterMinneapolis VA Medical Center

Empowering Evidence 2014

DisclosureDisclosure

• I have no financial relationships to disclose.

• I will not discuss off label use and/or investigational use in my presentation


Learning Objectives

By the end of this session participants should understand

•The difference between a prospective and retrospective cohort study•The difference between a cohort and a case control study •The concept of bias•The concept of confounding


Evidence Pyramid

Clinical, Epidemiologic,Health Services

Increasing strength of evidence for

clinical application

Basic Science


Cohort Studies

• Overview

• How they differ from Case Control Studies

• Bias

• Confounding

• Characteristics of a GOOD cohort study


Cohort Studies

May be used to study…

• Etiology/ Risk Factors/Prognosis

• Effect of Treatments– Hypothesis generating!

• May be either– Prospective– Retrospective


Prospective Cohort Study To evaluate Etiology/Risk Factors/Prognosis

samplesample

1000High blood pressure


60 Heart Attacks

60 Heart Attacks

Risk Factor Follow-up Outcome

populationpopulation

1000Normal blood pressure

1000Normal blood pressure 20 Heart

Attacks20 Heart Attacks

Study begins here

PRESENT, 2014 FUTURE, 2014-18


Retrospective Cohort Study To evaluate Etiology/Risk Factors/Prognosis

samplesample



60 Heart Attacks

60 Heart Attacks






You act as if study begins here

PAST, 2008 PRESENT, 2014


Cohort Study Cohort Study To evaluate Treatment To evaluate Treatment

Hypothesis generating onlyHypothesis generating only

samplesample

1000on treatment

1000on treatment

60 Heart Attacks

60 Heart Attacks


Population of middle agepeople with high blood pressure

Population of middle agepeople with high blood pressure

1000not on treatment

1000not on treatment 20 Heart


Study begins here

PRESENT, 2014 FUTURE, 2014-18


Cohort Studies• Overview


• Bias

• Confounding



Case Control StudiesCase Control StudiesTo evaluate Etiology/Risk FactorsTo evaluate Etiology/Risk Factors

PAST PRESENT, 2014

1000Prior Heart

Attack

1000Prior Heart

Attack

1000No Prior Heart

Attack

1000No Prior Heart

Attack

60%High blood pressure




Study begins here


1000

Prior heart attack

1000

Prior heart attack

1000

No prior heart attack

1000

No prior heart attack

20%On Aspirin

20%On Aspirin

60%On Aspirin

60%On Aspirin

PAST PRESENT, 2014

Study begins here

Case Control StudiesCase Control StudiesTo evaluate Treatment EfficacyTo evaluate Treatment Efficacy


Cohort v. Case ControlCohort v. Case Control• Cohort (either prospective or retrospective)

– Subjects are defined by risk factor/treatment status

– Disease occurrence in the future is then assessed and compared

• Case Control – Subjects are defined by disease status– Past history of risk factor/treatment are then

assessed and compared


Cohort StudiesCohort Studies• Overview


• Bias

• Confounding



Bias and ConfoundingBias and Confounding

• Two problems that can undermine validity of cohort studies

• Bias– Systematic error in the design, conduct, or

analysis of a study

• Confounding– It looks like Factor A causes Disease X but in

fact it is Factor B


BiasBias

• There are a million types of bias!!

• Some common ones to look for…– Selection bias– Information bias


Selection Bias: exampleSelection Bias: exampleTo evaluate Etiology/Risk FactorsTo evaluate Etiology/Risk Factors

samplesample



60 Heart Attacks

60 Heart Attacks





• HBP recruited from a cardiology clinic• Normal BP from a primary care clinic• What’s wrong with this picture??


Selection BiasSelection Bias

• Systematic difference in prognostic or treatment factors between the 2 groups

• In our example….– One group is more likely to have more cardiac

risk factors or history than the other– One group is more likely to be aggressively

treated than the other (eg lipids)


Information BiasInformation BiasTo evaluate Etiology/Risk FactorsTo evaluate Etiology/Risk Factors

• Heart Attack incidence is measured from hospital records in one group and from patient recall in another

• What’s wrong with this picture??

samplesample



60 Heart Attacks

60 Heart Attacks






BiasBias

• Systematic error in the design, conduct, or analysis of a study

• The question to ask yourself when reading a study: Did they do things differently between the 2 groups?– Recruitment? Treatment? Follow-up?

Ascertainment of Endpoints? Analysis of Data?


ConfoundingConfounding

• This is the main problem in ALL observational studies

• Bias is under control of investigators– Did they do things differently between the

2 groups?

• Confounding is NOT under the control of the investigators– It is endemic to observational studies– But it can be mitigated


We do this cohort study…We do this cohort study…To evaluate Etiology/Risk FactorsTo evaluate Etiology/Risk Factors

• We have done a good job controlling for bias• We find a significant association between a

history of HBP and risk of heart attack• Is that the end of the story?

samplesample



60 Heart Attacks

60 Heart Attacks





P<0.001


We still don’t know if…We still don’t know if…

• Its the high BP that increases the risk of heart attack or something else (that frequently

accompanies HBP) that is actually the culprit

• In other words, is there “confounding”?


Before we can definitively say that high blood pressure is a risk factor for heart

attacks, we need to rule out confounding

Before we can definitively say that high blood pressure is a risk factor for heart

attacks, we need to rule out confounding

High Blood PressureHigh Blood Pressure

Heart AttacksHeart Attacks

Risk factor Risk factor

OutcomeOutcome

ConfoundingConfoundingin Risk Factor/Etiology Studiesin Risk Factor/Etiology Studies


Population: Middle Aged People in the US

No HBP HBP

20 heartattacks

60 heart attacks

sample


Population: Middle Aged People in the US

No HBP HBP

20 heartattacks

60 heart attacks

sample

SmokeDon’t Exercise

Have highcholesterol

Don’t SmokeExercise

Have normal cholesterol


Confoundingin Risk Factor/Etiology Studies

High Blood PressureHigh Blood Pressure


Risk factor Risk factor

OutcomeOutcome

HighCholesterol

HighCholesterol

Confounding VariableConfounding VariableA variable that is associated with both

the risk factor and the diseaseA variable that is associated with both

the risk factor and the disease


Confoundingin Treatment Studies

Treatment of High Blood Pressure

Treatment of High Blood Pressure



Population: Middle Aged People in the with HBP

HBP treated

HBP Not treated

20 heartattacks

60 heart attacks

sample


Population: Middle Aged People in the with HBP

HBP treated

HBP Not treated

20 heartattacks

60 heart attacks

sample

Don’t getother

interventions

Get other Interventions

e.g. aspirin


Confounding

• A problem in even the most meticulously conducted cohort study

• There are ways to mitigate its effects– Have all the likely confounders been

identified?– Have the authors used appropriate statistical

techniques for dealing with potential confounders?


Confounding

• But it can never be totally ruled out in an observational study (cohort, case-control)

• You can deal with the known confounders– “control for”, “adjust for” them

• But you can’t deal with the unknown, unmeasured ones


Confounding

• The only way to avoid confounding is to do a randomized trial– Randomization balances the known and

unknown risk factors evenly between the two groups

• Treatment decisions (especially for prevention) should be based on randomized trial data


Cohort Studies

• Overview


• Bias

• Confounding



Features of Good Cohort StudiesFeatures of Good Cohort Studies• Sample representative and assembled at a

common point in time• Follow-up sufficiently long and complete• Outcome criteria objective or applied in a blinded

fashion• Adjustment for possible confounding (prognostic

factors)• Results reported with time to event curves (if f/u

longer than a few months)• Precision of the effect size reported (CI)


Small Group ExerciseSmall Group Exercise

Glucose Levels and Risk of DementiaCrane et al NEJM 2013; 369(6):540-548

Start by reading the abstract …Then try to answer these questions

• What kind of study was this?• Was follow-up sufficiently long and complete?• Were the outcome criteria objective or applied in a blind fashion?• Was adjustment for prognostic factors (confounding) done?• Were outcomes reported over time (ie time to event analysis)?• How precise were the estimates of prognosis?• How would you apply the results of this study in your practice?

Cohort Studies Hanna E. Bloomfield, MD, MPH Professor of Medicine Associate Chief of Staff, Research...

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