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Section Contents
 
Education Scenario
Examples of Clusters
 
Case Contents
 
Cover Page
Goals and Objectives
Case Study, Pretest
Definition of Clusters
Evaluating a Cluster
Case Definition
Case Confirmation
Population Denominator
Review the Literature
Exposure Assessment
Plausible Hypotheses
Web Resources
Suggested Reading
Answers
Exposure History Form
 
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Exposure Pathways
GATHER (GIS)
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Interactive Learning
Managing Incidents
Medical Guidelines
Minimal Risk Levels
Priority List
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Toxicological Profiles
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Agency for Toxic Substances and Disease Registry 
Case Studies in Environmental Medicine (CSEM) 

Disease Clusters: An Overview
Risk Communication


Sample Patient Education Scenario

Doctor: Your mammogram illustrates two abnormal areas that I would like to explore further by performing a biopsy. The biopsy will show whether the tissue is malignant or benign.

Patient: Four teachers at my school have been diagnosed with breast cancer in the past 4 years that the school has been open.

Doctor: Ms. Jones, cancer develops over a long period of time-decades-and it is important to know the family history. A percentage of cancer cases are inherited and recent research has identified changes (mutations) in two genes that greatly increase the risk for breast cancer.

Patient: So are you saying it is unlikely that the school is the cause of my cancer?

Doctor: First, I am not diagnosing you with cancer at this time. You have two abnormal areas that need to be biopsied so that we can determine whether the tissue is cancerous or not.

Patient: What about the school?

Doctor: It is highly unlikely that the school would be the cause because the school has only been open for 4 years. The latency period for cancer can be decades.

Patient: I understand. When do you want to schedule the biopsy?

The most important points to discuss during patient education are

  • The current problem and the next appropriate diagnostic step.
  • Specific factors related to the occurrence of the particular disease (e.g., latency period for cancer, significance of family history, and other confounding factors).
  • Whether it is likely or unlikely that the patient's perceived exposure might be responsible for the problem: If it is likely, discuss your role and responsibility.

Following are specific clinical points based on the case study scenarios.

In case scenario 1, the possibility would be unlikely that the breast cancer was caused by exposures in the school, which has only been open for 4 years. Successful cluster investigations most often involve a high occurrence of uncommon diseases.

In case scenario 2, the possibility would be unlikely that the miscarriages are caused by the neighborhood. Spontaneous abortion occurs in 10%-14% of pregnancies in women. Statistically, it would be expected that spontaneous abortion would occur in 10-14 of 100 women. Recurrent spontaneous abortions (defined as the loss of three or more consecutive pregnancies) occur in about 3%-4% of these women. Most spontaneous abortions occur because of abnormalities in the fetus (Matorras et al. 1998).

In case scenario 3, the possibility would be unlikely that the cancers are directly related to living in the neighborhood. The latency period for cancer can be decades. Additionally, several confounding factors including smoking, family history of cancer (particularly breast cancer), and potential workplace exposures must be explored in the medical history, family history, and exposure history before attempting to consider that the cancer rates in this neighborhood are related to a neighborhood exposure.

Most cluster associations result from coincidence and chance, but that does not mean that clusters are not useful sources of information. Numerous instances exist where reports of a disease cluster led to recognition of a new disease-causing agent or environment. Some examples from the occupational medicine literature include the associations of vinyl chloride monomer with angiosarcoma of the liver, dibromochloropropane with male infertility, and bis-chloromethyl ether with small-cell lung cancer in young men. Table 2 shows a list of other examples, such as human disease caused by toxicants, organisms, and dusts.

Clusters provide opportunities and impetus for developing new hypotheses about previously unsuspected exposure-outcome relationships. Some of these new hypotheses lead to better understanding of disease causation. Disease clusters help us to identify previously unrecognized hazards.

Table 2. Examples* of Community Clusters Leading to the Identification of New Exposure-Disease Relationships

Population Year Exposure Outcomes
Rural dwellers 1928 Castor bean dust Asthma
Harbor dwellers 1989 Soybean dust Asthma
Children and adults 1979, 1989 Polychlorinated biphenyls Developmental, central nervous system, lipid disorders
Homosexual males 1981 Human immunodeficiency virus (HIV) Pneumocystis carinii opportunistic infection
Drug users symptoms 1983 N-methyl-4-phenyl-1,2,5,6- tetrahydropyridine Parkinson-like
Health food consumers 1989 L-tryptophan (contaminated) Eosinophilia-myalgia
Fish handlers and estuarine visitors 1995 Pfiesteria piscicida Memory disturbance
Dieters 1997 Fenfluramine-Phentermine Valvular heart disease
*More examples of clusters, and many more of sentinel events, are available.

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Revised 2000-08-30.