How do cancer rates in your area

compare to those in other areas?

Understand the use of standardized rates, specific rates, and the limitations of computer mapping

2

Rates

Rates are standardized to a control population

Adjusted

Rates for specific segments/groups of the population (e.g. sex, age, race, cause of death, cancer site)

Specific

Summary rate of the actual number of observed events in a population over a given time period (e.g. all cancer deaths in 2000)

Crude

3

Crude Rates

Estimates the burden of disease in a

population

Not useful for making comparisons between

groups or examining changes over time,

because it depends largely on population

structure

4

Specific Rate Important because outcomes may be profoundly

affected by factors such as age, race, and gender

More precise indicator of risk than a crude rate as

it controls for a particular characteristic of interest

Allows for comparisons between strata or between

groups

5

Age specific rates

Gender specific rates

Race specific rates

Cause specific rates

Site specific rates

Examples of Specific Rates

6

Lung Cancer Deaths by Age Group, United States, 1995

15,420 xxx188,500,741Total

12,356

2,709

303

41

11

Lung Cancer Deaths

12,356 / 31,078,760 = 39.76

2,709 / 42,467,719 = 6.38

303 / 40,873,139 = 0.74

41 / 35,946,635 = 0.11

11 / 38,134,488 = 0.03

Age-Specific Lung Cancer Death Rate

Per 100,000

31,078,76045-54

42,467,71935-44

40,873,13925-34

35,946,63515-24

38,134,4885-14

PopulationAge (years)

Cause Specific Rate = (15,420/188,500,741) x 100,000 = 8.18 / 100,000

7

Adjusted Rate Specific rates are standardized to a control

population and are summarized to produce an

adjusted rate

Used to compare rates of entire populations taking

into account differences in population structure

(e.g., age, gender, race or other variables)

Adjusted rates can be compared if they are

calculated using the same standard population

8

(1) / (2) x (4) = (5)(4)(1) / (2) = (3)(2)(1)

226,500,000xxx45,000115Total

25,700,00015,00010065+

140,300,00025,0001019-64

60,500,0005,00050-18

Expected Number of

Deaths

1980 U.S.

Standard Population

ASRPopulation

at riskCancer Deaths

Age

Creating a cause-specific, age-adjusted death rate using direct standardization

Crude Rate

(115 / 45,000) x 1000

2.56 per 1,000

9

(3) x (4) = (5)(4)(1) / (2) = (3)(2)(1)

288,039226,500,000xxx45,000115Total

171,41925,700,0006.67 per 100015,00010065+

56,120140,300,0000.40 per 100025,0001019-64

60,50060,500,0001.00 per 10005,00050-18

Expected Number of

Deaths

1980 U.S.

Standard Population

ASRPopulation at risk

Cancer Deaths

Age

Age-Adjusted Rate

(288,039 / 226,500,000) x 1000

1.27 per 1,000

Crude Rate

(115 / 45,000) x 1000

2.56 per 1,000

Creating a cause-specific, age-adjusted death rate using direct standardization

10

If crude rate decreases after adjustment,

the study population is older than the

standard population

If crude rate increases after adjustment,

the study population is younger than the

standard population

Comparing Crude and Age-Adjusted Rates

11

Standard Population

By convention, SEER uses the 1970

US standard population

12

Cancer Death Rates by State per 100,000, 2000

212Dist. Of Col.178Massachusetts163Connecticut

195Delaware178Indiana162Washington

193Louisiana 178Illinois160Iowa

192Kentucky 177Virginia159Montana

185Maine177Pennsylvania159Kansas

184West Virginia176Missouri157Wyoming

184Nevada175North Carolina156Minnesota

184Maryland175Georgia156California

182Mississippi173Michigan155South Dakota

181Tennessee172Vermont155North Dakota

181New Hampshire170Oklahoma 155Nebraska

181Arkansas169New York155Arizona

180Ohio168Texas148Idaho

179New Jersey167Alaska146New Mexico

179Alabama166Oregon142Colorado

178South Carolina166Florida133Hawaii

178Rhode Island163Wisconsin122Utah

Average annual mortality 1992-1996, age-adjusted to 1970United States = 170 per 100,000

13

Age-adjusted death rates per 100,000

14

15

Cautions in Comparing Rates

Precision: Rates calculated from an area with a

small population are subject to a large amount of

variation from year to year

Comparability: Rates are affected by differences

in population structure (e.g., a county with more

older women may have higher rates for breast

cancer than a county with more younger women)

16

Advanced Topics

What types of investigations address cancer etiology

and control?

How do we evaluate whether cancer studies are

valid?

How do we assess whether associations between

cancer and risk factors are causal?

How much of the morbidity and mortality from

cancer might be prevented by interventions?

What types of investigations address

cancer etiology and control?

Understand case-control, cohort, and intervention studies

18

Descriptive Studies (to generate hypotheses)

Case-Reports / Series

Cross-Sectional Studies (Prevalence Studies)

measure exposure and disease at the same time

Ecological Studies (Correlational Studies) use group

data rather than data on individuals.

These data cannot be used to assess individual risk –

to do so is to commit Ecological Fallacy

19

Observational Studies

Cohort Studies

Case-Control Studies

Experimental Studies

Randomized Control Trials

(RCT / Clinical Trials)

Analytic Studies (to test hypotheses)

20

Cohort Study Design

A group of people (cohort) without disease are

identified and characterized by an exposure

Group is followed forward over a period of

time to observe the development (incidence)

of the disease of interest

21

Disease-FreeCohort

Single Sample Cohort Study Design

Target Population

Exposed

Not Exposed

Diseased

Not Diseased

Diseased

Not Diseased

Time

22

Multi-Sample Cohort Study Design

Study Cohort

Exposed

Not Exposed

Diseased

Not Diseased

Diseased

Not Diseased

Time

Control Cohort

23

Calculating Outcome Measures

Outcome

D

B

No Disease

(controls)

IN = C / (C+D)CNot Exposed

IE = A / (A+B)AExposed

IncidenceDisease

(cases)Exposure

Relative Risk = IE / IN