Zuo-Feng Zhang, MD, PhDEpi242, 2009

Prospective: Cohort Studies: Observational studies Intervention Studies, Clinical Trials Nested Case-Control Studies

Cross-sectional Studies

Retrospective Case-Control Studies

Discussion of a study design for a prospective study in a near a nuclear plant

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.

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.

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.

Estimate the power of your study

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

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.

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?

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

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.

Exposure is measured before the outcome

The source population is defined

The participation rate is high if specimen are available for all subjects and follow-up is complete

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 long-term storage

The lack of details on other potentially confounding or interacting exposures

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.

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.

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.

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

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

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

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 -carotene in a randomized trial of -carotene.

Susceptibility markers (GSTM1) can also be used to determine whether the randomization is successful (comparable intervention and control arms)

For genetic susceptibility markers, case-control 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)

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.

1. Hypothesis:   Environmental Tobacco Smoking and other

Environmental exposures may be associated with lung cancer among non-smoking women. 

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.

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)

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.

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

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.

  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.

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)

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.

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