EPIDEMIOLOGY AND ITS CONTRIBUTION TO MEDICAL...

EPIDEMIOLOGY

AND ITS CONTRIBUTION

TO MEDICAL RESEARCH

(selected slides)

Jan E. Zejda

Department of Epidemiology, Medical University of Silesia

TOPICS

Roots of modern epidemiology

Epidemiology among health sciences

Definition of epidemiology

Epidemiological paradigms

Application of epidemiology in medical research

Clinical epidemiology

CHOLERA IN EUROPE

1829 in Orenburg (Russia)

1830 in Moscow (Russia)

1831

↓

Poland, Hungary, Austria, Prussia

1832

↓

England, France, Scandinavia,

Spain …

CHOLERA IN EUROPE

Second Wave of Epidemia

1848 in England: 53000 †††

Dr WILLIAM FARR

1807 – 1883

Physician

Founder of Medical Statistics

(measurement of health events:

birth, mortality, etc.)

CHOLERA CARRIED BY AIR POLLUTED BY MIASMA

(miasma = rotting organic matter)

Farr’s hypothesis („miasma theory”)

Deaths due to cholera versus elevation of the residence place in London

0

20

40

60

80

100

120

140

<20 20-40 40-60 60-80 80-100 100-120 340-360

Stopy nad poziomem morza

Zg

on

y/1

0000

Źródło: Gordis L.: Epidemiology. W.B. Sounders Company, Philadelphia 1996)

Feet above sea level

Deaths

MIASMA THEORY

(miasma in Greek = pollution)

340-360 100-120 80-100 60-80 40-60 20-40 <20

Stopy nad poziomem morza

...

Thickness of miasma layer

Feet above sea level

DR JOHN SNOW

1813 – 1858

One of the first physicians to test the

use of ether and chloroform

as anaesthetics.

Designer of devices to safely

administer ether and chloroform.

C2H5OC2H5

CHCl3

↓

Kidney

Liver

Heart

JOHN SNOW (1813-1858) on causes of cholera epidemics in London

Snow’s statistical argument

regarding water-borne disease

Mortality distribution according to the place of residence / source of drinking water

Water Supply Company Number of

houses

Number of

deaths

Deaths rate

(n/10000 houses)

Southwark&Vauxhall 40 046 1263 315

Lambeth 26 107 98 37

Source: Fox J.P. et al.: Epidemiology. Man and Disease. The Macmillan Company, London 1970)


SNOW’S DISTINCT METHODS

• Symptoms of acute intestinal infection (medical

background)

• Location (plotting the cases)

• Measurement of mortality rates (comparisons)

observation → hypothesis → measurement

knowledge → action

IMPORTANT MESSAGE

Cholera put under control long before

the causative agent was discovered

response

• 1848 - Establishment of General Health Department

(London)

• 1851 - International Health Conference (Paris)

• 1875 - Public Health Act (Great Britain): water supply,

sewage transportation, etc.

• 1907 - Establishment of International Health Organization

(Paris)

ROBERT KOCH (1843 – 1910)

[Vibrio cholerae – 1884]

Koch – 1884 !

FILIPPO PACINI (1812 – 1883)

[Vibrio Cholerae – 1854]

EPIDEMIOLOGY TODAY (from infectious to non-infectious diseases)

Ch. Niezakaźne

Ch. Zakaźne

√ ADVANCES IN MEDICINE

√ DEMOGRAPHY

√ QUALITY OF LIFE …

↑ YESTERDAY TODAY

↑

Non-infectious diseases

Infectious diseases

TOPICS







HEALTH SCIENCES

RESEARCH FIELD PRIMARY FOCUS

Health

Services

Epidemiology

Clinical Sciences

Biologic Sciences

Health care systems

Populations

Individual patients

Animal models, cells &

transmitters, molecules, genes,

drugs development

Source: Fletcher R.W., Fletcher S.W.: Clinical Epidemiology. The essentials .Lippincott Williams & Wilkins 2005

HEALTH SCIENCES

RESEARCH FIELD PRIMARY FOCUS

Health

Services

Epidemiology

Clinical Sciences

Biologic Sciences

Health care systems

Populations

Individual patients

Human & animal models, cells &

transmitters, molecules, genes,

drugs development


TOPICS







The study of the distribution

and determinants of health related states

or events in specified populations,

and the application of this study

to control of health problems

(Last, 2001)

!

DEFINITION OF EPIDEMIOLOGY

EPIDEMIOLOGY The study of the distribution and determinants of health

related states or events in specified populations, and the

application of this study to control of health problems

STUDY

surveillance, observation, hypothesis

testing, analytic research,

and experiments.




DISTRIBUTION analysis by person, place and time

„who” – „where” – „when”

?




DETERMINANTS (function)

risk factors, protective factors,

modyfying factors …

HOST

FACTORS

SOCIO-

ECONOMIC

FACTORS

ENVIRON-

MENTAL

FACTORS

LIFE STYLE

FACTORS

OTHER

FACTORS

- Genes

- Gender

- Age

- Poverty

- Employment

- Isolation

- Air quality

- Water

quality

- Occupational

environment

- Home

environment

- Social

environment

- Nutrition

- Physical

activity

- Tobacco

- Alcohol

- Drugs

- Sexual

activity

-Education

-- Health care

system

- Transport.

- Recreation

DETERMINANTS (source)




HEALTH RELATED STATES OR EVENTS

diseases, causes of death, behavior,

reactions to preventive regimens,

provision and use of health services …

HEALTH-RELATED PHENOMENA




APPLICATION TO CONTROL to assess the public health importance of

diseases, identify the population at risk,

identify the causes of disease, describe the

natural history of disease, and evaluate the

prevention and control of disease




APPLICATION TO CONTROL

health promotion

preventive measures

diagnostic standards

therapeutic standards

EPIDEMIOLOGY versus CLINICAL MEDICINE

PRINCIPAL TASKS

CLINICAL MEDICINE EPIDEMIOLOGY

Diagnosis Epidemiological study

Treatment Prevention, health

promotion

Prognosis Risk assessment

EPIDEMIOLOGY

FROM KNOWLEDGE

Descriptive epidemiology (what, who, where ..?)

Analytical epidemiology (why ?)

TO APPLICATION

Prevention

New diagnostic / therapeutic procedures

Refined provision of health services

…

TOPICS







EPIDEMIOLOGIC PARADIGMS

Non-random occurrence of diseases

Between-subject variability in health and

exposures* leading to co-variability • - a very broad concept (smoking=exposure; gene variant=exposure; etc..)

& Reliability of the results

DISEASES DO NOT OCCUR BY RANDOM

WHY ME ?

NON-RANDOM OCCURRENCE IMPLIES CAUSATION

EXPOSURE TO WHAT ? (HARMFUL AGENTS ? POOR GENES ? … ?)

?

?

?

?

(1) Between-subject variability in health status

(2) Between-subject variability in potential risk factors

(1) follows (2) = covariability

Q: IS KNOWN HEALTH DISORDER

RELATED TO KNOWN EXPOSURE ?

A: COVARIABILITY – Y/N

Reliable Measurement of Health and Exposure

Evidence of Covariability

SIR DAVID ROXBEE COX

FOUR CHALLENGES:

MEASUREMENT

STUDY DESIGN

DATA ANALYSIS

INTERPRETATION

David R. Cox: Some challenges for medical statistics (symposium „Modern Statistical Methods

in Medical Research” - Nobel Foundation Series „Frontiers in Medicine”

< European Journal of Epidemiology 2005;30:5-9 >

http://en.wikipedia.org/wiki/File:Nci-vol-8182-300_david_cox.jpg

LORD KELVIN (1824-1907)

When you can

measure what you

are speaking about,

and express it in

numbers, you know

something about it.

But when you

cannot your

knowledge is of

a meager and

unsatisfactory kind

(Lord Kelvin)

MEASUREMENT

- Quantitative scale: blood glucose level …

- Qulitative scale: round opacity on chest x-ray …

SOURCES

Interview, standardized questionnaire, laboratory tests,

composed indices … case definition …

MEASUREMENT - ERRORS

TYPE I: above, above, below, above, below, below, above, below, above, above

TYPE II: either above, above, above, above, above, above, above

or below, below, below, below, below, below, below

Repeat measurements and you are Repeat measurements and you

close to the true value (average) are always one way away from

the true value

RANDOM ERROR SYSTEMATIC ERROR

(BIAS)

GOOD EPIDEMIOLOGY PRACTICE

EPIDEMIOLOGICAL STUDY – A MEASURING TOOL

Prevalence of diabetes

Role of sleep deprivation in high blood pressure

Protective significance of face mask in COPD

etc., etc.

MEASUREMENT IS SUBJECT TO ERROR

RANDOM ERROR

Divergence – due to chance alone – of an observation

(measurement) on a sample from the true population value

(estimate ≠ parameter). Three sources:

• Biological variation;

• Sampling error;

• Measurement error.

Given biological variation and limited accuracy

of the measurement random error can be reduced

by increasing the size of the sample

( estimate obtained in a sample composed of all candidates = parameter)

SYSTEMATIC ERROR = BIAS

Systematic divergence (either ‘in plus’ or ‘in minus’) of

an observation (measurement) on a sample from the

true population value (estimate ≠ parameter). Three

principal classes of bias:

•Selection bias;

•Information bias;

•Confounding.

SELECTION BIAS

Distortion resulting from the manner in which subjects

are selected (from population to sample)

• Berkson’s bias (hospital admission bias): affects studies done

in hospitalized populations – the relation found in hospital may

not reflect the one in the population;

• Nonresponse bias: „refusers” are more likely to engage in

unhealthy behaviors

• Healthy worker effect: seriously ill people are unable to join and

remain in the workforce

• …

Way to avoid (minimize) = representative, probability sampling

INFORMATION BIAS

Causes: measurement device defects, inappropriate

questionnaires, inaccurate diagnostic procedures,

Result: placement of a subject in a wrong category

(misclassification)

• Recall bias: sick individuals are more likely to recall hazardous

exposures, events, etc. (mothers of leukemia children remember all,

mothers of healthy children „do not care”)

• Diagnostic suspicion bias: increased diagnostic attention toward

exposed (endometrial cancer versus hormone replacement therapy –

estrogens)

• …

CONFOUNDING

Distortion in an association between a study exposure and disease brought about by the influence of „a third factor”

Confounder:

Is associated with the exposure in question;

Is an independent risk factor for the disease

Confounder → →

↨ Disease

Exposure → ?

Is not intermediate in the causal pathway: exposure - disease

RANDOM ERROR AND SYSTEMATIC ERROR

True Value of the Studied Event = bull’s eye

Result of the Study = dot

Random Error (Imprecision)

Low High

Low

Systemtic

Error (Bias)

High

VALIDITY

• Internal validity (state-of-art measurements on

sample)

• External validity (generalizability)

GOOD EPIDEMIOLOGY PRACTICE !

GOOD EPIDEMIOLOGY PRACTICE

Identify potential sources of errors

Avoid errors

Control errors

Adjust for errors

TOPICS







Core Contributions

1,2,3,4

EPI CONTRIBUTION TO MEDICAL RESEARCH

I – INVESTIGATION INTO NATURAL HISTORY OF DISEASES

Good

Health

Subclinical

Changes

Clinical

Disease

Death

or

Recovery

Incidence

According to sex

According to age

According to …

Occurrence

of diseases

(health events)

Prevalence

According to sex

According to age

According to …


II – DESCRIPTION OF HEALTH STATUS OF POPULATION

Genetic

factors

Genetic

factors

Lifestyle

factors

Good

Health

Onset

of

disease

Ill

Health

Lifestyle

factors

Environ-

mental

factors

Environ-

mental

factors


III – EXPLORATION OF CAUSATION

Treatment

Good

Health

←

←

←

Ill

Health

Diagnostic

Procedures

Health promotion

Preventive measures

Public health services

Medical Care


IV – EVALUATION OF INTERVENTION

TOPICS







EPIDEMIOLOGY and CLINICAL MEDICINE


Patient Population/Group


promotion


HOWEVER

Patient A responds to the treatment T, patient B does not, and patient C …

(what is the true effect of the treatment T ?)

Low level of enzyme E has a prognostic value in patient A and not in patient B

(what is the true diagnostic value of enzyme E ?)

EPIDEMIOLOGY and CLINICAL MEDICINE



promotion


CLINICAL EPIDEMIOLOGY


The science of making predictions about individual

patients by counting clinical events in groups of

similar patients and using strong scientific methods

to ensure that the predictions are accurate.

The purpose of clinical epidemiology is to develop

and apply methods of clinical observation that will

lead to valid conclusions by avoiding being misled

by systamatic error and the play of chance



„Clinical” because it seeks to answer questions and

to guide clinical decisions making with the best

available evidence

„Epidemiology” because many of the methods

used to answer the questions have been developed

by epidemiologists (patient as a member of the

population of patients – disease specific)


CLINICAL EPIDEMIOLOGY ISSUES

Abnormality

Diagnosis

Frequency

Risk

Prognosis

Treatment

Prevention

Cause Source: Fletcher R.W., Fletcher S.W.: Clinical Epidemiology. The essentials .Lippincott Williams & Wilkins 2005

FROM CO-EXISTENCE TO SYNERGISM

EPIDEMIOLOGY vs CLINICAL MEDICINE

EPIDEMIOLOGY ↔ CLINICAL MEDICINE

EPIDEMIOLOGY AND ITS CONTRIBUTION TO MEDICAL...

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