Prospective Cohort Studies
Frederick L. Brancati, MD, MHS
Professor of Medicine & Epidemiology
Director, Division of General Internal Medicine
Osler Journal Club 2006
Visit Hopkins GIM at http://www.hopkinsmedicine.org/gim
Background
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Physical activity  lower CVD risk
DHHS recommends life-long pursuits
Sports differ in sustainability
CVD benefits of individual sports uncertain
The Johns Hopkins Precursors Study
Over 1300 students (mainly white men) from the JHUSOM Classes of
1948-64. Baseline data collected in person in medical school. Followup data collected by yearly mailed questionnaires thereafter.
Caroline Thomas, MD
The Johns Hopkins
Precursors Study
Outline
• Hypothesis: Tennis ability in youth predicts
lower CVD risk in middle age
• Design: Prospective cohort study
• Setting: Johns Hopkins Precursors Study
• Participants: 1019 male medical students
• Data Collection: Extensive interview and
physical assessment at baseline (early 20s);
annual mailed follow-up questionnaires
• Outcome: Incident CVD, including MI, CHD,
CABG or PTCA, hypertensive heart disease,
heart failure, & cerebrovascular disease
• Analysis: Kaplan-Meier, Cox models
Assessment of Sports Ability
• How would you rate your overall ability in
tennis (golf, football, baseball, basketball)
during and before medical school?
– No ability
– Poor or fair ability
– Good or excellent ability
• No data on frequency, intensity, or
subsequent participation
Results
Conclusions / Implications
• Self-described tennis ability in young
adulthood predicts lower CVD risk in
middle age
• Association of tennis to lower risk is
– Graded (i.e. dose-response)
– Independent of many possible confounders
– Specific to tennis (as hypothesized)
• Suggests promotion of tennis as a means
to reduce CVD risk
Strengths
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Prospective design
Long-term follow-up
Multiavariate analysis
Blinded assessment of CVD
Weaknesses
• Observational studies can’t prove causality
• Residual confounding is likely
• Assessment of exposure was suboptimal
– Ability, not activity
– Single point, not repeated measures
– Self-assessed, not objective
• Sample limits generalizability
Discussion Points
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What’s special about a cohort study?
What are common obstacles?
Can it be used for housestaff research?
Can it ever be sufficient to change
practice?
• How do cohort studies relate to outcomes
research?
Taxonomy of Designs
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Randomized Controlled Trial
Prospective Cohort Study
Case-Control Study
Cross-Sectional Study
Other Designs
– Quasi-Experimental
– Ecologic
– Case Report
The basic fighting unit was a cohort, composed of six centuries (480 men
plus 6 centurions). The legion itself was composed of ten cohorts, and the
first cohort had many extra men—the clerks, engineers, and other
specialists who did not usually fight—and the senior centurion of the legion,
the primipilus, or “number one javelin.”
pro·spec·tive
Pronunciation: pr&-'spek-tiv also 'prä-", prO-',
prä-'
Function: adjective
Date: circa 1699
1 : relating to or effective in the future
2 a : likely to come about : EXPECTED <the
prospective benefits of this law> b : likely to be
or become <a prospective mother>
“Prospective” in Epidemiology
• Clearly defined cohort (group, sample) of
persons at risk followed through time
• Data regarding exposures (risk factors,
predictors) collected prior to data on
outcomes (endpoints)
• Research-grade data collection methods
used for purpose of testing hypothesis (?)
Diagram of Hypothetical 6-Year Cohort Study to
Identify Risk Factors for Facial Acne in Teenagers
1000
12-year-olds without acne
5 moved
50 with Acne
10 no answer
35 refused
900
15-year-olds without acne
10 moved
300 with Acne
40 no answer
48 refused
500
18-year-olds without acne
2 deaths
6-yr Follow-up Rate = 850/1000 = 85%
Incidence Rate of Acne = 350/5475 PY = 63.9 per 1000 PY
350 incident
cases of acne
over 6 years
Why Do A Cohort Study?
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Get incidence data
Study a range of possible risk factors
Establish temporal sequence
Get representative data
Prepare for randomized controlled trial
Establish a research empire
Types of Cohorts
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Occupational (e.g. Asbestos workers)
Convenience (e.g. Precursors, Nurses)
Geographic (e.g. Framingham, ARIC)
Disease or Procedure
– Natural History (e.g. Syncope, Lupus)
– Outcomes Research (e.g. Dialysis, Cataracts)
Sources of Cohort Data
• Clinic Visits
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Laboratory Assays
Interview
Physical Examination
Imaging
Physiologic tests
• Home visits
• Mailed materials
• Telephone Interview
• Medical Records
• Administrative Data
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Medicare
Medicaid
Managed Care
Veterans Admin
• Birth Records
• Death Certificates
• Specimen Bank
The Framingham
Heart Study
William Castelli, MD
Recently Published Studies from the
Johns Hopkins Precursors Study
Outcome
• Coronary Disease
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Type 2 Diabetes
Hypertension
Knee Osteoarthritis
Depression
Exposure
-Anger, Depression, Gout,
-Sports Ability
-Blood pressure, Adiposity
-Coffee
-Knee injury
-Insomnia
What Might Explain Observed
Relationship of Tennis Ability to
Heart Disease Risk?
• Tennis protects against heart disease
• Men who like to play tennis are different
– Thinner
– Healthier Lifestyles
– Higher Socioeconomic Status
• Men who play tennis well are different
– Taller, Thinner
– Greater Cardiovascular Fitness
• Chance (type I error) – Needs confirmation
Hypothetical
Causal Pathway
Potential
Confounders
Healthier Men Choose Tennis
Plays Tennis
Healthier Men Play Tennis Well
Plays Tennis Well
Sustained Activity Thru Midlife
Lower adiposity, Greater Fitness
Lower BP, Lower LDL, Higher HDL
Lower Risk of CHD
Hypothetical
Causal Pathway
Grey Hair
Higher Risk
of CHD
Potential
Confounders
Older Age
Challenges in Cohort Studies
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Possibly long duration
Possibly large sample size
Need to recruit people “at risk”
Drop outs, Deaths, Other losses
Concern about residual confounding
Multiple comparisons  Type I error
How to Exploit Cohort Design When
Time is Short & Money is Scarce
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Analyze existing data from another study
Piggy-back onto on-going study
Choose hospital-based cohort
Choose short-term outcome
Consider administrative data
Consider public-use data
Consider non-concurrent design