April 6 -8, 2004

Cancer Clusters and Environmental QualityShanghai-California Environmental Health

Conference

Richard Kreutzer, M.D.California – China Environmental

Health Training Program

April 6 -8, 2004

Epidemiology is…

The study of the distribution and determinants of disease in human populations.

Characterizing disease as to person, place and time.

April 6 -8, 2004

“Cluster”

“An unusual aggregation of health events that are grouped together in time and space…”

CDC Guidelines for investigating clusters of Health Events, 1990

April 6 -8, 2004

Some Well-Known Cancer Clusters

Place Time Cancer Obs Exp O/E

Niles, ILL 1956-60 Child Leukemia 8 1.7 4.6

Sellafield, UK 1968-84 Child Leukemia 5 1.5 3.3

Woburn, MA 1969-79 Child Leukemia 12 5.3 2.3

McFarland, CA

1975-85 Child Cancer-several types

10 3.0 3.3

April 6 -8, 2004

Clusters

What are they-concept of randomness

5858 census tracts; 80 cancer sites=4686 clusters at 0.01 significance level

Why has DHS studied them

What is the success rate around the world

What has been the approach

The cluster investigation manual

What can be determined by looking at cluster cases

April 6 -8, 2004

Clusters in the United States Represent

• Fear of environment

• Distrust of government

• Frustration with lack of control over one’s surroundings

• Large degree of ignorance about disease

April 6 -8, 2004

Appendix A

There are 440 towns with less than 10,000 population in California, and about 5,000 census tracts with around 5,000 population each.

For diseases with an average expectation of five or more cases per time period of interest we can say the following:

In 100 such locations, the likelihood that a given disease (e.g. .lung cancer) is elevated enough to be statistically significant with a p value of .05 is 5%. So on the average, five out of 100 towns will show an elevation significant at the .05 level, while 95 towns will not.

What is the probability of a town escaping both lung cancer and bowel cancer clusters of p value of .05? The probability of -A and B is P(A) x P(B). So the answer is (.95) x'(.95) or .903.

The Probability of at least one statistically significant cluster in a census

tract home or town

Answer: (.95)80 = .0165

Answer: 1.00 minus the probability of no cluster, or 1.00 minus .0165 = .9835

What is the probability of a town escaping a cluster of each and every, one of the 80 major classifications of cancer?

What is the probability of at least one type of cancer cluster?

April 6 -8, 2004

So we can expect 8 out of 1,000 towns or census tracts to have at least one of 80 types of cancer elevated at the P = 1/10,000 level of significance. Since there are 5,440 localities in California, that means we can expect about 44 towns will have clusters of that extreme statistical significance.

About half the towns will have P = -.01- significant clusters.

The Probability of at least one statistically significant cluster in a census tract home or town (Cont.)

Probability of escaping Probability of at least one of P Value all 80 types of caner 80 cancers being elevated

.0l .447 .553

.0001 .992 .008

So there is a 98.4% probability that a town will have at least one type of cancer cluster at the p = .05 level.

Using your calculator you can verify the following figures:

April 6 -8, 2004

Comparison of Clusters

E.coli Cancer Cluster

Disease

Agent

Other Causes

Latency

Rare

Can be cultured from a case

Few

2-5 days

Common

Can’t be determined medically

Many

Years

April 6 -8, 2004

X X X

X X X

X X

X X X X

X X

X X X

X X X

X XX X

X X

X X

X X X X X

X X X XX

X X

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 6 7 8 9

Taylor & Wilde, “Drawing the line with Leukemia”

April 6 -8, 2004

Limitations of Science for Cluster Questions

Paradox’s of epidemiology

Large numbers –small confidence intervals (clusters disappear in average)

Small numbers-large confidence intervals (insufficient power)

Population vs. individual risk

Can look for known carcinogens

Rarely can identify new carcinogens

What should its role be in a democracy?

Science vs. pseudoscience

Citizen intuition vs. scientific certainty

April 6 -8, 2004

A BC D

Categories of Epidemiologic Studies

Disease No Disease

Total Exposed

Total Not Exposed

Richard Kreutzer, M.D.

Not Exposed

Exposed

Total with Disease

Total without Disease

April 6 -8, 2004

Chemicals in the Environment

Air

Water

Soil

Travel Through…….

Breathing

Eating

Touching

Get into body by…..

Figure 2. Toxicants as Causes of Disease: The General Model

Harmfulness of chemical

Amount of chemical

Length of exposure to chemical

HEALTH IMPACT

HOW CHEMICALS CAN AFFECT YOUR BODY

Chemical effects on your body depend on ……

April 6 -8, 2004

Determinants of Disease

Environmental

Behavioral

Lifestyle

Occupational

Other Diseases

Psychological

Genetic

Disease

April 6 -8, 2004

Measured Level Regulatory Action

EHIB Action

Below Regulatory number

Do nothing Provide public information about regulations and their scientific basis

Above regulatory number but below known toxicological threshold

Require compliance with regulation. Notify public

Provide public information on regulations and toxicology

Above toxicological threshold but below level of epidemiolgical detection

Require compliance with regulations. Notify public

Provide public information on regulations, toxicology and epidemiology

Above level of epidemiological detection

Require compliance with regulations. Notify public

Consider a health study*

Figure 4. Regulatory Agency and EHIB Action Regarding Toxicant Levels

*Must consider how study would be used and its feasibility. Should obtain community and individual informed consent.

April 6 -8, 2004

(A)

Dietary fat and colon cancer

(B)

DES and vaginal cancer

(C)

Chernobyl release and thyroid cancer

(D)

Vinyl chloride and hemangiosarcoma

Exposure

Common, widespread exposure

Rare, unique exposure

Type of Health OutcomeCommon Outcome Rare, Unusual

Outcome

How would different approaches to looking at clusters perform for these different situations?

1) Respond to inquires – Could pick up (B) and (D)

This approach could (and did) confirm the clusters of vaginal cancer and hemangiosarcoma

2) Actively search for clusters – Could pick up (B) and (D)

A cluster hunting team scanning registry data could probably have found these rare and unusual clusters, although perhaps later than Approach 1 because of the lag time for registration.

3) Study unusual exposures – Could pick up (C)

EHIB has mainly concentrated on being vigilant for new, unusual exposures and their possible consequences (e.g., aerial application of malathion).

Conclusions: The combination of Approaches 1 and 3

could pick up (B), (C), and (D).

None of these approaches would be a good way to detect (A).

Is there a compelling reason for Approach 2?

Approaches: