Cohort Research in the US NCI

Daehee Kang

Molecular & Genomic Epidemiology Laboratory (MGEL)

Seoul National University

Genesmutation

polymorphismsEnvironment

Diseases

Gene EnvironmentalInteraction

Etiology of Diseases

multi-factorial and complex, involving several interrelated biochemical pathways under

the influence of multiple genes and environmental exposures.

0

0.5

1

1.5

2

1995 1996 1997 1998 1999 2000 2001

Rate Ratio

Source : Korean Central Cancer Registry, 2003

Standardized Cancer Incidence Ratioamong Females in Korea

Breast 166%

Colorectum 147%

Lung 135%

Liver 132%

Stomach 111%

Cervix 86%

(98% with CIS)

GENOMIC COHORT STUDY DESIGN

Exposure Disease

Exposure &

Genome /

Gene-environment

Molecularly defined

disease

Plasma protein profile

Rx / Molecularly

defined disease

Early detection of

molecularly defined

disease

Outcome

Genome /

Gene-environment Disease

Genomic cohort 연구의 5 critical

components

• Goal and objectives:

– Rationale, uniqueness, competitiveness

• Recruitment

– Study design: efficiency (cost-benefit), feasibility

• Baseline & repeated survey

• Biospecimen collection

• Follow-up and case ascertainment

Cohort Studies in the US NCI

• OEEB (Occupation and Environment)– The Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO)

– The Agricultural Health Study (AHS)

– Shanghai Women's Health Study (SWHS)

– Formaldehyde exposed workers

• REB (Radiation)– The U.S. Radiologic Technologists Health Study (USRT)

• NEB (Nutrition)– ATBC study

– AARP Diet and Health Study

– Nutrition Intervention Trials in Linxian

• Others: Swedish construction, Swedish BPH patients

PLCO Trial: Study Design

• Screening Centers: 10

• Coordinating Center

• Participants: 155,000– Screening arm (6 years)

• Prostate - PSA & DRE

• Lung - x-ray

• Colorectal - sigmoidoscopy

• Ovarian – CA125 & TVU

– Control arm: usual care

• Gender 50:50

• Age 55-74 years

• Recruitment: 1993-2001

• Screening: 1993-2006

• Follow-up to 2015– Annual surveys

– Mortality searches

Studies in PLCO

• Does early detection reduce mortality?

• Clinical epidemiology

• Dietary risk factors

• Other behavioral risk factors

• Genetic risk factors

• Gene-environment interaction

• Blood-based early disease markers

Shanghai Women’s Health Study (SWHS)

• The large-scale population-based cohort study

• 75,049 Chinese women

• 40 - 70 years old

• 1997 – 2000

• urban Shanghai

SWHS: selected characteristics

10,6799,725

7,628

10,543

20,918

15,449

0

5,000

10,000

15,000

20,000

25,000

40-44 45-49 50-54 55-59 60-64 65-70

Age

No.

of

subje

cts

0

5

10

15

20

25

30

%

13

10,173

20,89027,683

8,1478,036

0

5,000

10,000

15,000

20,000

25,000

30,000

No e

duca

tion

Elem

enta

ry

Middle

scho

ol

Hig

h sc

hool

Ove

r colle

ge

Unkn

own

School

No.

of

subje

cts

0

5

10

15

20

25

30

35

40

%

Employment

M anufacturing, 35,367

, 47%

Agricurtural

, 2,054 ,3%

Profess ion

al, 21,389 ,29%

Cons tructio

n, 357 , 0%

Serv ices ,15,493 ,

21%

Unknow n,282 , 0%

Projected number of incidence cancer cases

Cancer site 2004 2008 2013

All sites

Breast

Lung

Liver

Stomach

Colon

Rectum

Esophagus

Bladder

Pancreas

NHL

1,452

353

154

68

124

133

89

18

18

48

29

2,690

697

320

123

209

258

142

37

46

95

86

4,635

1,201

593

207

357

451

245

63

85

166

146

The Nested Case-Control study of Breast Cancer

Matching variables- Age of baseline ±2 years

- Sample collection date <31 days

- Antibiotic use in the past week

- Previous cancer history

- Menopause status

- Post menopausal

1 : 2

74,942 subjects

353 breast

cancer cases

708

controls

• Biospecimen (e.g., lymphocytes, DNA)

• At least 1,500 cancer cases by 2,010

• Active F/U : cancer registry

• Sufficient amounts of baseline information using

standardized tools

• Intention to participate in Consortium

Genomic cohort 연구의 5 critical

components

• Goal and objectives:

– Rationale, uniqueness, competitiveness

• Recruitment

– Study design: efficiency (cost-benefit), feasibility

• Baseline & repeated survey

• Biospecimen collection

• Follow-up and case ascertainment

Genomic cohort 연구의5 critical components

• Goal and objectives:

– Rationales, uniqueness, competitiveness

– Exposure and/or occupation: AHS, USRT,

– Special groups: SWHS, AARP

– Screening efficacy: PLCO

– Preventive trials: ATBC, Linxian

Genomic cohort 연구의5 critical components

• Recruitment & Study Design– Sample size:

• G-E, G-G, G-G-E

– Efficiency (cost-benefit)• Utilize already existing system: PLCO

• Set up new infrastructure: AHS

– Feasibility

– Catchment area (SWHS vs PLCO),

– Representativeness (PLCO vs SWHS)

– Response rate,

SWHS: Sample collection

* Of the 75,221 study participants, 279 women who did not meet the age eligibility requirements for the study were excluded, resulting in a cohort of 74,942 subjects

No. of eligible

subjects

No. of

participants

Response

rate (%)

Baseline survey (1997–2000) 81,170 75,221* 92.7

Specimen collection

Blood

Urine

Exfoliated buccal cells

74,942*

74,942

18,111

56,831

65,754

8,934

75.8

87.7

49.3

Follow-up survey I (2000–2004)

Lifestyle survey

74,942

72,983

74,768

67,163

99.8

92.0

The EPIDEMIOLOGIC component of

Human Genomic Epidemiology

A fundamental question is how large

should a study be?

What is the study trying to accomplish?

• To estimate the overall effect of a SNP or haplotype?

• To detect gene-environment and gene-gene interactions?

• To protect against false positive findings?

Sample size for 80% power to detect range of genetic odds

ratios for varying prevalences of “at risk”genotype

Control/case ratio=1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0

250

500

750

1000

1250

1500

1750

2000

2250

2500

2750

3000

No

. cases (

=N

o.c

on

tro

ls)

Probability of "at risk" genotype

OR=1.5

OR=2.0

OR=3.0

Sample size for 80% power to test for

multiplicative and additive interactions

Power = 80%a-level = 5%P(G) = 50%

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.00

250

500

750

1000

1250

1500

1750

2000

2250

2500

2750

3000

Prevalence of exposure

No.

cas

es(=

no. co

ntro

ls)

Multiplicative

Additive

Genomic Cohort 연구의5 critical components

• Baseline survey– Sufficient amounts of baseline information

– Standardized tools

– Data collection (self-administered vs interview)

– Data entry: OCR, OMR, computer-based

– Related DB

• Repeated survey– Frequency

– How much information be collected

Materials collection in the PLCO Trial

Exam Risk Usual Viable TumorCycle Factors Diet Serum Plasma RBC DNA Cells Sample

Intervention Arm

Baseline X X X X X X

Year 1 X

Year 2 X

Year 3 X X X X X X

Year 4 X X X

Year 5 X X X X

2004-2008 P P

Non-intervention Arm

PX X X (X: in place; P: proposed)

Genomic Cohort 연구의5 critical components

• Biospecimen collection– Types & amount

• Whole blood

• Cryopreserved WB

• Isolated lymphocyte

• EBV transformation

• Serum, plasma, packed RBC

• Sputum, nail, hair, exfoliated cells (filter paper)

• Buccal cell DNA

• Urine

• Fresh frozen tissues

– Storage: LN2

• Follow-up and case ascertainment

SWHS: Sample storage

Vanderbilt University (VU), Shanghai Cancer Institute (SCI), National Cancer Institute (NCI)

VU SCI NCI

Sample from the first 20,000 women

Plasma (4 x 2ml/subject)

WBC (2ml/subject)

RBC (2 x 2ml/subject)

Urine (7 x 4ml, 1 x 20ml/subject)

2

1

1

2

2

0

1

3

0

0

0

4x4ml, 1x20ml

Samples from the remaining women

Plasma (4x 2ml’subject)

WBC (2 x 2ml/subject)

RBC (2 x 2ml/subject)

Urine (6 x 4ml/subject)

Buccal cells (2 x 2ml/subject)

1

0

1

1

1

1

1

0

2

0

2

1

1

3

1

PLCO : Whole Blood

Non-viable cells by days to freeze

0

5

10

15

20

25

30

Day 1 Day 2 Day 3 Day 4

Leukocytes

Lymphocytes

% Non-

viable

40

50

60

70

80

90

100

Fresh

Cryopreserved

1 d < 1 m 6-8 m 18-20 m

PLCO: Cryopreserved Blood:

Lymphocyte Viability (%)

CD45-gated Lymphocytes

Cohort study is NOT merely an

assembly or linkage of existing

records or simply collecting and store

the data