Transcript Lecture Slides

Zuo-Feng Zhang, MD, PhD
Epi242, 2009
Prospective:
 Cohort Studies: Observational studies
 Intervention Studies, Clinical Trials
 Nested Case-Control Studies
Cross-sectional Studies
Retrospective
 Case-Control Studies
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Discussion of a study design for a prospective
study in a near a nuclear plant
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General population cohort, the sampling
process should be depended on the
distance from the factory to their home,
e.g., 1km, 2km, etc.
Occupational cohort. This is the most
important cohort for radiation exposure. All
individuals in the factory should be included
in the occupational cohort.
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These cohorts should include all ages
because radiation may cause children's
leukemia and thyroid cancer
For occupational cohort, it would be better
that worker's family are also included
(workers may bring radiation exposure to
home)
For general population cohort should
include children of all ages.
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Occupational cohort should have personal
radiation monitor as well as site monitor
General population cohort sample site should
be corresponded to the site of radiation
monitoring
Setting-up air pollution monitoring if
possible.
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Estimate the power of your study
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IRB approval and Informed consent is
needed for this type of study
Interviewers' training is very important:
Close monitoring the quality of
questionnaire as well as the correspondent
biological specimen collection
try to avoid missing data
Use double entry to avoid mistakes in data
entry
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Setting up the follow-up durations (2 years or
4 years, etc.)
Decide what need to be collected in the
follow-up study (exposure status, end-point,
biological specimens, additional exposure
data.
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blood sample storage. At this point, -20
degree is a feasible way of the storage. It
would be better to have two tubes of blood,
EDTA and non-EDTA (or other chemicals).
Minimum 10 ml blood
Urine: Consider to collect urine and then to
get cells from urine and discard the fluid
part, if there is any problem of storage
Buccal sample. For these who do not want
to give blood, you should ask them to
donate buccal cell sample
Hair sample?
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The transportation of biological samples
need to be kept in low temperature, the
best way is the have dry ice. Otherwise, to
have blue ice for a short time.
The biological specimen be stored in two
separate sites, so that when there is
anything happened, we still have another
set of sample to use
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Setting-up internet based disease registry
and reporting system, including cancer,
chronic and infectious disease as disease
monitoring system which could be an
important follow-up system for end-points.
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Exposure is measured before the outcome
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The source population is defined
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The participation rate is high if specimen are
available for all subjects and follow-up is
complete
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The usually small number of cases of each
of many type of cancer
The lack of specimen if the biomarker
requires large amounts of specimen or
unusual specimens
Degradation of the biomarkers during longterm storage
The lack of details on other potentially
confounding or interacting exposures
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The major concern of cohort studies of the
short duration (as in case-control studies) is
the possibility that the disease process has
influenced the biomarker level among cases
diagnosed within 1 to 2 years of the
specimen being collected.
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In prospective studies in longer duration,
there may be considerable misclassification
of the etiologically relevant exposures if the
specimens have been collected only at
baseline.
This misclassification occurs when
individual’s exposure level may change
systematically over time and there may be
intra-individual variation in biomarker level.
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The intra-individual misclassification may
be reduced by taking multiple samples, but
this will generally increase expenses of
sample collection and storage and the
burden on study subjects
Similar approaches apply to taking sample
at several points in time in an attempt to
estimate time-integrated exposures or
exposure change.
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An alternative approach is to estimate the
extent of intra-individual variation, and the
misclassification involved in taking single
specimens, by taking multiple specimens in
a sample of the cohort.
This information can be used to correct for
bias to the null introduced if the
misclassification is non-differential, and
therefore de-attenuate observed relative
risks
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Repeated contact of subjects
Informing the cohort members of their
biomarker level is problematic if the
biomarker is not considered to be sufficiently
predictive of disease and if there is no
preventive steps cohort members can take to
reduce their risk of the disease
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The biomarker can be measured in specimens
matched on storage duration
The case-control set can be analyzed in the
same laboratory batch, reducing the potential
for bias introduced by sample degradation
and laboratory drift
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In studies of smoking cessation
intervention, we can measure either serum
cotinine or protein or DNA adducts
(exposure) or p53 mutation, dysplasia and
cell proliferation (intermediate markers for
disease)
Measure compliance with the intervention
such as assaying serum b-carotene in a
randomized trial of b-carotene.
Susceptibility markers (GSTM1) can also be
used to determine whether the randomization
is successful (comparable intervention and
control arms)
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For genetic susceptibility markers, casecontrol study design is highly appropriate
Clinic-based case-control studies are
particularly suitable for studies of
intermediate endpoints, as these end-point
can be systematically measured.
Clinic-based case-control studies are
excellent for studying etiology of
precancerous lesions (e.g., CIN)
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Biomarkers of internal dose (e.g., carrier
status for infectious agents, such as HBsAg)
or effective dose (PAH DNA adducts) are
appropriate when they are stable over a long
period of time or when the exposures have
been constant over exposure period.
However, it is essential that you are not
affected by the disease process, diagnosis, or
treatment.
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1. Hypothesis:
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Environmental Tobacco Smoking and other
Environmental exposures may be associated
with lung cancer among non-smoking
women.
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Women have less tobacco smokers and prevalence
of male smoking is relatively high
Women’s lung cancer is different from men’s lung
cancer.
High proportion of female lung cancer is
adenocarcinoma of the lung
The RR for women’s lung cancer is higher than
male lung cancer, which indicates that women may
be susceptible to low dose tobacco smoking
exposure
ETS have very similar carcinogens as active tobacco
smoking, but ETS may have some carcinogens with
high concentration.
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A population-based case-control study
(population-based versus hospital-base
case-control studies)
Inclusion (women, non-smokers. Definition of
non-smokers: lifetime cigarette smoking of
less than 100 cigarettes)
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There are several ways of controlling for potential
confounding factors. In the designing stage, we can
design a study which can control for potential
confounding effects, including: (1) randomization
(assigned subjects into treatment and control
groups; (2) matching; (3) exclusion/inclusion. In
the data analysis phase, we can use (4) stratified
analysis such as M-H methods and (5) multivariate
analysis such as proportional hazards model and
logistic regression model to control for potential
confounding effects.
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Age: 35-75
Gender: female
All new cases if possible (not a random
sample of new cases)
Newly diagnosed or incident cases (not
prevalent cases, why?)
Pathological diagnosis of lung cancer
In a stable mental and physical status
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Controls should be selected from the
population where the cases from and be a
representative sample of the source
population.
Matching variables: (age, gender, race. the
residence should not be matched for this
hypotheses, why?)
Frequency versus individual matching
Random sample of the general population
(stratified sampling by matching variables)
Random digital dialing, DMV registration,
etc.
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ETS exposures: exposure as child at home,
exposure from spouse and other family
members, and exposure from co-workers at
working environment
Other potential confounding factors: Other
indoor air-pollution, cooking oil fume, coal
smoke, etc. occupation history and
exposure, family history of cancer, alcohol
drinking, etc.
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Blood samples, urine samples, tissue
specimens
ETS measurements (urine or blood levels of
cotinine, hemoglobin protein adducts,
PM2.5, etc.)
DNA adducts at lung tissue (only for cases
with surgery)
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Sample size:
Case-control ratio
Alpha level (0.05)
Beta level (0.20 or power 0.80)
OR=1.5
Consideration of interactions and
confounding effects
Data analysis: M-H methods, Logistic
Regression Models.
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Relating a particular disease (or marker of
early effect); to a particular exposure; while
minimizing bias; controlling for confounding;
assessing and minimizing random error; and
assessing interactions