Evaluating environmental/occupational clusters of disease

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Evaluating environmental/occupational clusters
of disease

• Robert J. McCunney, MD

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Investigating Clusters of Disease

• Definition "cluster" is an unusual aggregation,
  real or perceived, of health events that are
  grouped together in time and space
• A cluster may be useful for generating hypotheses
  but is not likely to be useful for testing
  hypotheses

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Disease Clusters

• Focus usually on increased rate or risk of
  disease
• Breast cancer and pesticides
• Leukemia and contaminated water
• Increased risk of lung cancer from hexavalent
  chromium

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Cancer Cluster Activities at the CDCP

• Cancer cluster investigations occasionally have
  led to the discovery of important pathways in the
  etiology of specific cancers, such as with
• angiosarcoma
• lung cancer
• Kaposi sarcoma
• vaginal clear-cell carcinoma
• bladder cancer
• scrotal cancer
• NOTE The majority of studies that yielded
  etiologic information were of occupational,
  drug-induced, or infectious pathogenic exposure
  rather than studies of environmental exposure

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Media survey of cancer cluster reports

• For the period 1977 through 2001, media reports
  of 1,440 records of approximately 175 suspected
  cancer cluster reports
• These data reflect the breadth of popular concern
  and awareness regarding issues of exposure types,
  pollution sites, and specific environmental
  chemicals.

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Clusters case study

• 7 cases of kidney cancer at a manufacturing plant
• Is there a cluster?

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Criteria to determine whether to proceed to
investigate a cluster

• identification of a single cancer type
• biological plausibility
• adequate latency
• political pressure
• identification of a common cancer in an unusual
  age group
• identification of a rare cancer
• identification of exposure to a carcinogenic
  substance
• elevated ratio of observed/expected confirmed
  cancer cases

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Guidelines for Investigating Clusters of Health
Events

• CDC

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GUIDELINES FOR A SYSTEMATIC APPROACH

• The issue of increased frequency of occurrence
  should be separated from the issue of potential
  etiologies
• Stage 1. Collect information.
• A variety of diagnoses speaks against a common
  origin

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Stage 2. Assessment

• Separate two concurrent issues
• 1. whether an excess has occurred and
• 2. whether the excess can be linked etiologically
  to some exposure

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Stage 3. Feasibility Study

• Conduct detailed literature search with
  particular attention to known and putative causes
  of the health effect of concern.
• Consider an appropriate study design
• Determine what data should be collected on cases
  and controls, including laboratory measurements.
  Determine the nature, extent, and frequency of
  methods used for environmental measurements.
• Determine hypotheses to be tested and power to
  detect differences

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Stage 4. Etiologic Investigation

• Purpose Perform an etiologic investigation of a
  potential disease- exposure relationship.
• Types of studies
• Retrospective cohort mortality-most common
• Case/control-good for rare diseases
• Cross sectional-good for morbidity assessments

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Cluster Investigations

• A number of problems are encountered in the study
  of clusters.
• The health events being investigated (often
  morbidity or mortality) are usually rare, and
  increases of these events tend to be small and
  may occur over a long period.
• A major complication is that most clusters are
  chance events

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CDC

• a) provides a centralized, coordinated response
  system for cancer cluster inquiries,
• b) supports an electronic cancer cluster list
  server,
• c) maintains an informative web page, and
• d) provides support to states, ranging from
  laboratory analysis to epidemiologic assistance
  and expertise

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Occupational/Environmental epidemiology

• Goal Evaluate exposure- disease relationships
• Strengths risks in humans no need to
  extrapolate from animal studies
• Evaluate consequences of exposure in which it
  actually occurs

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Occupational epidemiology

• Limitations
• Low level risks difficult to identify
• Small increases in risk may be affected by bias,
  confounding and chance
• Long latency with cancer
• Inadequate exposure categorization

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Measures of effect

• RATES are the central metric used to assess
  disease occurrence in occupational cohort studies
• Comparison of a study group to a reference group-
  usually done by assessing the ratio of their
  respective standardized rates
• one frequently used outcome measure is the
  Standardized Mortality Ratio (SMR)
• SMR ratio of the sum of the observed events in
  the study group to the sum of the expected
  numbers in the study group expected numbers are
  based on standardized rates in the reference
  group

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Example of use of Standardized Mortality Ratio
(SMR)

• Null hypothesis (H0) no effect of exposure
• SMR for lung cancer of 1.8
• 80 excess compared to reference population
• Plt.05 95 Confidence Intervals (1.2-2.3)
  thus, statistically significant
• ? Role of confounding and bias

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Interpreting SMR results

• Chance P values plt.05 and 95 confidence
  intervals (reflect uncertainty to random
  error-not confounding
• Bias selection, recall
• Confounding (understates the uncertainty about a
  true effect smoking and lung cancer (biases
  SMR upward) alcohol and liver disease, diabetes
  and neuropathy

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Occupational epidemiology

• Reference population of paramount importance-
  ideally should match study group in all important
  demographics characteristics aside from
  exposure of interest
• Type of reference populations General (national,
  state, county) population disease rates
  categorized by age, gender, race, geographical
  area, calendar time
• Key point reference and study populations should
  be identical as much as possible aside from the
  exposure of interest

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Reference population

• Lung cancer and carbon black German study
• SMR 2.2 (national rates)
• SMR 1.8 (local rates)

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PRINCIPLES IN EVALUATING WHETHER A DISEASE IS
ENVIRONMENTALLY RELATED

• Strength of association
• Consistency of results does the association hold
  in different settings and among different study
  groups?
• Specificity How closely are the exposure factors
  and health outcome associated?
• Temporality Does exposure precede disease
  outcome. Is latency involved?
• From Hill AB. The environment and disease
  association or causation? Proc R Soc Med 1965
  58 295-300

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PRINCIPLES IN EVALUATING WHETHER A DISEASE IS
WORK RELATED

• Biological gradient does a dose- response
  relationship exist?
• Plausibility Does the association make sense
  biologically?
• Coherence Is the association consistent with the
  natural history and biology of the disease?
• Experimental Evidence Does experimental evidence
  support the hypothesis of an association?
• Analogy Are there other examples with similar
  risk factors and outcome?

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Interpreting occupational epidemiological
literature

• Study design- is the hypothesis clearly defined?
• Methods are they adequate to evaluate the
  hypothesis?
• How was exposure assessed?
• How was the cohort defined? Is there adequate
  ascertainment of vital status?
• What is the reference population? Is it an
  appropriate comparison group for the cohort being
  studied?
• Results
• What statistical methods were used?
• How was chance assessed?
• How was confounding controlled?
• How were potential biases addressed in the
  analysis, such as selection bias and confounding?

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Interpreting occupational epidemiological
literature

• Discussion
• Have the authors contrasted their results with
  previous scientific literature?
• Have the authors discussed the limitations of
  their study?
• What further work can be done to more fully
  define the results?
• Conclusion
• Have the authors properly assessed the results
  based on their own analysis ands limitations in
  light of previous literature?

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Renal cell carcinoma
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Renal cell carcinoma

• Incidence increased diagnostic accuracy CT,
  ultrasound, MRI
• Obesity, hypertension, smoking established risk
  factors
• Occupational ? TCE, solvents

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Plant

• 1200 employees
• Produces plastics, TDI, benzene, phosgene
• Built in 1950s
• Product manufacturing and research

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Is there an excess ?

• Expected rate of renal cancer 12/100,000
• Preliminary analysis
• From 1990-2006 1200 employees for 16 years
  20,000 person years 7 observed
• 35 observed over 100,000 person years
• 12 expected
• Thus 3 fold excess???

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Disease clusters and students

• Be critical of media reports
• Systematic approach to evaluations
• Recognize role of health departments
• Most clusters are statistical artifacts
• Interpret epidemiology studies cautiously
• Be attentive to possible new links between
  exposure and disease ) eg. nanoparticles, new
  materials etc

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Discussion

• Next step?