7/2/2015Ch 7: Cohort Studies11 Chapter 7: Observational Cohort Studies.
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04/19/23 Ch 7: Cohort Studies 11
Chapter 7: Observational Cohort Studies
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Ch 7 Outline
7.1 Introduction 7.2 Historical perspective7.3 Assembling and following a cohort 7.4 Prospective, retrospective, and ambidirectional
7.5 Addressing the potential for confounding 7.6 Data analysis 7.7 Wade Hampton Frost (optional)
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Basic Cohort Design
Closed populatio
n
Incidence1
Incidence0
RR or RD
•Recruit study subjects•Classify individual as exposed or non-exposed•Follow individuals over time, ascertain outcomes•Compare incidences of study outcomes
Exposedindividuals
non-exposedindividuals
RR or RD
RR or RD
RR or RD
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Do not lose sight of Do not lose sight of individual experiences individual experiences from the beginning to from the beginning to the end (William Farr) the end (William Farr)
Historical Perspective• From the Latin cohors
– “an enclosure” – a unit of the Roman army
• Historical notes• Ramazzini studied worker health
(1713)• Louis studied clinical outcomes in
patients (18th century)• Pinel studied mental health
outcomes associated with humane treatment (18th century)
• Doll & Hill studied British doctors and smokers (1951 - present)
• Americans studied the causes of heart disease in Framingham Massachusetts
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British Doctors Study Survival Curves
Source: Doll, R., Peto, R., Wheatley, K., Gray, R., & Sutherland, I. (1994). Mortality in relation to smoking: 40 years' observations on male British doctors. British Medical Journal, 309(6959), 901-911.
Begun in 1951 by Doll and Hill with a mailing of a 6 question Begun in 1951 by Doll and Hill with a mailing of a 6 question questionnaire sent to 59,600 individual addresses. questionnaire sent to 59,600 individual addresses.
80% of nonsmoker survived to age 70
50% heavy smokers survived to 70
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WHI Observational Cohort
• WHI project included both experimental and observational cohorts
• Observational study: 93,676 women, 50-79 @ 40 clinical centers
• Recruitment period 1993 - 1998
• Up to 15 years of follow-up
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WHI Observational CohortBreast CA & Analgesic Use
Group DurationOf use
nBreastCA cases
PYsInc. Rateper 1000
P-value trend
Referent < 1 yr 54,102 955 194,884 49.0 N/A
NSAIDs 1–4 yr≥5 yr
9,000 10,162
148 83
32,127 36,576
46.4 40.5
0.01
Aspirin 1–4 yr≥5 yr
5,124 6,759
149 99
18,231 24,398
45.5 40.6
0.03
Acetamin. 1–4 yr≥5 yr
2,4504,675
44 79
8,608 16,698
51.1 47.3
0.71
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Prospective, Retrospective, Ambidirectional
• Based on proximityproximity of data collection to actual events• ProspectiveProspective = data collected near time of event• RetrospectiveRetrospective = data are from the past (“historical data”)• AmbidirectionalAmbidirectional - combination of prospective and
retrospective data
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WHI analgesic / breast cancer study Proximity of Data Collection
Analgesic use history Breast cancer occurrence
Initial data collection
The ascertainment of the exposure was retrospective.
The ascertainment of the outcome (breast cancer) was prospective.
Overall, the study was ambi-directional.
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Example 7.4 (Retrospective Cohort) Chemical workers and bladder cancer
• Exposure to benzidine, β-naphthylamine, alpha-naphthylamine • Historical cohort: occupational records of 4622 men in the British
chemical industry, 1900 to 1950 • Bladder cancer info from death certificates 1921 – 1950• Data collection: 1952• Retrospective (“historical”) cohort study
Initial data collection
Chemical Exposures Bladder tumors
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Multiple levels of exposure Analgesics and Breast cancer
Group DurationOf use
nBreastCA cases
PYsRate per 1000
P-value trend
Referent < 1 yr 54,102 955 194,884 4.90 N/A
NSAIDs 1–4 yr≥5 yr
9,000 10,162
148 83
32,127 36,576
4.64 4.5
0.01
• Let R0 ≡ rate per 1000 p-yrs in referent group• Let R1 ≡ rate per 1000 p-yrs in NSAID users of 1-4 years• Let R2 ≡ rate per 1000 p-yrs in NSAID users of 5+ years• RR1 = R1 / R0 = 46.4 / 49.0 = 0.95 [no units]• RR2 = R2 / R0 = 40.5 / 49.0 = 0.83 [no units]• RD1 = R1 − R0 = 46.4 − 49.0 = −2.6 per 1000 p-yrs• RD2 = R2 − R0 = 40.5 − 49.0 = −8.5 per 1000 p-yrs
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04/19/23 Ch 7: Cohort Studies
OpenEpi.com for data analysis
• “Counts” menu for incidence proportions, prevalences, and case-control data
• “Person Time” menu for rate data
• Descriptive and inferentialinferential (confidence intervalsconfidence intervals and PP-values-values) statistics
• Can be used as a learning tool
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