Ora Paltiel, MD, MSc
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Transcript of Ora Paltiel, MD, MSc
Ora Paltiel, MD, MSc
Braun School of Public Health & Community Medicine
Hebrew University of Jerusalem Hadassah Medical Organization
Israel
Epidemiological Reasoning
Using Cancer Statistics
Or, how to use descriptive statistics to raise hypotheses
Issues to be discussed
Validity of data• Reporting• Confounding • Effect
modification
Using Descriptive Data
• Burden of Disease• Planning• Hypothesis raising• Measuring
progress
What are the objectives of epidemiology?
1. To determine the extent of disease (states of health) and/or behaviors in the community.
2. To identify the etiology or the cause/s of a disease and the risk factors - that is, factors that increase a person’s risk for a disease.
3. To study the natural history and prognosis of disease.
4. To evaluate new preventive and therapeutic measures and new modes of health care delivery.
5. To provide the foundation for developing public policy and regulatory decisions relating to public health problems.
Objectives of epidemiology
“When we measure, we know better”
- Center for Disease Control (CDC), Atlanta, Georgia,USA
The epidemiological
tool-box
Kaposi sarcoma in New York
0
20
40
60
80
100
73 74 75 76 77 78 79 80 81 82
Year
No
. of c
ases
The context of disease reporting
Lowest cancer death rate
In the Former Yugoslav Republic of Macedonia, only 6
people per 100,000 of population die from cancer
each year
Lifetime risk of developing breast cancer, 1940-1987
0
2
4
6
8
10
12
1940 1950 1960 1970 1980 1987
perc
ent o
f wom
en
YEARONE IN.…194020195015196014197013198011
1987 9
Source: American Cancer Society, 1991
Lifetime risk of developing breast cancer, 1940-1987 cont’d
Descriptive epidemiology - hypothesis raising rarely provides enough evidence for causation
Person: characteristics for study include:• Age• Gender• Religion• Marital status• Ethnicity• Occupation• Socio-economic class• Heredity vs. Environment
Age-specific rates of Breast Cancer Mortality
Russian Federation
Israel
Population Pyramids 1998
Trends of Cervical Cancer Mortality in Europe and North
America
Age-standardized cervical cancer death rates (and 95% confidence intervals) per
100 000 women in urban Canada by neighbourhood income quintile from 1971
to 1996. Q1 = richest Q5 = poorest .
Place and time
Time trends - raise hypotheses regarding environmental factors or results of medical care
Geographic variation - on small + large scale, environmental genetic factors
Study of migrants: important for separating environmental from genetic factors
Numbers of cases of cancer at 16 anatomical sites in developed and in developing countries, with relative ranks
Lung Cancer Mortality for Women 1998, ASR/100000
Lung Cancer Mortality for men 1998, ASR/100000
Age-adjusted cancer death rates, males by site, US, 1930-1996
Age-adjusted cancer death rates, females by site, US, 1930-1996
Estimated annual percent changes in mortality from all types of cancer in the US over 2 periods 1973-
1990 and 1991-1995, according to age group
0.7
0.3
0
-1.8
-2.1
-1.7
-1.3
-2.6
-3.4
-0.6
1.1
0.9
0.9
-0.9
-1.4
-1.1
-2.2
-3
0.4
0.4
-4 -2 0 2 4
>85
75-84
65-74
55-64
45-54
35-44
25-34
15-24
<15
All ages
Age
gro
up (y
r)
Annual change (%)
1973-19901991-1995
Japanese colon cancer incidence:
Japan Hawaii California
- rate is affected by age at immigration- for breast cancer: 2 generations required for rate
Place and time cont’d
Low
IntermediateHigh
Biases in migrant studies
1) Different reporting
2) Different diagnostic criteria
3) Migrants are selected group
Clinical observati
on
Descriptive data
Hypothesis raising
Where does evidence come from?
Clinical observati
on
Descriptive data
Hypothesis raising
Analytical studies
Hypothesis testing